WO2018145235A1 - Distributed storage system for use with high-precision maps and application thereof - Google Patents
Distributed storage system for use with high-precision maps and application thereof Download PDFInfo
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- WO2018145235A1 WO2018145235A1 PCT/CN2017/073022 CN2017073022W WO2018145235A1 WO 2018145235 A1 WO2018145235 A1 WO 2018145235A1 CN 2017073022 W CN2017073022 W CN 2017073022W WO 2018145235 A1 WO2018145235 A1 WO 2018145235A1
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
- G01C21/34—Route searching; Route guidance
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- the present invention relates to the field of intelligent driving technology, and in particular, to a storage node of a high-precision map, a high-precision map distributed storage system including the storage node, and a method for deploying a high-precision map in the distributed storage system, which is high in use.
- An intelligent driving system with an accuracy map and a vehicle in which the intelligent driving system is installed.
- Intelligent driving can be divided into automatic driving and driverless driving.
- Autopilot is a man-machine driving. It refers to driving on a certain section of a road and driving by a car on certain sections. The less the person is driving, the higher the degree of automatic driving.
- Driverless driving is not required for driverless driving.
- High-precision maps are one of the necessary technologies for large-scale deployment of unmanned vehicles. High-precision maps are an indispensable technology even for highly automated driving. Because high-precision maps contain rich road traffic information elements, high-precision maps can provide not only high-precision geographic coordinates, but also accurate road shapes, number of lanes, and lanes. Slope, curvature, heading, roll, etc. This combination of rich information and related positioning technology ensures smart driving safety and a good ride experience.
- the general navigation map can be stored offline in the car and provide navigation services to the driver due to the small amount of information.
- the richness of the information described by the high-precision map determines that the high-precision map needs to occupy a relatively large storage space (for example, the high-resolution map formed by the map scanned by Google with lidar is occupied every mile. Approximately 1 gigabyte of storage space). Due to the limited capacity of storage devices that store high-precision maps on smart-drive vehicles, high-precision maps covering a large area cannot be stored entirely on a typical smart-driving car, which directly affects the range of exercise of intelligently-driving vehicles.
- a large area-wide map can be stored on the vehicle.
- the dynamic update of the map is relatively simple. Generally, only the difference between the two map versions needs to be compared and the differentiated part is sent to the vehicle. can.
- the methods of storage, update, and use applied to conventional navigation maps cannot be directly applied.
- the present application provides a storage node of a high-precision map, a high-precision map distributed storage system including the storage node, and a high-precision map deployed in the distributed storage system.
- the method the intelligent driving system using a high-precision map, and the vehicle in which the intelligent driving system is installed.
- the application specifically includes the following contents:
- Embodiment 1 A storage node of a high precision map, comprising:
- An information transceiving module for transmitting and/or receiving subgraphs of high precision maps
- a storage device for storing a sub-atlas of a high-precision map, wherein the sub-atlas includes map information of a traveling direction directly related to the storage node, and each sub-picture corresponds to a traveling direction directly related to the storage node Map information.
- Embodiment 2 The storage node of the high precision map according to embodiment 1, wherein the sub-atlas comprises a direct pre-order storage node of the current storage node (which is a pre-order storage node of the current storage node, and in the pre-order There is no other storage node on the shortest path of the storage node to the current storage node) through the current storage node to the direct subsequent storage node (which is the subsequent storage node of the current storage node, and not on the shortest path from the current storage node to the subsequent storage node) There is high-precision map information of all traveling directions between other storage nodes), and each sub-picture corresponds to high-precision map information of each traveling direction.
- a direct pre-order storage node of the current storage node which is a pre-order storage node of the current storage node, and in the pre-order
- the direct subsequent storage node which is the subsequent storage no
- Embodiment 3 The storage node of embodiment 1, wherein the information transceiving module comprises a wireless communication module and optionally a communication module with a cloud system.
- Embodiment 4 The storage node of embodiment 3, wherein the wireless communication module performs wireless communication using a V2X communication protocol (a communication protocol between the automobile and other objects).
- V2X communication protocol a communication protocol between the automobile and other objects.
- V2X communication protocol is selected from the group consisting of DSRC (Dedicated Short Range Communications), LTE-V (a 4G wireless broadband technology), and 5G ( At least one of the 5th generation mobile communication technologies).
- the storage node according to any one of embodiments 1 to 5, wherein the storage node stores a high-precision map sub-picture from the storage node to a nearest emergency station route, the emergency site storage ratio A high-resolution map submap of a wider area of the storage node.
- the storage node according to any one of embodiments 1 to 5, further comprising a CPU, a GPS system, and a memory.
- Embodiment 8 A distributed storage system for high precision maps, including
- a plurality of storage nodes according to any one of embodiments 1 to 7, wherein each storage node is disposed at a specific location of the high precision map.
- Embodiment 9 The distributed storage system of embodiment 8, wherein the storage node is installed on at least one of an existing road infrastructure and a roadside building or as a new road infrastructure.
- Embodiment 10 The distributed storage system of embodiment 9, wherein the existing road infrastructure is selected from the group consisting of traffic lights, street lights, illegal cameras, street signs, roadside utility poles, and bridges.
- Embodiment 11 The distributed storage system of embodiment 8, wherein the high precision map comprises: high precision geographic location coordinates, and road shape, number of lanes, slope of each lane, curvature, heading, and side One, many or all of the information.
- Embodiment 12 The distributed storage system of embodiment 8, further comprising an emergency site, wherein each storage node stores a high-resolution map sub-map from the current storage node to the nearest emergency site route, the most recent The emergency site stores at least a high-precision map sub-picture stored by all direct subsequent storage nodes of the current storage node.
- Passengers of smart driving vehicles can download more map sets than ordinary storage nodes through these interfaces and human-computer interaction interfaces, such as downloading to the local high-precision atlas that is needed to complete the driving.
- the storage capacity of each storage node can accommodate the size of the stored high-precision map sub-atlas, and each storage node can meet the bandwidth and delay requirements of high-precision map sub-picture transmission.
- Embodiment 15 The distributed storage system of embodiment 12 or 13, wherein the emergency site is the storage node according to any one of embodiments 1 to 7, wherein the emergency site further stores a surrounding thereof A sub-atlas of a high-precision map stored in a storage node.
- Embodiment 17 A method of deploying a high-precision map in the distributed storage system according to any one of embodiments 8-16, comprising the steps of:
- All constructed high precision map subgraphs are stored in a storage node to form the sub-atlas.
- Embodiment 18 The method of embodiment 17, further comprising:
- the step of "searching out all direct preamble nodes and all direct subsequent nodes of the current storage node determined by each direct preamble node" is performed according to the location topology map of the storage node.
- Embodiment 19 The method of embodiment 17, wherein the distributed storage system further comprises an emergency site, the method further comprising: storing, in each storage node, a high precision map from the current storage node to the nearest emergency site route a submap, and a high precision map submap stored by at least all of the direct subsequent storage nodes of the current storage node in the nearest emergency site.
- Embodiment 20 The method of embodiment 17, comprising:
- All constructed high precision map subgraphs are stored in a storage node to form the sub-atlas.
- Embodiment 21 The method of embodiment 17, comprising:
- All constructed high precision map subgraphs are stored in a storage node to form the sub-atlas.
- Embodiment 22 An intelligent driving system using a high-precision map, comprising:
- An intelligent driving storage device for storing a current high-precision map, the current high-precision map including a sub-atlas of a high-precision map, and optionally a frequency of use corresponding to each sub-graph of the high-precision map;
- the intelligent driving system is configured to perform the following steps:
- the smart driving information transceiver module receives a sub-graph of the high-precision map from the current storage node, which is a slave a subgraph of a high-precision map of the direct pre-order storage node heading for the direction of travel of the current storage node;
- Map update step update the subgraph of the received high precision map to the current high precision map
- Execution step The control device controls the vehicle to perform intelligent driving according to the current high-precision map.
- Embodiment 23 The intelligent driving system of embodiment 22, wherein the receiving In the step, the smart driving information transceiver module first receives the version information of the submap of the high-precision map from the current storage node, and determines whether the sub-graph of the same high-precision map exists in the “smart driving storage device”, if the same does not exist. The subgraph of the high-precision map continues to receive the sub-picture of the high-precision map, and if there is a sub-picture of the same high-precision map, the sub-picture of the high-precision map is stopped;
- the usage frequency information of the subgraph of the high precision map is updated.
- version information comprises at least one, a plurality or all of: a subgraph of the high precision map from a direct preamble storage node to a current storage The direction of travel of the node, the date of the update, and the updated version number.
- map updating step further comprises: determining whether a storage space of the smart driving storage device is sufficient, if sufficient, continuing to store, if not, deleting A subgraph of one or more high precision maps until the storage space is sufficient.
- Embodiment 26 The intelligent driving system according to Embodiment 25, wherein in the step of "deleting a sub-picture of one or more high-precision maps", priority is deleted according to usage frequency information of a sub-picture of the high-precision map Use subgraphs of high-precision maps with lower frequency.
- the receiving step further comprises: the smart driving information transceiver module receiving, from the current storage node, a high-precision map of the current storage node traveling to the direction of travel of the nearest emergency site Subgraph.
- the storage node update step after the vehicle drives past the current storage node and heads to a direct subsequent storage node, updates the current storage node to a direct preamble node, and updates the direct subsequent storage node to the current node.
- Embodiment 30 A vehicle in which the intelligent driving system according to any one of Embodiments 22 to 29 is installed.
- the application solves the problem that the high-precision map has large storage requirements and dynamic update on the smart car according to the system of distributed storage of the global high-precision map according to the storage node.
- the method for deploying and updating the global high-precision map provided by the invention can conveniently determine the high-precision map sub-graph of each storage node according to the distribution of the storage nodes and effectively implement the high-accuracy map sub-graph of each storage node when updating the global high-precision map.
- Dynamic update The intelligent driving system of the present application instantly updates the high-precision map required for driving during driving, thereby saving the storage space of the intelligent driving system, and caching the high-precision map sub-picture according to the frequency of use effectively avoids frequent sub-picture downloading.
- it provides a practical and intelligent driving system that uses high-precision maps for intelligent driving.
- Emergency site considerations also add to the safety of smart driving vehicles.
- FIG. 1 is an external schematic diagram of a distributed storage system of a high precision map of the present application.
- FIG. 2 is a schematic structural diagram of a system of a storage node of the present application.
- FIG 3 is a schematic diagram of storage of a local high precision map in a storage node of the present application.
- FIG. 4 is an example of an algorithm flow diagram of a high precision map of the present application deployed in a storage node of a distributed storage system.
- FIG. 5 is an example of an algorithm flow chart of a high-precision map dynamic update of the present application.
- FIG. 6 is an example of a flow chart for updating and using a local high-precision map of the intelligent driving system of the present application.
- the global high-precision map can actually be divided into many small blocks, each of which is a partial sub-map.
- the subgraph of the high precision map refers to a local submap of the global high precision map.
- the intelligent driving car can also travel normally.
- An aspect of the present application provides a storage node of a high-precision map, comprising: an information transceiving module for transmitting and/or receiving a sub-picture of a high-precision map; and a storage device for storing a sub-map of the high-precision map Atlas, wherein the sub-atlas includes map information of a driving direction directly related to the storage node, and each sub-picture corresponds to map information of one driving direction directly related to the storage node.
- the storage node of the present embodiment is an important component of a distributed storage system with high-precision maps. It is used to transmit sub-graphs of high-precision maps to a moving car in real time, which is the key to realizing the intelligent driving method of the present application.
- the car approaches the storage node from different directions, and it is considered that there are different driving directions.
- the storage node and the car that the car has recently passed are The running storage node serves as a driving direction, and the driving direction determines a high-precision map sub-picture, and the high-precision map sub-picture should include high-precision map information reaching all subsequent storage nodes in the traveling direction.
- the sub-atlas includes a direct pre-order storage node of the current storage node (which is a pre-order storage node of the current storage node, and there is no other shortest path on the pre-order storage node reaching the current storage node)
- Storage node high precision of all driving directions between the current storage node and the direct subsequent storage node (which is the subsequent storage node of the current storage node and no other storage nodes on the shortest path from the current storage node to the subsequent storage node)
- Map information each sub-picture corresponds to high-precision map information for each driving direction.
- each direction of travel is determined by a direct pre-order storage node and a current storage node, and each high-precision map sub-picture contains high-precision map information that can reach all direct subsequent storage nodes from the direction of travel.
- the driving direction in the present application is mainly used for planning a reasonable driving route. Therefore, in general, the driving direction described in the present application only includes a reasonable driving direction, and does not include driving without obeying traffic rules. Directions, such as retrograde, reversing across solid lines are not a reasonable direction of travel.
- the information transceiving module includes a wireless communication module and an optional communication module with the cloud system.
- the wireless communication module exchanges information with the moving automobile, and mostly sends high-precision map sub-picture information to the intelligent driving system on the automobile.
- the wireless communication module uses a V2X communication protocol (car and Communication protocol between other objects) performs wireless communication.
- V2X communication protocol car and Communication protocol between other objects
- Other objects herein mainly refer to roadside equipment units, such as storage nodes installed on road infrastructure or on roadside buildings.
- the V2X communication protocol may be selected from the group consisting of DSRC (Dedicated Short Range Communications), LTE-V (a 4G wireless broadband technology), and 5G (5th generation mobile communication technology). At least one of them.
- DSRC Dedicated Short Range Communications
- LTE-V a 4G wireless broadband technology
- 5G 5th generation mobile communication technology
- the storage node stores a high-precision map sub-map from the storage node to the nearest emergency site route, the emergency site storing a high-precision map sub-graph within a wider area than the storage node.
- the emergency site may be one of the storage nodes, except that the storage capacity of the emergency site should be larger than that of the ordinary storage node, and the latest emergency site stores at least the high storage of all direct subsequent storage nodes of the current storage node.
- Accurate map subgraphs and also store a high-resolution map of a wide range of current administrative regions. When the intelligent driving vehicle runs to the current node, it is found that it cannot communicate with the current node.
- the intelligent driving vehicle runs to the emergency site using the recently downloaded high-precision map sub-picture from the storage node to the nearest emergency station route. And to obtain a wider range of stored maps at the emergency site, even in the case of a wide range of storage node downtime, the current driving requirements can be met.
- the storage node further includes a CPU, a GPS system, and a memory.
- the storage node can contain a complete computer and GPS system, so it can contain CPU and memory.
- the distributed storage system of the high precision map includes a master node for storing a global high precision map; and a plurality of the above described storage nodes, wherein each storage node is disposed at a specific location of the high precision map.
- the master node stores a global high-precision map
- the storage node stores a high-resolution map subgraph.
- the global high-precision map refers to the entire high-precision map. In general, the map includes a map including all maps in a country such as China, or all maps including an administrative region such as a province.
- the size of the high-resolution map sub-picture is allocated by the master node from the global high-precision map according to the deployment situation of the storage node.
- the storage node is installed on at least one of an existing road infrastructure and a roadside building or as a new road infrastructure.
- the existing road infrastructure may be selected from one or more of traffic lights, street lights, illegal cameras, street signs, roadside poles, and bridges.
- the high precision map includes: high precision Geographical coordinates, and one or more of the shape of the road, the number of lanes, the slope of each lane, the curvature, the heading, and the roll information.
- the distributed storage system further includes an emergency site, wherein each storage node stores a high-precision map sub-map from the current storage node to the nearest emergency site route, the latest emergency site storing at least A high-resolution map submap stored by all direct subsequent storage nodes of the current storage node.
- the emergency site has strong storage capacity, can store a large range of high-precision map sub-pictures, and can even store high-precision map sub-pictures of an administrative area such as a county or the entire city.
- the emergency site has an interface to access and download a high precision map submap in a network cable and/or USB communication mode.
- Passengers of intelligent driving vehicles can download more map sets than ordinary storage nodes through these interfaces and corresponding human-computer interaction interfaces (human-computer interaction interfaces can be used on smart driving cars or on the emergency site), such as in smart driving.
- human-computer interaction interfaces can be used on smart driving cars or on the emergency site, such as in smart driving.
- the storage space of the car's intelligent driving system can be received, it can even be downloaded to all local high-precision maps required to complete the current driving.
- the density of the plurality of storage nodes on the ground is set according to the information storage density of the high-precision map and the communication efficiency including the bandwidth and the delay, so that the storage capacity of each storage node can be accommodated.
- the size of the stored high-resolution map sub-atlas, and each storage node can meet the bandwidth and delay requirements of high-precision map sub-picture transmission.
- 4G wireless broadband communication protocol storage nodes can be installed at each intersection. On the highway without intersections, storage nodes can be installed at the entrance and exit of the highway.
- 4G wireless broadband technology It can achieve a download speed of about 100 megabits per second, and the speed will be reduced at high speeds.
- the high-precision map occupies 1 Gbyte. It is also possible to download the map in about tens of seconds, and the high-precision map information of the expressway takes up less storage space. Therefore, this layout method can be completed by using the current common communication network. In the case of using high-precision maps of lower precision, a more sparse storage node layout can also be employed. With the improvement of the communication system, in the case of adopting the 5th generation mobile communication network in the future, it is also possible to adopt a more sparse storage node layout manner.
- the emergency site is any one of the storage nodes described in the manner described above, wherein the emergency site also stores a sub-atlas of high precision maps stored in storage nodes around it.
- the emergency site is an enhanced storage node.
- each storage node is configured as an emergency site, that is, each storage node stores a sub-atlas of high-precision maps stored in storage nodes around it.
- each storage node acts not only as a storage node but also as an emergency site, so that if there is a problem with one or two storage nodes in the network of the storage node, it does not affect the operation of the entire distributed storage system, thus The entire distributed storage system has high robustness.
- the primary node is a cloud system
- the cloud system includes a cloud communication module.
- the cloud described in the present application has a meaning that is generally understood by those skilled in the art, and is actually a network.
- the term cloud system refers to a web server.
- the cloud system uses a cloud communication module, so that the storage node accesses the cloud system data (global high-precision map) in any place that can connect to the network.
- the present application also provides a method for deploying a high-precision map in the distributed storage system described in any of the above, comprising the following steps:
- All constructed high precision map subgraphs are stored in a storage node to form the sub-atlas.
- the direct preamble node refers to the predecessor storage node of the current storage node, and there are no other storage nodes on the shortest path of the predecessor storage node to the current storage node.
- a direct subsequent node refers to a subsequent storage node of the current storage node, and there are no other storage nodes on the shortest path from the current storage node to the subsequent storage node.
- all direct subsequent nodes determined by each direct preamble node refers to all direct subsequent nodes that can be reached in the direction of travel determined from the immediate preamble node to the current node.
- each high precision map submap includes high precision map information from a direct preamble node of the current node to all direct subsequent nodes determined by the direct preamble node.
- the method further comprises: forming a location topology map of the storage node, wherein "searching out all direct direct preamble nodes and all direct current nodes determined by each direct preamble node directly The steps of the subsequent nodes are performed according to the location topology map of the storage node.
- the direct preamble node and the direct subsequent node can be searched more conveniently by forming a topology map of the storage node, and the almost complete off-the-shelf graph-based data structure algorithm in the computer field can complete the search.
- the distributed storage system further includes an emergency site, the method further comprising: storing, in each storage node, a high-precision map sub-picture from the current storage node to the nearest emergency site route And storing at least the high-precision map sub-picture stored by all direct subsequent storage nodes of the current storage node in the nearest emergency site.
- the method of the present invention also includes a map update process. Therefore, in some implementations of the method, the method further includes:
- All constructed high precision map subgraphs are stored in a storage node to form the sub-atlas.
- the method of the present invention also includes a storage node deployment update process. Therefore, in some implementations of the method, the method further includes:
- All constructed high precision map subgraphs are stored in a storage node to form the sub-atlas.
- the present application also provides an intelligent driving system using a high-precision map, comprising: an intelligent driving information transceiver module; a control device for controlling vehicle motion; and a smart driving storage device for storing a current high-precision map,
- the current high-precision map includes a sub-atlas of the high-precision map, and optionally the frequency of use corresponding to the sub-picture of each high-precision map;
- the intelligent driving system is configured to perform the following steps: receiving step: installing the In the process of driving the vehicle of the intelligent driving system from the direct pre-order storage node to the current storage node, the intelligent driving information transceiver module receives a sub-graph of the high-precision map from the current storage node, which is from the direct pre-order storage node to the current a sub-picture of a high-precision map of the direction of travel of the storage node; a map update step: updating the sub-picture of the received high-precision map to the current high-precision map; and performing
- the present application also provides an intelligent driving method of an intelligent driving system using a high-precision map, the smart driving reminder comprising: an intelligent driving information transceiver module; and a control device for controlling vehicle motion; And a smart driving storage device for storing a current high-precision map comprising a sub-atlas of a high-precision map, and optionally a frequency of use corresponding to a sub-picture of each high-precision map;
- the method includes the following steps: receiving a step of: receiving, in a process of driving a vehicle with the intelligent driving system from a direct pre-order storage node to a current storage node, the intelligent driving information transceiver module receives a high-precision map sub-sector from a current storage node a sub-picture of a high-precision map that travels from a direct pre-order storage node to a current storage node; a map update step: updating a sub-picture of the received high-precision map to a
- the smart driving information transceiver module first receives version information of a submap of the high precision map from the current storage node, and determines whether the same high precision exists in the “smart driving storage device”.
- the sub-picture of the map if there is no sub-picture of the same high-precision map, the sub-picture of the high-precision map is continued to be received, and if the sub-picture of the same high-precision map exists, the sub-picture of the high-precision map is stopped;
- the usage frequency information of the subgraph of the high precision map is updated.
- the smart driving storage device in the intelligent driving system is often capable of storing a plurality of high-precision map sub-pictures, and the frequently used map sub-pictures can be saved in the smart driving storage device.
- you need to use it you only need to exchange the version number with the current storage node. If it is the latest one, you can download the high-resolution map sub-picture without using it repeatedly, and use it directly, which can save bandwidth. Save energy.
- the frequency information is used, the frequency information is incremented by 1, indicating that the frequency of use is increased once.
- the version information includes at least one, a plurality or all of: a driving direction of the sub-picture of the high-precision map from a direct pre-order storage node to a current storage node, an update date, and an update Version number.
- the map updating step further comprises: determining whether the storage space of the smart driving storage device is sufficient, if sufficient, continuing to store, if not, deleting one or more submaps of the high precision map Until the storage space is sufficient.
- the smart driving system is further configured to be able to share a sub-picture of a high precision map with a surrounding smart driving vehicle.
- the sub-pictures of the high-precision map are used to preferentially delete the sub-high-precision maps with lower frequency.
- the receiving step further comprises: the smart driving information transceiver module receiving, from the current storage node, a sub-graph of the high-precision map of the current storage node heading toward the traveling direction of the nearest emergency station.
- the driving system is further configured to control the vehicle to be stored according to the direct pre-order when the location where the vehicle with the smart driving system is close to the current storage node still does not receive information from the current storage node.
- the smart driving method further includes the step of: controlling the vehicle according to the slave directly when the location of the vehicle in which the smart driving system is installed is close to the current storage node and the information is still not received from the current storage node.
- the intelligent driving system is further configured to perform the step of: storing a node update step: updating the current storage node to direct after the vehicle drives past the current storage node and heads to a direct subsequent storage node Preorder node and update the immediate subsequent storage node to the current node.
- the smart driving method further includes the storage node update step described above.
- the application also provides a vehicle equipped with the intelligent driving system of any of the above.
- FIG. 1 is an external schematic diagram of a distributed storage system of a high precision map of the present application.
- the storage node is mounted on a pole of a street light (2 in Figure 1). If a roadside infrastructure (such as traffic lights, illegal cameras, street lights, etc.) is installed with a storage node to store a high-precision map near the infrastructure (actually a sub-graph of a global high-precision map), the storage node is essentially one A small computer device that stores, receives, transmits (one-to-many), and updates functions such as high-precision map sub-pictures (see Figure 2).
- a roadside infrastructure such as traffic lights, illegal cameras, street lights, etc.
- the intelligent driving car (1 in Figure 1) can download the stored high-precision map sub-picture to the smart driving car through communication with the corresponding current storage node when passing the corresponding infrastructure during driving (4 in Figure 1) .
- the smart driving car is equipped with an intelligent driving system, and can also be “watched” as an enhanced version of the mobile “storage node” that can store, receive, update and share multiple high-precision map sub-pictures.
- the high-precision map stored by the storage nodes on the infrastructure is a partial sub-graph of the global high-precision map, it is designed and deployed to make V2X communication protocols (such as DSRC, LTE-V, and 5G, even at high speeds).
- each smart car only needs to store some small local maps.
- the smart car can continue to obtain the high-precision map needed for the current driving from the roadside storage infrastructure with high-precision map (similar to a partial window). Switch frequently in the global high-precision map).
- the nodes stored on the roadside infrastructure that store high-precision maps actually constitute a network map.
- each storage node only needs to store the direct pre-order storage node during the driving process (there is no other storage node on the way that the pre-order node reaches the current node) through this storage node to the direct subsequent storage node.
- A, B, C, D, E, F, G, H, and K are storage nodes on the road, and the arrows drawn on each road indicate the direction in which the car can be used on the road.
- Storage Node B stores three high-resolution map sub-pictures in three different ways (from left to right, right to left, and top to bottom) that may pass through it. Each smart driving car follows B when it passes.
- Direction of travel Obtain the corresponding high-resolution map subgraph. In each subgraph, a subsection can be uniquely determined from a predecessor node to the current node. It should be noted that some of the road travel directions in Figure 3 are one-way roads, and some are two-way roads.
- the high-precision map sub-pictures directly ignore the travel paths that do not obey the traffic rules.
- the high-resolution map sub-picture acquired by the vehicle from the storage node B should be reached in the direction of travel determined by the direct pre-order storage node A to the storage node B. All direct subsequent storage nodes F, D, E, G, and C.
- a high-precision map sub-picture corresponding to the other two driving directions in which the storage node B exists can be similarly explained according to FIG.
- the information storage density of high-precision maps (the average number of bytes per kilometer) and the communication efficiency (bandwidth and latency) between the vehicle and the infrastructure will affect the denseness of the storage node deployment.
- the cloud system (5 in FIG. 1) can calculate one or more local high-precision map sub-maps that each storage node needs to store according to the global high-precision map and the location topology of the storage node. (For details, see Figure 4), and then the corresponding high-resolution map submap will be deployed to the corresponding storage node through the network (3 in Figure 1).
- the cloud system Whenever the storage node increases or decreases, the cloud system will re-execute the algorithm of Figure 3 to calculate the high-resolution map sub-graph that each storage node needs to deploy after the storage node increases or decreases. At this time, the cloud system only needs to change the sub-picture.
- the storage node can deploy a new high-resolution map submap.
- the high-precision map may be updated at any time as the measurement technology is updated and the road conditions are updated. Therefore, the method of the present application also includes a dynamic update process of the high-precision map. Regardless of the method used to update the global high-precision map, when the global high-precision map is updated, the cloud system calculates which high-resolution map sub-graphs in the distributed storage nodes need to be updated, and then the storage nodes that need to be updated A new high-resolution map subgraph (see Figure 5).
- the intelligent driving system includes: an intelligent driving information transceiver module; a control device for controlling vehicle motion; and a smart driving storage device for storing a current high-precision map, the current high-precision map including high a sub-atlas of the accuracy map, and optionally a frequency of use corresponding to each of the sub-graphs of the high-precision map; the intelligent driving system is configured to perform the following steps: receiving the step: the vehicle from which the intelligent driving system is installed In the process of driving the direct pre-order storage node to the current storage node, the intelligent driving information transceiver module receives a sub-graph of the high-precision map from the current storage node, which is a driving direction from the direct pre-order storage node to the current storage node. Subgraph of high-precision map; map update step: update the subgraph of the received high-precision map to the current high-precision map And the execution step: the control device controls the vehicle
- the storage space on common smart cars should be enough to store some high-precision map sub-pictures, but there is often no global high-precision map.
- the high-precision map storage space on the smart car can be managed according to the frequency of use, that is, those high-precision map sub-pictures that retain high frequency of use if the storage space allows.
- the smart car receives a new high-precision map sub-picture and the storage space on the car is not enough, then those sub-pictures with relatively low frequency used in the previously cached high-precision map sub-pictures will be replaced.
- the larger the storage space on the smart car the more high-resolution map sub-pictures it can cache.
- the high-precision map sub-pictures can be reduced in the frequently-traveled area without the update of the high-precision map.
- the probability of the graph With high-precision maps and corresponding positioning algorithms, smart driving cars can get rich information in high-precision maps for better planning and control, allowing passengers to enjoy a safe travel experience with good user experience (see Figure 6).
- a smart driving vehicle supporting such a contingency plan must draw a specific storage area to store a high-precision map sub-picture from a storage node to some nearby emergency stations, so that the smart driving car can travel safely when a problem occurs. Go to the nearby emergency site.
- storing a high-precision map sub-picture from the current storage node to the nearest emergency site in each storage node can meet the needs of this scenario.
- the algorithms of Figure 4, Figure 5 and Figure 6 need to be corresponding. Expansion.
- FIG. 4 is an example of an algorithm flow diagram of a high precision map of the present application deployed in a storage node of a distributed storage system.
- the process of the algorithm is as follows. First, a global high-precision map is stored in the master node, and the master node acquires a location topology map of the storage node. Then all the storage nodes are processed. In the process of processing each storage node N, each driving direction of the storage node N is processed: in the current running direction, all direct fronts of the storage node N are calculated according to the location topology map of the storage node.
- Sequence node and all direct subsequent nodes (actually each straight According to the global high-precision map, a high-precision map sub-atlas containing N and all its direct pre-order nodes and all direct subsequent nodes in the current driving direction is constructed according to the global high-precision map.
- FIG. 5 is an example of an algorithm flow chart of a high-precision map dynamic update of the present application.
- the process of the algorithm is as follows. First, the storage node set S included in the update area is found according to the update area of the global high-precision map and the topology map of all the storage nodes. A high precision map deployment algorithm similar to that shown in Figure 4 is then performed for all of the storage nodes in S. This algorithm is an example of a map update algorithm.
- FIG. 6 is an example of a flow chart for updating and using a local high-precision map of the intelligent driving system of the present application.
- the process of the algorithm is as follows.
- the smart driving vehicle detects the presence of the front storage node CurNode (ie, the current storage node), it communicates with the current storage node CurNode, and sends the direct preamble node PreNode to the storage node CurNode.
- the smart driving car that is, the intelligent driving system installed on the car
- the high-precision map cache of the smart driving car contains the same version of the high-precision map sub-picture, there is no need to re-download, otherwise the high-resolution map sub-picture is re-downloaded.
- the high-precision map buffer space on the smart-driving car is not enough, the high-precision map with a lower frequency of use in the cache is eliminated according to the size of the high-resolution map sub-picture to be received. Subgraph.
- the intelligently-driving vehicle that is, the intelligent driving system performs intelligent driving based on the current high-precision map.
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Abstract
Provided in the present application is a storage node for use with high-precision maps, comprising: a distributed storage system for a high-precision map of the storage node, a method for deploying a high-precision map in the distributed storage system, a smart driving system which uses a high-precision map, and a vehicle in which the smart driving system is installed. The storage node for use with high-precision maps comprises: an information transceiving module, which is used for sending and/or receiving a sub-map of a high-precision map; and a storage equipment, which is used for storing a sub-map set of the high-precision map, wherein the sub-map set comprises map information of a driving direction which is directly relevant to a present storage node, and each sub-map corresponds to map information of a driving direction which is directly relevant to the present storage node. The technical solution of the present application saves the storage space of a smart driving system, and provides a feasible smart driving system which carries out smart driving by using high-precision maps.
Description
本申请属于智能驾驶技术领域,具体地涉及一种高精度地图的存储节点,包含该存储节点的高精度地图分布式存储***,将高精度地图部署在该分布式存储***中的方法,使用高精度地图的智能驾驶***,以及安装该智能驾驶***的车辆。The present invention relates to the field of intelligent driving technology, and in particular, to a storage node of a high-precision map, a high-precision map distributed storage system including the storage node, and a method for deploying a high-precision map in the distributed storage system, which is high in use. An intelligent driving system with an accuracy map and a vehicle in which the intelligent driving system is installed.
智能驾驶可以分为自动驾驶和无人驾驶。自动驾驶即人机共驾,指在某些路段上由人驾驶而在某些路段上由汽车自动驾驶,需要人驾驶的情况越少则自动驾驶的程度越高。无人驾驶不需要司机,完全由汽车来实现驾驶出行。高精度地图是实现无人驾驶大规模部署的必要技术之一。即使对高度自动驾驶,高精度地图也是不可或缺的技术。由于高精度地图包含了丰富的道路交通信息元素,跟普通的导航电子地图相比,高精度地图不仅能提供高精度的地理位置坐标,还能描述准确的道路形状、车道的数目、各车道的坡度、曲率、航向、侧倾等。这些丰富的信息和相关定位技术的结合可以确保智能驾驶的安全性和良好的乘坐体验。Intelligent driving can be divided into automatic driving and driverless driving. Autopilot is a man-machine driving. It refers to driving on a certain section of a road and driving by a car on certain sections. The less the person is driving, the higher the degree of automatic driving. Driverless driving is not required for driverless driving. High-precision maps are one of the necessary technologies for large-scale deployment of unmanned vehicles. High-precision maps are an indispensable technology even for highly automated driving. Because high-precision maps contain rich road traffic information elements, high-precision maps can provide not only high-precision geographic coordinates, but also accurate road shapes, number of lanes, and lanes. Slope, curvature, heading, roll, etc. This combination of rich information and related positioning technology ensures smart driving safety and a good ride experience.
一般的导航地图由于信息量比较小,可以离线存储在汽车上并给司机提供导航服务。与一般的导航地图不同,高精度地图所描述信息的丰富性决定了高精度地图需要占用比较大的存储空间(例如谷歌用激光雷达扫描出的图经过标注后形成的高精度地图每英里需要占用大约1G字节的存储空间)。由于智能驾驶汽车上存储高精度地图的存储设备容量有限,覆盖一个较大区域的高精度地图无法在一般的智能驾驶汽车上被全部存储,这将直接影响智能驾驶车辆的行使范围。而在智能汽车行驶过程中通过云端的全局高精度地图的动态更新需要耗费很大的带宽并产生较长的延迟,所以在实际应用场景中这种动态更新方法的可行性比较小。智能驾驶的推广急需一种实用的方法来实现智能驾驶汽车上高精度地图的有效动态更新。
The general navigation map can be stored offline in the car and provide navigation services to the driver due to the small amount of information. Different from the general navigation map, the richness of the information described by the high-precision map determines that the high-precision map needs to occupy a relatively large storage space (for example, the high-resolution map formed by the map scanned by Google with lidar is occupied every mile. Approximately 1 gigabyte of storage space). Due to the limited capacity of storage devices that store high-precision maps on smart-drive vehicles, high-precision maps covering a large area cannot be stored entirely on a typical smart-driving car, which directly affects the range of exercise of intelligently-driving vehicles. However, the dynamic update of the global high-precision map through the cloud during the driving process of the smart car requires a large bandwidth and generates a long delay, so the feasibility of the dynamic update method is relatively small in practical application scenarios. The promotion of intelligent driving urgently requires a practical method to achieve effective dynamic update of high-precision maps on smart driving vehicles.
对于常规的导航地图,车辆上可以存储很大区域范围的地图,地图的动态更新相对来说也比较简单,一般只需要比较两个地图版本之间的差异并把差异化的部分发送到车辆上就可以。但对于高精度地图,应用在常规导航地图上的存储、更新和使用的方法将无法被直接应用。For a conventional navigation map, a large area-wide map can be stored on the vehicle. The dynamic update of the map is relatively simple. Generally, only the difference between the two map versions needs to be compared and the differentiated part is sent to the vehicle. can. However, for high-precision maps, the methods of storage, update, and use applied to conventional navigation maps cannot be directly applied.
发明内容Summary of the invention
针对现有技术中存在的一种或多种问题,本申请提供一种高精度地图的存储节点,包含该存储节点的高精度地图分布式存储***,将高精度地图部署在该分布式存储***中的方法,使用高精度地图的智能驾驶***,以及安装该智能驾驶***的车辆。For one or more problems existing in the prior art, the present application provides a storage node of a high-precision map, a high-precision map distributed storage system including the storage node, and a high-precision map deployed in the distributed storage system. The method, the intelligent driving system using a high-precision map, and the vehicle in which the intelligent driving system is installed.
本申请具体地包含如下内容:The application specifically includes the following contents:
实施方式1.一种高精度地图的存储节点,其包括:Embodiment 1. A storage node of a high precision map, comprising:
信息收发模块,其用于发送和/或接收高精度地图的子图;和An information transceiving module for transmitting and/or receiving subgraphs of high precision maps; and
存储设备,其用于存储高精度地图的子图集,其中所述子图集包括与本存储节点直接相关的行驶方向的地图信息,每个子图对应于与本存储节点直接相关的一个行驶方向的地图信息。a storage device for storing a sub-atlas of a high-precision map, wherein the sub-atlas includes map information of a traveling direction directly related to the storage node, and each sub-picture corresponds to a traveling direction directly related to the storage node Map information.
实施方式2.根据实施方式1所述的高精度地图的存储节点,其中所述子图集包括当前存储节点的直接前序存储节点(是当前存储节点的前序存储节点,并且在该前序存储节点到达当前存储节点的最短路径上不存在其它存储节点)通过当前存储节点到直接后续存储节点(是当前存储节点的后续存储节点,并且在当前存储节点到该后续存储节点的最短路径上不存在其它存储节点)间的所有行驶方向的高精度地图信息,每个子图对应于每个行驶方向的高精度地图信息。 Embodiment 2. The storage node of the high precision map according to embodiment 1, wherein the sub-atlas comprises a direct pre-order storage node of the current storage node (which is a pre-order storage node of the current storage node, and in the pre-order There is no other storage node on the shortest path of the storage node to the current storage node) through the current storage node to the direct subsequent storage node (which is the subsequent storage node of the current storage node, and not on the shortest path from the current storage node to the subsequent storage node) There is high-precision map information of all traveling directions between other storage nodes), and each sub-picture corresponds to high-precision map information of each traveling direction.
实施方式3.根据实施方式1所述的存储节点,其中所述信息收发模块包括无线通讯模块和任选的与云端***的通信模块。 Embodiment 3. The storage node of embodiment 1, wherein the information transceiving module comprises a wireless communication module and optionally a communication module with a cloud system.
实施方式4.根据实施方式3所述的存储节点,其中所述无线通讯模块采用V2X的通讯协议(汽车与其它物体之间的通信协议)进行无线通信。Embodiment 4. The storage node of embodiment 3, wherein the wireless communication module performs wireless communication using a V2X communication protocol (a communication protocol between the automobile and other objects).
实施方式5.根据实施方式4所述的存储节点,其中所述V2X的通讯协议选自DSRC(Dedicated Short Range Communications,专用短程通信技术)、LTE-V(一种4G无线宽带技术)和5G(第5代移动通讯技术)中的至少一种。
The storage node according to embodiment 4, wherein the V2X communication protocol is selected from the group consisting of DSRC (Dedicated Short Range Communications), LTE-V (a 4G wireless broadband technology), and 5G ( At least one of the 5th generation mobile communication technologies).
实施方式6.根据实施方式1至5中任一项所述的存储节点,其中所述存储节点中存储从本存储节点到最近的应急站点路线的高精度地图子图,所述应急站点存储比存储节点更宽区域范围内的高精度地图子图。The storage node according to any one of embodiments 1 to 5, wherein the storage node stores a high-precision map sub-picture from the storage node to a nearest emergency station route, the emergency site storage ratio A high-resolution map submap of a wider area of the storage node.
实施方式7.根据实施方式1至5中任一项所述的存储节点,其还包括CPU、GPS***和内存。The storage node according to any one of embodiments 1 to 5, further comprising a CPU, a GPS system, and a memory.
实施方式8.高精度地图的分布式存储***,其包括Embodiment 8. A distributed storage system for high precision maps, including
主节点,其用于存储全局高精度地图;和a master node for storing global high precision maps; and
多个根据实施方式1至7中任一项所述的存储节点,其中每个存储节点设置于高精度地图的具***置处。A plurality of storage nodes according to any one of embodiments 1 to 7, wherein each storage node is disposed at a specific location of the high precision map.
实施方式9.根据实施方式8所述的分布式存储***,其中所述存储节点安装于既有的道路基础设施和路边的建筑物中的至少一种上或者作为新的道路基础设施安装。Embodiment 9. The distributed storage system of embodiment 8, wherein the storage node is installed on at least one of an existing road infrastructure and a roadside building or as a new road infrastructure.
实施方式10.根据实施方式9所述的分布式存储***,其中所述既有的道路基础设施选自红绿灯、路灯、违章摄像机、路牌、路边电线杆、和桥梁的一种或多种。Embodiment 10. The distributed storage system of embodiment 9, wherein the existing road infrastructure is selected from the group consisting of traffic lights, street lights, illegal cameras, street signs, roadside utility poles, and bridges.
实施方式11.根据实施方式8所述的分布式存储***,其中所述高精度地图包括:高精度的地理位置坐标,以及道路形状、车道的数目、各车道的坡度、曲率、航向、和侧倾信息的一种、多种或者全部。Embodiment 11. The distributed storage system of embodiment 8, wherein the high precision map comprises: high precision geographic location coordinates, and road shape, number of lanes, slope of each lane, curvature, heading, and side One, many or all of the information.
实施方式12.根据实施方式8所述的分布式存储***,还包括应急站点,其特征在于每个存储节点中存储从当前存储节点到最近的应急站点路线的高精度地图子图,所述最近的应急站点至少存储当前存储节点的所有直接后续存储节点所存储的高精度地图子图。Embodiment 12. The distributed storage system of embodiment 8, further comprising an emergency site, wherein each storage node stores a high-resolution map sub-map from the current storage node to the nearest emergency site route, the most recent The emergency site stores at least a high-precision map sub-picture stored by all direct subsequent storage nodes of the current storage node.
实施方式13.根据实施方式12所述的分布式存储***,其中所述应急站点具有以网线和/或USB通讯方式访问并下载高精度地图子图的接口。智能驾驶车的乘客可以通过这些接口及人机交互界面下载比普通的存储节点更多的地图集,比如可以下载到完成行驶所需要的局部高精度地图集。The distributed storage system of embodiment 12, wherein the emergency site has an interface for accessing and downloading a high-resolution map sub-picture in a network cable and/or USB communication manner. Passengers of smart driving vehicles can download more map sets than ordinary storage nodes through these interfaces and human-computer interaction interfaces, such as downloading to the local high-precision atlas that is needed to complete the driving.
实施方式14.根据实施方式8所述的分布式存储***,其中所述多个存储节点在地面的设置稠密程度根据高精度地图的信息存储密度与包括带宽和延时在内的通讯效率设置,使得:每个存储节点的存储容量能够容纳所存储的高精度地图子图集的大小,并且每个存储节点能够满足高精度地图子图传输的带宽和延时需求。
The distributed storage system of embodiment 8, wherein the density of the plurality of storage nodes on the ground is set according to an information storage density of the high-precision map and a communication efficiency including a bandwidth and a delay. The storage capacity of each storage node can accommodate the size of the stored high-precision map sub-atlas, and each storage node can meet the bandwidth and delay requirements of high-precision map sub-picture transmission.
实施方式15.根据实施方式12或13所述的分布式存储***,其中所述应急站点是根据实施方式1至7中任一项所述的存储节点,其中所述应急站点还存储其周围的存储节点中所存储的高精度地图的子图集。Embodiment 15. The distributed storage system of embodiment 12 or 13, wherein the emergency site is the storage node according to any one of embodiments 1 to 7, wherein the emergency site further stores a surrounding thereof A sub-atlas of a high-precision map stored in a storage node.
实施方式16.根据实施方式8所述的分布式存储***,其中所述主节点是云端***,其中所述云端***包括云端通讯模块。The distributed storage system of embodiment 8, wherein the primary node is a cloud system, wherein the cloud system comprises a cloud communication module.
实施方式17.一种将高精度地图部署在实施方式8-16中任一项所述的分布式存储***中的方法,包括如下步骤:Embodiment 17. A method of deploying a high-precision map in the distributed storage system according to any one of embodiments 8-16, comprising the steps of:
在主节点中存储全局高精度地图;Store a global high-precision map in the primary node;
对于每个存储节点(称为当前存储节点),执行如下过程:For each storage node (called the current storage node), perform the following process:
搜索出所有直接前序节点和每个直接前序节点所确定的当前存储节点的所有直接后续节点,对于每个直接前序节点到当前存储节点的行驶方向,构造出从该直接前序节点通过当前存储节点至其所有直接后续节点的高精度地图子图,Searching all the direct subsequent nodes of the current storage node determined by all the direct preamble nodes and each direct preamble node, for each direct preamble node to the current storage node's traveling direction, constructing a pass from the direct preamble node a high-resolution map submap of the current storage node to all its immediate subsequent nodes,
将所有构造的高精度地图子图存储于存储节点中,形成所述子图集。All constructed high precision map subgraphs are stored in a storage node to form the sub-atlas.
实施方式18.根据实施方式17的方法,还包括:Embodiment 18. The method of embodiment 17, further comprising:
形成存储节点的位置拓扑图,Forming a location topology map of the storage node,
其中,“搜索出所有直接前序节点和每个直接前序节点所确定的当前存储节点所有直接后续节点”的步骤根据存储节点的位置拓扑图进行。The step of "searching out all direct preamble nodes and all direct subsequent nodes of the current storage node determined by each direct preamble node" is performed according to the location topology map of the storage node.
实施方式19.根据实施方式17的方法,其中所述分布式存储***还包括应急站点,所述方法还包括:在每个存储节点中存储从当前存储节点到最近的应急站点路线的高精度地图子图,和在所述最近的应急站点中至少存储当前存储节点的所有直接后续存储节点所存储的高精度地图子图。Embodiment 19. The method of embodiment 17, wherein the distributed storage system further comprises an emergency site, the method further comprising: storing, in each storage node, a high precision map from the current storage node to the nearest emergency site route a submap, and a high precision map submap stored by at least all of the direct subsequent storage nodes of the current storage node in the nearest emergency site.
实施方式20.根据实施方式17的方法,其中包括:Embodiment 20. The method of embodiment 17, comprising:
地图更新过程:Map update process:
在主节点中使用更新区域的高精度地图替换该区域中原有的高精度地图;Replace the original high-precision map in the area with the high-precision map of the update area in the master node;
对更新区域中的每个存储节点,执行如下过程:For each storage node in the update area, perform the following process:
搜索出当前存储节点的所有直接前序节点和每个直接前序节点所确定的当前存储节点的所有直接后续节点,对于每个直接前序节点到当前存储节点的行驶方向,构造出从当前存储节点的该直接前序节
点通过当前存储节点至当前存储节点的所有直接后续节点的高精度地图子图,Searching all direct immediate nodes of the current storage node and all direct subsequent nodes of the current storage node determined by each direct preamble node, constructing a current storage from each direct preamble node to the current storage node The direct preamble of the node
Pointing through the high-precision map submap of the current storage node to all direct subsequent nodes of the current storage node,
将所有构造的高精度地图子图存储于存储节点中,形成所述子图集。All constructed high precision map subgraphs are stored in a storage node to form the sub-atlas.
实施方式21.根据实施方式17的方法,其中包括:Embodiment 21. The method of embodiment 17, comprising:
存储节点部署更新过程:Storage node deployment update process:
对于新的存储节点集合中的每个存储节点,重新搜索出所有直接前序节点和每个直接前序节点所确定的当前存储节点的所有直接后续节点,将重新搜索到的结果与更新前的结果进行对比,For each storage node in the new storage node set, re-search all direct forward nodes and all direct subsequent nodes of the current storage node determined by each direct pre-order node, and re-search the results with the pre-update The results are compared,
对于“所有直接前序节点和每个直接前序节点所确定的当前存储节点的所有直接后续节点”有变化的存储节点,执行如下过程:For a storage node that has a change in "all direct successor nodes and all direct subsequent nodes of the current storage node determined by each direct preamble node", the following process is performed:
对于每个直接前序节点到当前存储节点的行驶方向,构造出从该直接前序节点通过当前存储节点至其所有直接后续节点的高精度地图子图,For each direct preamble node to the current storage node's driving direction, construct a high-precision map sub-picture from the direct pre-order node through the current storage node to all its immediate subsequent nodes,
将所有构造的高精度地图子图存储于存储节点中,形成所述子图集。All constructed high precision map subgraphs are stored in a storage node to form the sub-atlas.
实施方式22.一种使用高精度地图的智能驾驶***,包括:Embodiment 22. An intelligent driving system using a high-precision map, comprising:
智能驾驶信息收发模块;Intelligent driving information transceiver module;
控制设备,其用于控制车辆运动;和a control device for controlling vehicle motion; and
智能驾驶存储设备,其用于存储当前高精度地图,所述当前高精度地图包括高精度地图的子图集,和任选的每个高精度地图的子图所对应的使用频次;An intelligent driving storage device for storing a current high-precision map, the current high-precision map including a sub-atlas of a high-precision map, and optionally a frequency of use corresponding to each sub-graph of the high-precision map;
所述智能驾驶***配置为执行如下步骤:The intelligent driving system is configured to perform the following steps:
接收步骤:在安装有所述智能驾驶***的车辆从直接前序存储节点驶向当前存储节点的过程中,所述智能驾驶信息收发模块从当前存储节点接收高精度地图的子图,其为从直接前序存储节点驶向当前存储节点的行驶方向的高精度地图的子图;Receiving step: in the process of driving the vehicle with the intelligent driving system from the direct pre-order storage node to the current storage node, the smart driving information transceiver module receives a sub-graph of the high-precision map from the current storage node, which is a slave a subgraph of a high-precision map of the direct pre-order storage node heading for the direction of travel of the current storage node;
地图更新步骤:将接收到的高精度地图的子图更新到当前高精度地图中;和Map update step: update the subgraph of the received high precision map to the current high precision map; and
执行步骤:控制设备根据当前的高精度地图控制车辆进行智能驾驶。Execution step: The control device controls the vehicle to perform intelligent driving according to the current high-precision map.
实施方式23.根据实施方式22所述的智能驾驶***,其中在所述接收
步骤中,所述智能驾驶信息收发模块首先从当前存储节点接收高精度地图的子图的版本信息,判断“智能驾驶存储设备”中是否存在相同的高精度地图的子图,如果不存在相同的高精度地图的子图,则继续进行高精度地图的子图的接收,如果存在相同的高精度地图的子图,则停止接收高精度地图的子图;Embodiment 23. The intelligent driving system of embodiment 22, wherein the receiving
In the step, the smart driving information transceiver module first receives the version information of the submap of the high-precision map from the current storage node, and determines whether the sub-graph of the same high-precision map exists in the “smart driving storage device”, if the same does not exist. The subgraph of the high-precision map continues to receive the sub-picture of the high-precision map, and if there is a sub-picture of the same high-precision map, the sub-picture of the high-precision map is stopped;
更新所述高精度地图的子图的使用频次信息。The usage frequency information of the subgraph of the high precision map is updated.
实施方式24.根据实施方式23所述的智能驾驶***,其中所述版本信息包括以下的至少一种,多种或者全部:该高精度地图的子图的从直接前序存储节点驶向当前存储节点的行驶方向,更新日期,和更新的版本号。The smart driving system of embodiment 23, wherein the version information comprises at least one, a plurality or all of: a subgraph of the high precision map from a direct preamble storage node to a current storage The direction of travel of the node, the date of the update, and the updated version number.
实施方式25.根据实施方式22所述的智能驾驶***,其中所述地图更新步骤还包括:判断所述智能驾驶存储设备的存储空间是否足够,如果足够,则继续进行存储,如果不够,则删除一个或多个高精度地图的子图直到存储空间足够为止。The intelligent driving system of embodiment 22, wherein the map updating step further comprises: determining whether a storage space of the smart driving storage device is sufficient, if sufficient, continuing to store, if not, deleting A subgraph of one or more high precision maps until the storage space is sufficient.
实施方式26.根据实施方式25所述的智能驾驶***,其中在所述“删除一个或多个高精度地图的子图”的步骤中,根据高精度地图的子图的使用频次信息,优先删除使用频次较低的高精度地图的子图。[Embodiment 26] The intelligent driving system according to Embodiment 25, wherein in the step of "deleting a sub-picture of one or more high-precision maps", priority is deleted according to usage frequency information of a sub-picture of the high-precision map Use subgraphs of high-precision maps with lower frequency.
实施方式27.根据实施方式22所述的智能驾驶***,其中接收步骤还包括:所述智能驾驶信息收发模块从当前存储节点接收当前存储节点驶向最近的应急站点的行驶方向的高精度地图的子图。The intelligent driving system of embodiment 22, wherein the receiving step further comprises: the smart driving information transceiver module receiving, from the current storage node, a high-precision map of the current storage node traveling to the direction of travel of the nearest emergency site Subgraph.
实施方式28.根据实施方式27所述的智能驾驶***,其中所述驾驶***还配置为当所述安装有所述智能驾驶***的车辆接近当前存储节点的位置仍然没有从当前存储节点接收到信息时,控制车辆根据从直接前序存储节点驶向最近的应急站点的行驶方向的高精度地图的子图驶向最近的应急站点。The intelligent driving system of embodiment 27, wherein the driving system is further configured to not receive information from a current storage node when the vehicle in which the intelligent driving system is installed is close to a current storage node At the time, the control vehicle is driven to the nearest emergency site based on a sub-graph of a high-precision map that travels from the immediate pre-order storage node to the direction of travel of the nearest emergency site.
实施方式29.根据实施方式22所述的智能驾驶***,其中所述智能驾驶***还配置为执行如下步骤:The intelligent driving system of embodiment 22, wherein the intelligent driving system is further configured to perform the following steps:
存储节点更新步骤:在所述车辆驶过当前存储节点后并且驶向一个直接后续存储节点时,将该当前存储节点更新为直接前序节点,并且将该直接后续存储节点更新为当前结点。The storage node update step: after the vehicle drives past the current storage node and heads to a direct subsequent storage node, updates the current storage node to a direct preamble node, and updates the direct subsequent storage node to the current node.
实施方式30.安装有实施方式22至29中任一项所述的智能驾驶***的车辆。
Embodiment 30. A vehicle in which the intelligent driving system according to any one of Embodiments 22 to 29 is installed.
本申请把全局高精度地图按存储节点分布式存储的***解决了高精度地图在智能汽车上存储需求大和动态更新困难的问题。本发明提供的全局高精度地图的部署和更新方法可以方便地按照存储节点的分布决定各存储节点的高精度地图子图并在全局高精度地图更新时有效地实现各存储节点高精度地图子图的动态更新。本申请的智能驾驶***在行驶过程中即时更新行驶所需的高精度地图,从而节省了智能驾驶***的存储空间,按使用频度来缓存高精度地图子图有效地避免了频繁的子图下载,从而提供了一种确实可行的利用高精度地图进行智能驾驶的智能驾驶***。应急站点的考虑也为智能驾驶汽车的安全行驶增加了保证。The application solves the problem that the high-precision map has large storage requirements and dynamic update on the smart car according to the system of distributed storage of the global high-precision map according to the storage node. The method for deploying and updating the global high-precision map provided by the invention can conveniently determine the high-precision map sub-graph of each storage node according to the distribution of the storage nodes and effectively implement the high-accuracy map sub-graph of each storage node when updating the global high-precision map. Dynamic update. The intelligent driving system of the present application instantly updates the high-precision map required for driving during driving, thereby saving the storage space of the intelligent driving system, and caching the high-precision map sub-picture according to the frequency of use effectively avoids frequent sub-picture downloading. Thus, it provides a practical and intelligent driving system that uses high-precision maps for intelligent driving. Emergency site considerations also add to the safety of smart driving vehicles.
为了更清楚地说明本公开实施例的技术方案,下面将对实施例的附图作简单地介绍,显而易见地,下面描述中的附图仅仅涉及本公开的一些实施例,而非对本公开的限制。In order to more clearly illustrate the technical solutions of the embodiments of the present disclosure, the drawings of the embodiments will be briefly described below. It is obvious that the drawings in the following description relate only to some embodiments of the present disclosure, and are not to limit the disclosure. .
图1是本申请的高精度地图的分布式存储***的外部示意图。1 is an external schematic diagram of a distributed storage system of a high precision map of the present application.
图2是本申请的存储节点的***结构示意图。2 is a schematic structural diagram of a system of a storage node of the present application.
图3是本申请的存储节点内局部高精度地图的存储示意图。3 is a schematic diagram of storage of a local high precision map in a storage node of the present application.
图4是本申请的将高精度地图部署在分布式存储***的存储节点中的算法流程图示例。4 is an example of an algorithm flow diagram of a high precision map of the present application deployed in a storage node of a distributed storage system.
图5是本申请的高精度地图动态更新的算法流程图示例。FIG. 5 is an example of an algorithm flow chart of a high-precision map dynamic update of the present application.
图6是本申请的智能驾驶***的局部高精度地图的更新和使用流程图示例。6 is an example of a flow chart for updating and using a local high-precision map of the intelligent driving system of the present application.
为使本公开实施例的目的、技术方案和优点更加清楚,下面将结合本公开实施例的附图,对本公开实施例的技术方案进行清楚、完整地描述。显然,所描述的实施例是本公开的一部分实施例,而不是全部的实施例。基于所描述的本公开的实施例,本领域普通技术人员在无需创造性劳动的前提下所获得的所有其他实施例,都属于本公开保护的范围。The technical solutions of the embodiments of the present disclosure will be clearly and completely described below in conjunction with the drawings of the embodiments of the present disclosure. It is apparent that the described embodiments are part of the embodiments of the present disclosure, and not all of the embodiments. All other embodiments obtained by a person of ordinary skill in the art based on the described embodiments of the present disclosure without departing from the scope of the invention are within the scope of the disclosure.
全局的高精度地图其实可以分成很多个小块,每个小块都是一个局部子地图。从理论上说,不管在哪个地理位置,只要每辆智能驾驶汽车里面存储
着当前位置附近的若干个高精度地图子图,那么这辆智能驾驶汽车就能够正常行驶。因此在本申请中,高精度地图的子图是指全局的高精度地图的局部子地图。在理想的情况下,只要智能驾驶汽车能不断获取规划好的行驶路径上从当前位置到前面一段距离内的高精度地图子图,智能驾驶汽车也能够正常行驶。The global high-precision map can actually be divided into many small blocks, each of which is a partial sub-map. In theory, no matter which location, as long as each smart car is stored inside
With a number of high-resolution map subgraphs near the current location, the smart car can drive normally. Therefore, in the present application, the subgraph of the high precision map refers to a local submap of the global high precision map. In an ideal situation, as long as the smart driving car can continuously obtain high-precision map sub-pictures from the current position to the previous distance on the planned driving path, the intelligent driving car can also travel normally.
本申请的一方面提供一种高精度地图的存储节点,其包括:信息收发模块,其用于发送和/或接收高精度地图的子图;和存储设备,其用于存储高精度地图的子图集,其中所述子图集包括与本存储节点直接相关的行驶方向的地图信息,每个子图对应于与本存储节点直接相关的一个行驶方向的地图信息。本实施方式的存储节点是高精度地图的分布式存储***的重要组成部分,它用来实时向行驶中的汽车发送高精度地图的子图,是实现本申请的智能驾驶方法的关键所在。在每个存储节点处,汽车从不同的方向接近存储节点,就认为是存在不同的行驶方向,为了便于在所存储的高精度地图子图中进行区分,将汽车最近驶过的存储节点与汽车驶向的存储节点作为一个行驶方向,该行驶方向确定一个高精度地图子图,该高精度地图子图中应该包含该行驶方向上到达所有后续存储节点的高精度地图信息。An aspect of the present application provides a storage node of a high-precision map, comprising: an information transceiving module for transmitting and/or receiving a sub-picture of a high-precision map; and a storage device for storing a sub-map of the high-precision map Atlas, wherein the sub-atlas includes map information of a driving direction directly related to the storage node, and each sub-picture corresponds to map information of one driving direction directly related to the storage node. The storage node of the present embodiment is an important component of a distributed storage system with high-precision maps. It is used to transmit sub-graphs of high-precision maps to a moving car in real time, which is the key to realizing the intelligent driving method of the present application. At each storage node, the car approaches the storage node from different directions, and it is considered that there are different driving directions. In order to facilitate the distinction among the stored high-precision map sub-pictures, the storage node and the car that the car has recently passed are The running storage node serves as a driving direction, and the driving direction determines a high-precision map sub-picture, and the high-precision map sub-picture should include high-precision map information reaching all subsequent storage nodes in the traveling direction.
在一些实施方式中,所述子图集包括当前存储节点的直接前序存储节点(是当前存储节点的前序存储节点,并且在该前序存储节点到达当前存储节点的最短路径上不存在其它存储节点)通过当前存储节点到直接后续存储节点(是当前存储节点的后续存储节点,并且在当前存储节点到该后续存储节点的最短路径上不存在其它存储节点)间的所有行驶方向的高精度地图信息,每个子图对应于每个行驶方向的高精度地图信息。由此可见,每个行驶方向由一个直接前序存储节点和当前存储节点所确定,而每个高精度地图子图包含从该行驶方向能够到达所有直接后续存储节点的高精度地图信息。本申请中的行驶方向主要是用来规划合理的行驶路线用的,因此一般而言,本申请中所述的行驶方向仅包含合理的行驶方向,并不包含不遵守交通规则的情况下的行驶方向,比如逆行,跨实线倒车等都不算是合理行驶方向。In some embodiments, the sub-atlas includes a direct pre-order storage node of the current storage node (which is a pre-order storage node of the current storage node, and there is no other shortest path on the pre-order storage node reaching the current storage node) Storage node) high precision of all driving directions between the current storage node and the direct subsequent storage node (which is the subsequent storage node of the current storage node and no other storage nodes on the shortest path from the current storage node to the subsequent storage node) Map information, each sub-picture corresponds to high-precision map information for each driving direction. It can be seen that each direction of travel is determined by a direct pre-order storage node and a current storage node, and each high-precision map sub-picture contains high-precision map information that can reach all direct subsequent storage nodes from the direction of travel. The driving direction in the present application is mainly used for planning a reasonable driving route. Therefore, in general, the driving direction described in the present application only includes a reasonable driving direction, and does not include driving without obeying traffic rules. Directions, such as retrograde, reversing across solid lines are not a reasonable direction of travel.
在一些实施方式中,所述信息收发模块包括无线通讯模块和任选的与云端***的通信模块。所述无线通讯模块与行驶中的汽车进行信息交换,最主要是向汽车上的智能驾驶***发送高精度地图子图信息。In some embodiments, the information transceiving module includes a wireless communication module and an optional communication module with the cloud system. The wireless communication module exchanges information with the moving automobile, and mostly sends high-precision map sub-picture information to the intelligent driving system on the automobile.
在一些实施方式中,所述无线通讯模块采用V2X的通讯协议(汽车与
其它物体之间的通信协议)进行无线通信。这里的其它物体主要是指路边设备单元,例如安装于道路基础设施上的或者路边建筑物上的存储节点。In some embodiments, the wireless communication module uses a V2X communication protocol (car and
Communication protocol between other objects) performs wireless communication. Other objects herein mainly refer to roadside equipment units, such as storage nodes installed on road infrastructure or on roadside buildings.
在一些实施方式中,所述V2X的通讯协议可以选自DSRC(Dedicated Short Range Communications,专用短程通信技术)、LTE-V(一种4G无线宽带技术)和5G(第5代移动通讯技术)中的至少一种。然而,本领域技术人员应该理解,带宽和延时满足通信要求的所有其他的通讯协议都可以用于本申请中。In some embodiments, the V2X communication protocol may be selected from the group consisting of DSRC (Dedicated Short Range Communications), LTE-V (a 4G wireless broadband technology), and 5G (5th generation mobile communication technology). At least one of them. However, those skilled in the art will appreciate that all other communication protocols that meet the communication requirements for bandwidth and latency can be used in this application.
在一些实施方式中,所述存储节点中存储从本存储节点到最近的应急站点路线的高精度地图子图,所述应急站点存储比存储节点更宽区域范围内的高精度地图子图。所述应急站点可以是存储节点中的一个,所不同的是应急站点的存储能力应该比普通的存储节点大,所述最近的应急站点至少存储当前存储节点的所有直接后续存储节点所存储的高精度地图子图,并且还可以存储当前某行政区域中较宽范围的高精度地图。在智能驾驶汽车运行到当前节点时,发现无法与当前节点进行通信,此时,智能驾驶汽车采用最近下载下来的从本存储节点到最近的应急站点路线的高精度地图子图运行至应急站点,并且在应急站点获取更宽范围内的存储地图,即使在发生较宽范围内的存储节点宕机的情况下,也能够满足当前的驾驶要求。In some embodiments, the storage node stores a high-precision map sub-map from the storage node to the nearest emergency site route, the emergency site storing a high-precision map sub-graph within a wider area than the storage node. The emergency site may be one of the storage nodes, except that the storage capacity of the emergency site should be larger than that of the ordinary storage node, and the latest emergency site stores at least the high storage of all direct subsequent storage nodes of the current storage node. Accurate map subgraphs, and also store a high-resolution map of a wide range of current administrative regions. When the intelligent driving vehicle runs to the current node, it is found that it cannot communicate with the current node. At this time, the intelligent driving vehicle runs to the emergency site using the recently downloaded high-precision map sub-picture from the storage node to the nearest emergency station route. And to obtain a wider range of stored maps at the emergency site, even in the case of a wide range of storage node downtime, the current driving requirements can be met.
在一些实施方式中,所述存储节点还包括CPU、GPS***和内存。存储节点可以包含一台完整的计算机和GPS***,因此可以包含CPU和内存。In some embodiments, the storage node further includes a CPU, a GPS system, and a memory. The storage node can contain a complete computer and GPS system, so it can contain CPU and memory.
本申请提供的高精度地图的分布式存储***包括主节点,其用于存储全局高精度地图;和多个以上所述的存储节点,其中每个存储节点设置于高精度地图的具***置处。主节点存储全局高精度地图,存储节点存储高精度地图子图。全局高精度地图是指整个高精度地图,一般而言,该地图包括的范围包括一个国家比如中国境内的全部地图,也可以是包括某个行政区域比如一个省的全部地图。而高精度地图子图的大小则是根据存储节点的部署情况,由主节点从全局高精度地图中分配。The distributed storage system of the high precision map provided by the present application includes a master node for storing a global high precision map; and a plurality of the above described storage nodes, wherein each storage node is disposed at a specific location of the high precision map. The master node stores a global high-precision map, and the storage node stores a high-resolution map subgraph. The global high-precision map refers to the entire high-precision map. In general, the map includes a map including all maps in a country such as China, or all maps including an administrative region such as a province. The size of the high-resolution map sub-picture is allocated by the master node from the global high-precision map according to the deployment situation of the storage node.
在分布式存储***的一些实施方式中,所述存储节点安装于既有的道路基础设施和路边的建筑物中的至少一种上或者作为新的道路基础设施安装。所述既有的道路基础设施可以选自红绿灯、路灯、违章摄像机、路牌、路边电线杆、和桥梁的一种或多种。In some embodiments of the distributed storage system, the storage node is installed on at least one of an existing road infrastructure and a roadside building or as a new road infrastructure. The existing road infrastructure may be selected from one or more of traffic lights, street lights, illegal cameras, street signs, roadside poles, and bridges.
在分布式存储***的一些实施方式中,所述高精度地图包括:高精度的
地理位置坐标,以及道路形状、车道的数目、各车道的坡度、曲率、航向、和侧倾信息中的一种,多种或者全部。In some implementations of the distributed storage system, the high precision map includes: high precision
Geographical coordinates, and one or more of the shape of the road, the number of lanes, the slope of each lane, the curvature, the heading, and the roll information.
在一些实施方式中,所述的分布式存储***还包括应急站点,其中每个存储节点中存储从当前存储节点到最近的应急站点路线的高精度地图子图,所述最近的应急站点至少存储当前存储节点的所有直接后续存储节点所存储的高精度地图子图。应急站点具有较强的存储能力,可以存储更大范围的高精度地图子图,甚至可以存储一个行政区域比如一个县城或者整个城市的高精度地图子图。In some embodiments, the distributed storage system further includes an emergency site, wherein each storage node stores a high-precision map sub-map from the current storage node to the nearest emergency site route, the latest emergency site storing at least A high-resolution map submap stored by all direct subsequent storage nodes of the current storage node. The emergency site has strong storage capacity, can store a large range of high-precision map sub-pictures, and can even store high-precision map sub-pictures of an administrative area such as a county or the entire city.
在一些实施方式中,所述应急站点具有以网线和/或USB通讯方式访问并下载高精度地图子图的接口。智能驾驶汽车的乘客可以通过这些接口及相应的人机交互界面(人机交互界面可以在智能驾驶汽车上或者在该应急站点上)下载比普通的存储节点更多的地图集,比如在智能驾驶汽车的智能驾驶***的存储空间能够接收的情况下,甚至可以下载到完成当前行驶所需要的所有局部高精度地图。In some embodiments, the emergency site has an interface to access and download a high precision map submap in a network cable and/or USB communication mode. Passengers of intelligent driving vehicles can download more map sets than ordinary storage nodes through these interfaces and corresponding human-computer interaction interfaces (human-computer interaction interfaces can be used on smart driving cars or on the emergency site), such as in smart driving. In the case where the storage space of the car's intelligent driving system can be received, it can even be downloaded to all local high-precision maps required to complete the current driving.
在一些实施方式中,所述多个存储节点在地面的设置稠密程度根据高精度地图的信息存储密度与包括带宽和延时在内的通讯效率设置,使得:每个存储节点的存储容量能够容纳所存储的高精度地图子图集的大小,并且每个存储节点能够满足高精度地图子图传输的带宽和延时需求。比如,在采用4G无线宽带通信协议的情况下,可以在每个十字路口安装存储节点,在没有十字路口的高速路上,可以在高速公路的入口和出口处安装存储节点,目前4G的无线宽带技术能够达到每秒约100兆的下载速度,在高速行驶下速度会有所降低,因此,在这种设计条件下,即使每两个十字路口之间的距离有一英里,高精度地图占用1G字节,也能够在数十秒左右将地图下载完毕,而高速公路的高精度地图信息会占用更小的存储空间,因此,采用这种布局方式,使用目前通用的通信网络即可完成。在采用较低精度的高精度地图的情况下,也可以采用更加稀疏的存储节点布局方式。随着通信***的改进,在采用以后的第5代移动通信网络的情况下,也可能采用更加稀疏的存储节点布局方式。In some embodiments, the density of the plurality of storage nodes on the ground is set according to the information storage density of the high-precision map and the communication efficiency including the bandwidth and the delay, so that the storage capacity of each storage node can be accommodated. The size of the stored high-resolution map sub-atlas, and each storage node can meet the bandwidth and delay requirements of high-precision map sub-picture transmission. For example, in the case of 4G wireless broadband communication protocol, storage nodes can be installed at each intersection. On the highway without intersections, storage nodes can be installed at the entrance and exit of the highway. Currently 4G wireless broadband technology It can achieve a download speed of about 100 megabits per second, and the speed will be reduced at high speeds. Therefore, under this design condition, even if the distance between every two intersections is one mile, the high-precision map occupies 1 Gbyte. It is also possible to download the map in about tens of seconds, and the high-precision map information of the expressway takes up less storage space. Therefore, this layout method can be completed by using the current common communication network. In the case of using high-precision maps of lower precision, a more sparse storage node layout can also be employed. With the improvement of the communication system, in the case of adopting the 5th generation mobile communication network in the future, it is also possible to adopt a more sparse storage node layout manner.
在一些实施方式中,所述应急站点是根据前面所述方式中所述的任一项存储节点,其中所述应急站点还存储其周围的存储节点中所存储的高精度地图的子图集。在本实施方式中,应急站点是一个加强的存储节点。
In some embodiments, the emergency site is any one of the storage nodes described in the manner described above, wherein the emergency site also stores a sub-atlas of high precision maps stored in storage nodes around it. In this embodiment, the emergency site is an enhanced storage node.
在一种特别特殊的实施方式中,每个存储节点都配置为应急站点,也即每个存储节点都存储其周围的存储节点中所存储的高精度地图的子图集。在这种情形下,每个存储节点都不仅作为存储节点,还作为应急站点,从而使得存储节点的网络中如果有一两个存储节点出现问题,并不影响整个分布式存储***的运行,因此使得整个分布式存储***具有较高的稳健性。In a particularly specific embodiment, each storage node is configured as an emergency site, that is, each storage node stores a sub-atlas of high-precision maps stored in storage nodes around it. In this case, each storage node acts not only as a storage node but also as an emergency site, so that if there is a problem with one or two storage nodes in the network of the storage node, it does not affect the operation of the entire distributed storage system, thus The entire distributed storage system has high robustness.
在分布式存储***的一些实施方式中,所述主节点是云端***,其中所述云端***包括云端通讯模块。本申请所述的云端具有本领域技术人员通常理解的含义,其实就是泛指网络。而术语云端***,就是指网络服务器。该云端***采用了云端通讯模块,从而使得存储节点在任何能够连接到网络的地方访问云端***的数据(全局高精度地图)。In some implementations of the distributed storage system, the primary node is a cloud system, and the cloud system includes a cloud communication module. The cloud described in the present application has a meaning that is generally understood by those skilled in the art, and is actually a network. The term cloud system refers to a web server. The cloud system uses a cloud communication module, so that the storage node accesses the cloud system data (global high-precision map) in any place that can connect to the network.
本申请还提供一种将高精度地图部署在以上任一项所述的分布式存储***中的方法,包括如下步骤:The present application also provides a method for deploying a high-precision map in the distributed storage system described in any of the above, comprising the following steps:
在主节点中存储全局高精度地图;Store a global high-precision map in the primary node;
对于每个存储节点,执行如下过程:For each storage node, perform the following process:
搜索出所有直接前序节点和每个直接前序节点所确定的当前存储节点的所有直接后续节点,对于每个直接前序节点到当前存储节点的行驶方向,构造出从该直接前序节点通过当前存储节点至其所有直接后续节点的高精度地图子图,Searching all the direct subsequent nodes of the current storage node determined by all the direct preamble nodes and each direct preamble node, for each direct preamble node to the current storage node's traveling direction, constructing a pass from the direct preamble node a high-resolution map submap of the current storage node to all its immediate subsequent nodes,
将所有构造的高精度地图子图存储于存储节点中,形成所述子图集。All constructed high precision map subgraphs are stored in a storage node to form the sub-atlas.
在本申请中,直接前序节点是指当前存储节点的前序存储节点,并且在该前序存储节点到达当前存储节点的最短路径上不存在其它存储节点。在本申请中,直接后续节点是指当前存储节点的后续存储节点,并且在当前存储节点到该后续存储节点的最短路径上不存在其它存储节点。在本申请中,术语“每个直接前序节点所确定的所有直接后续节点”是指在从直接前序节点到当前节点所确定的行驶方向上所能够达到的所有直接后续节点。一般而言,在本申请中,每个高精度地图子图包括从当前节点的一个直接前序节点到该直接前序节点所确定的所有直接后续节点的高精度地图信息。In the present application, the direct preamble node refers to the predecessor storage node of the current storage node, and there are no other storage nodes on the shortest path of the predecessor storage node to the current storage node. In the present application, a direct subsequent node refers to a subsequent storage node of the current storage node, and there are no other storage nodes on the shortest path from the current storage node to the subsequent storage node. In the present application, the term "all direct subsequent nodes determined by each direct preamble node" refers to all direct subsequent nodes that can be reached in the direction of travel determined from the immediate preamble node to the current node. In general, in the present application, each high precision map submap includes high precision map information from a direct preamble node of the current node to all direct subsequent nodes determined by the direct preamble node.
在所述方法的一些实施方式中,所述方法还包括:形成存储节点的位置拓扑图,其中,“搜索出所有直接前序节点和每个直接前序节点所确定的当前存储节点的所有直接后续节点”的步骤根据存储节点的位置拓扑图进行。
通过形成存储节点的拓扑图能够更加方便地对直接前序节点和直接后续节点进行搜索,计算机领域中具有几乎完全现成的基于图的数据结构算法可以完成该搜索。In some embodiments of the method, the method further comprises: forming a location topology map of the storage node, wherein "searching out all direct direct preamble nodes and all direct current nodes determined by each direct preamble node directly The steps of the subsequent nodes are performed according to the location topology map of the storage node.
The direct preamble node and the direct subsequent node can be searched more conveniently by forming a topology map of the storage node, and the almost complete off-the-shelf graph-based data structure algorithm in the computer field can complete the search.
在所述方法的一些实施方式中,所述分布式存储***还包括应急站点,所述方法还包括:在每个存储节点中存储从当前存储节点到最近的应急站点路线的高精度地图子图,和在所述最近的应急站点中至少存储当前存储节点的所有直接后续存储节点所存储的高精度地图子图。In some embodiments of the method, the distributed storage system further includes an emergency site, the method further comprising: storing, in each storage node, a high-precision map sub-picture from the current storage node to the nearest emergency site route And storing at least the high-precision map sub-picture stored by all direct subsequent storage nodes of the current storage node in the nearest emergency site.
在实际应用中,高精度地图随着测量技术的更新和道路情况的更新等情况会存在随时更新的问题,因此,本发明的方法还包括了地图更新过程。因此,在所述方法的一些实施方式中,所述方法还包括:In practical applications, high-precision maps may be updated at any time as the measurement technology is updated and the road conditions are updated. Therefore, the method of the present invention also includes a map update process. Therefore, in some implementations of the method, the method further includes:
地图更新过程:Map update process:
在主节点中使用更新区域的高精度地图替换该区域中原有的高精度地图;Replace the original high-precision map in the area with the high-precision map of the update area in the master node;
对更新区域中的每个存储节点,执行如下过程:For each storage node in the update area, perform the following process:
搜索出当前存储节点的所有直接前序节点和每个直接前序节点所确定的所有直接后续节点,对于每个直接前序节点到当前存储节点的行驶方向,构造出从当前存储节点的该直接前序节点通过当前存储节点至当前存储节点的所有直接后续节点的高精度地图子图,Searching all direct preamble nodes of the current storage node and all direct subsequent nodes determined by each direct preamble node, constructing the direct from the current storage node for each direct preamble node to the current storage node The high-precision map subgraph of the pre-order node through all current direct nodes of the current storage node to the current storage node,
将所有构造的高精度地图子图存储于存储节点中,形成所述子图集。All constructed high precision map subgraphs are stored in a storage node to form the sub-atlas.
在实际应用中,高精度地图的部署存在着需要根据存储节点的部署的变化而随时更新的问题,因此,本发明的方法还包括了存储节点部署更新过程。因此,在所述方法的一些实施方式中,所述方法还包括:In practical applications, the deployment of high-precision maps has problems that need to be updated at any time according to changes in the deployment of storage nodes. Therefore, the method of the present invention also includes a storage node deployment update process. Therefore, in some implementations of the method, the method further includes:
存储节点部署更新过程:Storage node deployment update process:
对于新的存储节点集合中的每个存储节点,重新搜索出所有直接前序节点和每个直接前序节点所确定的当前存储节点的所有直接后续节点,将重新搜索到的结果与更新前的结果进行对比,For each storage node in the new storage node set, re-search all direct forward nodes and all direct subsequent nodes of the current storage node determined by each direct pre-order node, and re-search the results with the pre-update The results are compared,
对于“所有直接前序节点和每个直接前序节点所确定的所有直接后续节点”有变化的存储节点,执行如下过程:For a storage node that has a change in "all direct preamble nodes and all direct subsequent nodes determined by each direct preamble node", the following process is performed:
对于每个直接前序节点到当前存储节点的行驶方向,构造出从该直接前序节点通过当前存储节点至其所有直接后续节点的高精度地
图子图,For each direct preamble node to the current storage node's direction of travel, construct a high precision from the direct preamble node through the current storage node to all its immediate subsequent nodes
Picture map,
将所有构造的高精度地图子图存储于存储节点中,形成所述子图集。All constructed high precision map subgraphs are stored in a storage node to form the sub-atlas.
本申请还提供一种使用高精度地图的智能驾驶***,包括:智能驾驶信息收发模块;控制设备,其用于控制车辆运动;和智能驾驶存储设备,其用于存储当前高精度地图,所述当前高精度地图包括高精度地图的子图集,和任选的每个高精度地图的子图所对应的使用频次;所述智能驾驶***配置为执行如下步骤:接收步骤:在安装有所述智能驾驶***的车辆从直接前序存储节点驶向当前存储节点的过程中,所述智能驾驶信息收发模块从当前存储节点接收高精度地图的子图,其为从直接前序存储节点驶向当前存储节点的行驶方向的高精度地图的子图;地图更新步骤:将接收到的高精度地图的子图更新到当前高精度地图中;和执行步骤:控制设备根据当前的高精度地图控制车辆进行智能驾驶。在本实施方式中,所述的存储节点可以是本申请所述的高精度地图的分布式存储***中的存储节点。The present application also provides an intelligent driving system using a high-precision map, comprising: an intelligent driving information transceiver module; a control device for controlling vehicle motion; and a smart driving storage device for storing a current high-precision map, The current high-precision map includes a sub-atlas of the high-precision map, and optionally the frequency of use corresponding to the sub-picture of each high-precision map; the intelligent driving system is configured to perform the following steps: receiving step: installing the In the process of driving the vehicle of the intelligent driving system from the direct pre-order storage node to the current storage node, the intelligent driving information transceiver module receives a sub-graph of the high-precision map from the current storage node, which is from the direct pre-order storage node to the current a sub-picture of a high-precision map of the direction of travel of the storage node; a map update step: updating the sub-picture of the received high-precision map to the current high-precision map; and performing steps: controlling the device to control the vehicle according to the current high-precision map Smart driving. In this embodiment, the storage node may be a storage node in a distributed storage system of the high precision map described in the present application.
与该智能驾驶***响应的,本申请还提供一种使用高精度地图的智能驾驶***的智能驾驶方法,所述智能驾驶提醒包括:智能驾驶信息收发模块;控制设备,其用于控制车辆运动;和智能驾驶存储设备,其用于存储当前高精度地图,所述当前高精度地图包括高精度地图的子图集,和任选的每个高精度地图的子图所对应的使用频次;所述方法包括如下步骤:接收步骤:在安装有所述智能驾驶***的车辆从直接前序存储节点驶向当前存储节点的过程中,所述智能驾驶信息收发模块从当前存储节点接收高精度地图的子图,其为从直接前序存储节点驶向当前存储节点的行驶方向的高精度地图的子图;地图更新步骤:将接收到的高精度地图的子图更新到当前高精度地图中;和执行步骤:控制设备根据当前的高精度地图控制车辆进行智能驾驶。In response to the smart driving system, the present application also provides an intelligent driving method of an intelligent driving system using a high-precision map, the smart driving reminder comprising: an intelligent driving information transceiver module; and a control device for controlling vehicle motion; And a smart driving storage device for storing a current high-precision map comprising a sub-atlas of a high-precision map, and optionally a frequency of use corresponding to a sub-picture of each high-precision map; The method includes the following steps: receiving a step of: receiving, in a process of driving a vehicle with the intelligent driving system from a direct pre-order storage node to a current storage node, the intelligent driving information transceiver module receives a high-precision map sub-sector from a current storage node a sub-picture of a high-precision map that travels from a direct pre-order storage node to a current storage node; a map update step: updating a sub-picture of the received high-precision map to a current high-precision map; and executing Step: The control device controls the vehicle for intelligent driving according to the current high-precision map.
在一些实施方式中,在所述接收步骤中,所述智能驾驶信息收发模块首先从当前存储节点接收高精度地图的子图的版本信息,判断“智能驾驶存储设备”中是否存在相同的高精度地图的子图,如果不存在相同的高精度地图的子图,则继续进行高精度地图的子图的接收,如果存在相同的高精度地图的子图,则停止接收高精度地图的子图;更新所述高精度地图的子图的使用频次信息。本步骤鉴于智能驾驶***中的智能驾驶存储设备常常能够存储多个高精度地图子图,而常常使用的地图子图可以保存在智能驾驶存储设备
中,当需要使用时,只需要跟当前存储节点交换一下版本号是不是最新的,如果是最新的,即可不用重复下载高精度地图子图,而直接使用,这样既可以节省带宽,也可以节省能量。当每次使用相同的高精度地图子图时,都将其使用频次信息进行更新,一般而言,如果使用频次信息是使用次数,那么就将使用频次信息加1,表示使用频率提高了一次。In some embodiments, in the receiving step, the smart driving information transceiver module first receives version information of a submap of the high precision map from the current storage node, and determines whether the same high precision exists in the “smart driving storage device”. The sub-picture of the map, if there is no sub-picture of the same high-precision map, the sub-picture of the high-precision map is continued to be received, and if the sub-picture of the same high-precision map exists, the sub-picture of the high-precision map is stopped; The usage frequency information of the subgraph of the high precision map is updated. In this step, the smart driving storage device in the intelligent driving system is often capable of storing a plurality of high-precision map sub-pictures, and the frequently used map sub-pictures can be saved in the smart driving storage device.
In the middle, when you need to use it, you only need to exchange the version number with the current storage node. If it is the latest one, you can download the high-resolution map sub-picture without using it repeatedly, and use it directly, which can save bandwidth. Save energy. When the same high-precision map sub-picture is used each time, it is updated with the frequency information. Generally speaking, if the frequency information is used, the frequency information is incremented by 1, indicating that the frequency of use is increased once.
在一些实施方式中,所述版本信息包括以下的至少一种,多种或者全部:该高精度地图的子图的从直接前序存储节点驶向当前存储节点的行驶方向,更新日期,和更新的版本号。In some embodiments, the version information includes at least one, a plurality or all of: a driving direction of the sub-picture of the high-precision map from a direct pre-order storage node to a current storage node, an update date, and an update Version number.
在一些实施方式中,所述地图更新步骤还包括:判断所述智能驾驶存储设备的存储空间是否足够,如果足够,则继续进行存储,如果不够,则删除一个或多个高精度地图的子图直到存储空间足够为止。In some embodiments, the map updating step further comprises: determining whether the storage space of the smart driving storage device is sufficient, if sufficient, continuing to store, if not, deleting one or more submaps of the high precision map Until the storage space is sufficient.
在一些实施方式中,所述智能驾驶***还配置为能够与周围的智能驾驶汽车分享高精度地图的子图。In some embodiments, the smart driving system is further configured to be able to share a sub-picture of a high precision map with a surrounding smart driving vehicle.
在一些实施方式中,在所述“删除一个或多个高精度地图的子图”的步骤中,根据高精度地图的子图的使用频次信息,优先删除使用频次较低的高精度地图的子图。In some embodiments, in the step of “deleting a sub-picture of one or more high-precision maps”, the sub-pictures of the high-precision map are used to preferentially delete the sub-high-precision maps with lower frequency. Figure.
在一些实施方式中,所述接收步骤还包括:所述智能驾驶信息收发模块从当前存储节点接收当前存储节点驶向最近的应急站点的行驶方向的高精度地图的子图。In some embodiments, the receiving step further comprises: the smart driving information transceiver module receiving, from the current storage node, a sub-graph of the high-precision map of the current storage node heading toward the traveling direction of the nearest emergency station.
在一些实施方式中,所述驾驶***还配置为当所述安装有所述智能驾驶***的车辆接近当前存储节点的位置仍然没有从当前存储节点接收到信息时,控制车辆根据从直接前序存储节点驶向最近的应急站点的行驶方向的高精度地图的子图驶向应急站点。在一些实施方式中,所述智能驾驶方法还包括如下步骤:当所述安装有所述智能驾驶***的车辆接近当前存储节点的位置仍然没有从当前存储节点接收到信息时,控制车辆根据从直接前序存储节点驶向最近的应急站点的行驶方向的高精度地图的子图驶向应急站点。In some embodiments, the driving system is further configured to control the vehicle to be stored according to the direct pre-order when the location where the vehicle with the smart driving system is close to the current storage node still does not receive information from the current storage node. A subgraph of the high-precision map of the node heading for the direction of travel of the nearest emergency site heads for the emergency site. In some embodiments, the smart driving method further includes the step of: controlling the vehicle according to the slave directly when the location of the vehicle in which the smart driving system is installed is close to the current storage node and the information is still not received from the current storage node. The sub-picture of the high-precision map of the pre-order storage node heading for the direction of travel of the nearest emergency station heads to the emergency site.
在一些实施方式中,所述智能驾驶***还配置为执行如下步骤:存储节点更新步骤:在所述车辆驶过当前存储节点后并且驶向直接后续存储节点时,将该当前存储节点更新为直接前序节点,并且将该直接后续存储节点更新为当前结点。在一些实施方式中,所述智能驾驶方法还包括以上所述的存储节点更新步骤。
In some embodiments, the intelligent driving system is further configured to perform the step of: storing a node update step: updating the current storage node to direct after the vehicle drives past the current storage node and heads to a direct subsequent storage node Preorder node and update the immediate subsequent storage node to the current node. In some embodiments, the smart driving method further includes the storage node update step described above.
本申请还提供安装有以上任一项所述的智能驾驶***的车辆。The application also provides a vehicle equipped with the intelligent driving system of any of the above.
实施例Example
下面结合附图对本申请的技术方案做更加具体的解释,应该理解,实施例仅用于说明本申请的技术方案,并不是对本申请技术方案的限制。The technical solutions of the present application are explained in more detail below with reference to the accompanying drawings. It should be understood that the embodiments are only used to illustrate the technical solutions of the present application, and are not intended to limit the technical solutions of the present application.
图1是本申请的高精度地图的分布式存储***的外部示意图。在图1中,存储节点安装于路灯的杆上(图1中的2)。如果路边的基础设施(如红绿灯、违章摄像机、路灯等)上安装有存储节点存储此基础设施附近的高精度地图(其实是全局高精度地图的子图),该存储节点实质上是一个具有存储、接收、发送(一对多)、更新高精度地图子图等功能的小型计算机装置(参见图2)。智能驾驶汽车(图1中的1)在行驶过程中经过相应的基础设施时通过与相应的当前存储节点的通讯可以下载存储的高精地图子图到智能驾驶汽车上(图1中的4)。从某种角度上说,智能驾驶汽车安装了智能驾驶***,也可以“看成”是一个增强版的移动“存储节点”,可以存储、接收、更新和分享多个高精度地图子图。因为基础设施上的存储节点存储的高精度地图是全局高精度地图的局部子图,经过的设计和部署从而使得即使在高速行驶的情况下V2X的通讯协议(如DSRC、LTE-V和5G等)也能满足局部高精度地图传输的带宽和延时需求。这样每辆智能汽车只需要存储一些比较小的局部地图,智能汽车在行驶过程中可以从路边存储有高精地图的基础设施处持续获得当前驾驶所需要的高精度地图(类似于一个局部窗口在全局高精地图频繁地切换)。1 is an external schematic diagram of a distributed storage system of a high precision map of the present application. In Figure 1, the storage node is mounted on a pole of a street light (2 in Figure 1). If a roadside infrastructure (such as traffic lights, illegal cameras, street lights, etc.) is installed with a storage node to store a high-precision map near the infrastructure (actually a sub-graph of a global high-precision map), the storage node is essentially one A small computer device that stores, receives, transmits (one-to-many), and updates functions such as high-precision map sub-pictures (see Figure 2). The intelligent driving car (1 in Figure 1) can download the stored high-precision map sub-picture to the smart driving car through communication with the corresponding current storage node when passing the corresponding infrastructure during driving (4 in Figure 1) . In a certain sense, the smart driving car is equipped with an intelligent driving system, and can also be “watched” as an enhanced version of the mobile “storage node” that can store, receive, update and share multiple high-precision map sub-pictures. Because the high-precision map stored by the storage nodes on the infrastructure is a partial sub-graph of the global high-precision map, it is designed and deployed to make V2X communication protocols (such as DSRC, LTE-V, and 5G, even at high speeds). It can also meet the bandwidth and delay requirements of local high-precision map transmission. In this way, each smart car only needs to store some small local maps. The smart car can continue to obtain the high-precision map needed for the current driving from the roadside storage infrastructure with high-precision map (similar to a partial window). Switch frequently in the global high-precision map).
在本实施例中,路边基础设施上安装的存储有高精度地图的节点其实构成一个网络图。在路边的基础设施上,每个存储节点其实只需要存储行驶过程中的直接前序存储节点(在此前序节点到达当前节点的路上不存在其它存储节点)通过此存储节点到直接后续存储节点(在当前存储节点到后续存储节点的路上不存在其它存储节点)间所有合理路段的高精度地图信息。因为驶向一个存储节点的汽车行驶方向可以有多种,每个存储节点可能存储有多个高精度地图子图。比如说在图3中,A、B、C、D、E、F、G、H、K是路上的存储节点,每条路上画的箭头表示道路上面汽车可以行使的方向。存储节点B按照可能驶过它的3种不同方式(从左到右、从右到左和从上到下)就存储有3个高精度地图子图,每辆智能驾驶汽车在经过B时按照行驶方向
获取相应的高精度地图子图。在各个子图中,其实从某个前序节点到当前节点的路段可以唯一确定一个子图。需要注意的是,图3中的道路行驶方向中有些是单向通行的道路,有的是双向通行的道路,高精度地图子图中会直接忽略不遵守交通规则的行驶路径。在图3中,当车辆从左向右靠近存储节点B时,车辆从存储节点B获取的高精度地图子图应该是以直接前序存储节点A至存储节点B所确定的行驶方向上可能达到的所有直接后续存储节点F、D、E、G和C。对于存储节点B存在的其他的两种行驶方向所对应的高精度地图子图,可以类似地根据图3解释。In this embodiment, the nodes stored on the roadside infrastructure that store high-precision maps actually constitute a network map. On the roadside infrastructure, each storage node only needs to store the direct pre-order storage node during the driving process (there is no other storage node on the way that the pre-order node reaches the current node) through this storage node to the direct subsequent storage node. High-precision map information of all reasonable sections between (there are no other storage nodes on the way from the current storage node to the subsequent storage node). Since there are many different directions for driving to a storage node, each storage node may store multiple high-resolution map subgraphs. For example, in Figure 3, A, B, C, D, E, F, G, H, and K are storage nodes on the road, and the arrows drawn on each road indicate the direction in which the car can be used on the road. Storage Node B stores three high-resolution map sub-pictures in three different ways (from left to right, right to left, and top to bottom) that may pass through it. Each smart driving car follows B when it passes. Direction of travel
Obtain the corresponding high-resolution map subgraph. In each subgraph, a subsection can be uniquely determined from a predecessor node to the current node. It should be noted that some of the road travel directions in Figure 3 are one-way roads, and some are two-way roads. The high-precision map sub-pictures directly ignore the travel paths that do not obey the traffic rules. In FIG. 3, when the vehicle approaches the storage node B from left to right, the high-resolution map sub-picture acquired by the vehicle from the storage node B should be reached in the direction of travel determined by the direct pre-order storage node A to the storage node B. All direct subsequent storage nodes F, D, E, G, and C. A high-precision map sub-picture corresponding to the other two driving directions in which the storage node B exists can be similarly explained according to FIG.
高精度地图的信息存储密度(平均每公里大约占多少字节数)与车辆跟基础设施间的通讯效率(带宽和延时)将影响存储节点的部署稠密程度。一旦存储节点的位置确定,云端***(图1中的5)可以根据全局的高精度地图以及存储节点的位置拓扑计算出每个存储节点所需要存储的1个或多个局部高精度地图子图(具体算法请参见图4),然后相应的高精度地图子图会通过网络部署到对应的存储节点上(图1中的3)。每当存储节点有增减时,云端***会重新执行图3的算法从而算出存储节点增减后每个存储节点需要部署的高精度地图子图,此时云端***只需要对子图有变化的存储节点部署新的高精度地图子图即可。The information storage density of high-precision maps (the average number of bytes per kilometer) and the communication efficiency (bandwidth and latency) between the vehicle and the infrastructure will affect the denseness of the storage node deployment. Once the location of the storage node is determined, the cloud system (5 in FIG. 1) can calculate one or more local high-precision map sub-maps that each storage node needs to store according to the global high-precision map and the location topology of the storage node. (For details, see Figure 4), and then the corresponding high-resolution map submap will be deployed to the corresponding storage node through the network (3 in Figure 1). Whenever the storage node increases or decreases, the cloud system will re-execute the algorithm of Figure 3 to calculate the high-resolution map sub-graph that each storage node needs to deploy after the storage node increases or decreases. At this time, the cloud system only needs to change the sub-picture. The storage node can deploy a new high-resolution map submap.
在实际应用中,高精度地图随着测量技术的更新和道路情况的更新等情况会存在随时更新的问题,因此,本申请的方法还包括了高精度地图的动态更新过程。不管采用何种方法更新全局高精度地图,当全局的高精度地图有更新时,云端***会计算出哪些分布式存储节点中的高精度地图子图需要被更新,并进而对需要更新的存储节点布署新的高精度地图子图(参见图5)。In practical applications, the high-precision map may be updated at any time as the measurement technology is updated and the road conditions are updated. Therefore, the method of the present application also includes a dynamic update process of the high-precision map. Regardless of the method used to update the global high-precision map, when the global high-precision map is updated, the cloud system calculates which high-resolution map sub-graphs in the distributed storage nodes need to be updated, and then the storage nodes that need to be updated A new high-resolution map subgraph (see Figure 5).
有了如上所述的分布式存储***,就可以设计出相应的智能驾驶***。在本实施例中,智能驾驶***包括:智能驾驶信息收发模块;控制设备,其用于控制车辆运动;和智能驾驶存储设备,其用于存储当前高精度地图,所述当前高精度地图包括高精度地图的子图集,和任选的每个高精度地图的子图所对应的使用频次;所述智能驾驶***配置为执行如下步骤:接收步骤:在安装有所述智能驾驶***的车辆从直接前序存储节点驶向当前存储节点的过程中,所述智能驾驶信息收发模块从当前存储节点接收高精度地图的子图,其为从直接前序存储节点驶向当前存储节点的行驶方向的高精度地图的子图;地图更新步骤:将接收到的高精度地图的子图更新到当前高精度地图
中;和执行步骤:控制设备根据当前的高精度地图控制车辆进行智能驾驶。With the distributed storage system described above, the corresponding intelligent driving system can be designed. In this embodiment, the intelligent driving system includes: an intelligent driving information transceiver module; a control device for controlling vehicle motion; and a smart driving storage device for storing a current high-precision map, the current high-precision map including high a sub-atlas of the accuracy map, and optionally a frequency of use corresponding to each of the sub-graphs of the high-precision map; the intelligent driving system is configured to perform the following steps: receiving the step: the vehicle from which the intelligent driving system is installed In the process of driving the direct pre-order storage node to the current storage node, the intelligent driving information transceiver module receives a sub-graph of the high-precision map from the current storage node, which is a driving direction from the direct pre-order storage node to the current storage node. Subgraph of high-precision map; map update step: update the subgraph of the received high-precision map to the current high-precision map
And the execution step: the control device controls the vehicle to perform intelligent driving according to the current high-precision map.
在汽车安装了以上的智能驾驶***之后,就可以使用高精度地图进行智能驾驶了。After the above intelligent driving system is installed in the car, it is possible to use the high-precision map for intelligent driving.
常见智能汽车上的存储空间应该足以存下好些高精度地图子图,但是却往往存不下全局高精度地图。智能汽车上的高精度地图存储空间可以按照使用频度来管理,即在存储空间允许的情况下保留高使用频度的那些高精度地图子图。当智能汽车接收到新的高精度地图子图而车上的存储空间不够时,那么原先缓存的高精度地图子图中使用频率相对低的那些子图会被替换出去。智能汽车上的存储空间越大,它可以缓存的高精度地图子图也可以越多,在频繁行驶的区域内在高精度地图子图没有更新的情况下就可以减少智能汽车重新下载高精度地图子图的概率。有了高精度地图,再加上相应的定位算法,智能驾驶汽车可以获得高精度地图中的丰富信息从而做出更好的规划和控制,让乘客享受良好用户体验的安全出行(参见图6)The storage space on common smart cars should be enough to store some high-precision map sub-pictures, but there is often no global high-precision map. The high-precision map storage space on the smart car can be managed according to the frequency of use, that is, those high-precision map sub-pictures that retain high frequency of use if the storage space allows. When the smart car receives a new high-precision map sub-picture and the storage space on the car is not enough, then those sub-pictures with relatively low frequency used in the previously cached high-precision map sub-pictures will be replaced. The larger the storage space on the smart car, the more high-resolution map sub-pictures it can cache. The high-precision map sub-pictures can be reduced in the frequently-traveled area without the update of the high-precision map. The probability of the graph. With high-precision maps and corresponding positioning algorithms, smart driving cars can get rich information in high-precision maps for better planning and control, allowing passengers to enjoy a safe travel experience with good user experience (see Figure 6).
在实际部署过程中,可以考虑在某些场所(如充电站、停车场、休息服务区等)设置应急站点,以便在智能驾驶汽车跟存储节点出现通讯问题(比如说突然的网络瘫痪)时也可以有机会更新高精度地图。在应急站点中智能驾驶汽车的乘坐人员可以用别的通讯方式(例如网线、USB等)连接智能驾驶汽车和应急站点中的高精地图服务***,然后根据目的地选择子图数据集下载到本车,以便智能驾驶汽车能继续行驶至目的地。也就是说,支持这种应急方案的智能驾驶汽车必须划出一块特定的存储区域存储从某个存储节点行驶至一些附近应急站点的高精度地图子图,以便出现问题时智能驾驶汽车能安全行驶到附近的应急站点。其实在每个存储节点中多存储一个从当前存储节点至最近的应急站点的高精度地图子图就可以满足这一场景需求,此时图4、图5和图6的算法就需要做相应的扩展。In the actual deployment process, you can consider setting up emergency sites in certain places (such as charging stations, parking lots, rest service areas, etc.) so that when there is communication problem between the smart driving car and the storage node (such as sudden network failure) There is an opportunity to update high-resolution maps. In the emergency site, the occupant of the intelligent driving car can connect to the high-precision map service system in the smart driving car and the emergency station by other communication methods (such as network cable, USB, etc.), and then download the data to the present according to the destination selection sub-picture data set. The car so that the smart car can continue to travel to the destination. That is to say, a smart driving vehicle supporting such a contingency plan must draw a specific storage area to store a high-precision map sub-picture from a storage node to some nearby emergency stations, so that the smart driving car can travel safely when a problem occurs. Go to the nearby emergency site. In fact, storing a high-precision map sub-picture from the current storage node to the nearest emergency site in each storage node can meet the needs of this scenario. At this time, the algorithms of Figure 4, Figure 5 and Figure 6 need to be corresponding. Expansion.
下面对图4、图5和图6的算法进行描述。The algorithms of Figures 4, 5 and 6 are described below.
图4是本申请的将高精度地图部署在分布式存储***的存储节点中的算法流程图示例。该算法的过程如下。首先,向主节点中存储全局高精度地图,并且主节点获取存储节点的位置拓扑图。然后对所有的存储节点,进行处理。在对每个存储节点N进行处理的过程中,对该存储节点N的每个行驶方向进行处理:在当前的行使方向下,根据存储节点的位置拓扑图,计算出存储节点N的所有直接前序节点和所有直接后续节点(实际上是每个直
接前序节点所确定的所有直接后续节点),然后根据全局高精度地图构造出当前行驶方向下包含N以及它的所有直接前序节点和所有直接后续节点的高精度地图子图集。4 is an example of an algorithm flow diagram of a high precision map of the present application deployed in a storage node of a distributed storage system. The process of the algorithm is as follows. First, a global high-precision map is stored in the master node, and the master node acquires a location topology map of the storage node. Then all the storage nodes are processed. In the process of processing each storage node N, each driving direction of the storage node N is processed: in the current running direction, all direct fronts of the storage node N are calculated according to the location topology map of the storage node. Sequence node and all direct subsequent nodes (actually each straight
According to the global high-precision map, a high-precision map sub-atlas containing N and all its direct pre-order nodes and all direct subsequent nodes in the current driving direction is constructed according to the global high-precision map.
图5是本申请的高精度地图动态更新的算法流程图示例。该算法的过程如下。首先,根据全局高精度地图的更新区域和所有存储节点的拓扑结构图,找更新区域中包含的存储节点集合S。然后对S中所有的存储节点进行类似于图4中所示的高精度地图部署算法。本算法是地图更新算法的示例。FIG. 5 is an example of an algorithm flow chart of a high-precision map dynamic update of the present application. The process of the algorithm is as follows. First, the storage node set S included in the update area is found according to the update area of the global high-precision map and the topology map of all the storage nodes. A high precision map deployment algorithm similar to that shown in Figure 4 is then performed for all of the storage nodes in S. This algorithm is an example of a map update algorithm.
图6是本申请的智能驾驶***的局部高精度地图的更新和使用流程图示例。该算法的过程如下。在智能驾驶汽车检测到前方存储节点CurNode(即当前存储结点)的存在时,与该当前存储结点CurNode进行通信,把直接前序节点PreNode发送给存储节点CurNode。然后智能驾驶汽车(也即安装于该汽车上的智能驾驶***)接收CurNode发过来的高精度地图子图的版本标识。如果智能驾驶汽车的高精度地图缓存内包含同一版本的高精度地图子图,就无需重新下载,否则重新下载高精度地图子图。在重新下载高精度地图子图的情况下,如果智能驾驶汽车上的高精度地图缓存空间不够,就根据需要接收的高精度地图子图的大小淘汰若干个缓存中使用频率较低的高精度地图子图。然后再接收CurNode发过来的以PreNode至CurNode作为首路段(即行驶方向)的高精度地图子图,并把此高精度地图子图存入高精度地图缓存中。在准备好当前行驶方向上的高精度地图子图之后,智能驾驶车辆(也即该智能驾驶***)根据当前的高精度地图进行智能驾驶。6 is an example of a flow chart for updating and using a local high-precision map of the intelligent driving system of the present application. The process of the algorithm is as follows. When the smart driving vehicle detects the presence of the front storage node CurNode (ie, the current storage node), it communicates with the current storage node CurNode, and sends the direct preamble node PreNode to the storage node CurNode. Then the smart driving car (that is, the intelligent driving system installed on the car) receives the version identifier of the high-resolution map sub-picture sent by the CurNode. If the high-precision map cache of the smart driving car contains the same version of the high-precision map sub-picture, there is no need to re-download, otherwise the high-resolution map sub-picture is re-downloaded. In the case of re-downloading the high-resolution map sub-picture, if the high-precision map buffer space on the smart-driving car is not enough, the high-precision map with a lower frequency of use in the cache is eliminated according to the size of the high-resolution map sub-picture to be received. Subgraph. Then, the high-precision map sub-picture sent by the CurNode as the first road segment (ie, the driving direction) sent by the CurNode is received, and the high-precision map sub-picture is stored in the high-precision map buffer. After the high-precision map sub-picture in the current traveling direction is prepared, the intelligently-driving vehicle (that is, the intelligent driving system) performs intelligent driving based on the current high-precision map.
以上所述仅是本公开的示范性实施方式,而非用于限制本公开的保护范围,本公开的保护范围由所附的权利要求确定。
The above description is only an exemplary embodiment of the present disclosure, and is not intended to limit the scope of the disclosure. The scope of the disclosure is determined by the appended claims.
Claims (30)
- 一种高精度地图的存储节点,其包括:A storage node of high precision map, comprising:信息收发模块,其用于发送和/或接收高精度地图的子图;和An information transceiving module for transmitting and/or receiving subgraphs of high precision maps; and存储设备,其用于存储高精度地图的子图集,其中所述子图集包括与本存储节点直接相关的行驶方向的地图信息,每个子图对应于与本存储节点直接相关的一个行驶方向的地图信息。a storage device for storing a sub-atlas of a high-precision map, wherein the sub-atlas includes map information of a traveling direction directly related to the storage node, and each sub-picture corresponds to a traveling direction directly related to the storage node Map information.
- 根据权利要求1所述的高精度地图的存储节点,其中所述子图集包括当前存储节点的直接前序存储节点(是当前存储节点的前序存储节点,并且在该前序存储节点到达当前存储节点的最短路径上不存在其它存储节点)通过当前存储节点到直接后续存储节点(是当前存储节点的后续存储节点,并且在当前存储节点到该后续存储节点的最短路径上不存在其它存储节点)间的所有行驶方向的高精度地图信息,每个子图对应于每个行驶方向的高精度地图信息。The storage node of the high-precision map according to claim 1, wherein the sub-atlas comprises a direct pre-order storage node of the current storage node (which is a pre-order storage node of the current storage node, and the pre-order storage node arrives at the current There is no other storage node on the shortest path of the storage node) through the current storage node to the direct subsequent storage node (which is the subsequent storage node of the current storage node, and there is no other storage node on the shortest path from the current storage node to the subsequent storage node) High-precision map information of all driving directions between each, and each sub-picture corresponds to high-precision map information of each traveling direction.
- 根据权利要求1所述的存储节点,其中所述信息收发模块包括无线通讯模块和任选的与云端***的通信模块。The storage node of claim 1 wherein said information transceiving module comprises a wireless communication module and optionally a communication module with a cloud system.
- 根据权利要求3所述的存储节点,其中所述无线通讯模块采用V2X的通讯协议(汽车与其它物体之间的通信协议)进行无线通信。The storage node according to claim 3, wherein said wireless communication module performs wireless communication using a V2X communication protocol (a communication protocol between the automobile and other objects).
- 根据权利要求4所述的存储节点,其中所述V2X的通讯协议选自DSRC(Dedicated Short Range Communications,专用短程通信技术)、LTE-V(一种4G无线宽带技术)和5G(第5代移动通讯技术)中的至少一种。The storage node according to claim 4, wherein said V2X communication protocol is selected from the group consisting of DSRC (Dedicated Short Range Communications), LTE-V (a 4G wireless broadband technology), and 5G (5th generation mobile) At least one of communication technologies).
- 根据权利要求1至5中任一项所述的存储节点,其中所述存储节点中存储从本存储节点到最近的应急站点路线的高精度地图子图,所述应急站点存储比存储节点更宽区域范围内的高精度地图子图。The storage node according to any one of claims 1 to 5, wherein the storage node stores a high-precision map sub-picture from the storage node to a nearest emergency site route, the emergency site storage being wider than the storage node High-resolution map subgraphs within the region.
- 根据权利要求1至5中任一项所述的存储节点,其还包括CPU、GPS***和内存。The storage node according to any one of claims 1 to 5, further comprising a CPU, a GPS system, and a memory.
- 高精度地图的分布式存储***,其包括High-resolution map distributed storage system, including主节点,其用于存储全局高精度地图;和a master node for storing global high precision maps; and多个根据权利要求1至7中任一项所述的存储节点,其中每个存储节点设置于高精度地图的具***置处。A plurality of storage nodes according to any one of claims 1 to 7, wherein each storage node is disposed at a specific location of the high precision map.
- 根据权利要求8所述的分布式存储***,其中所述存储节点安装于 既有的道路基础设施和路边的建筑物中的至少一种上或者作为新的道路基础设施安装。The distributed storage system of claim 8 wherein said storage node is mounted to Installed on at least one of the existing road infrastructure and roadside buildings or as a new road infrastructure.
- 根据权利要求9所述的分布式存储***,其中所述既有的道路基础设施选自红绿灯、路灯、违章摄像机、路牌、路边电线杆、和桥梁的一种或多种。The distributed storage system of claim 9 wherein said existing road infrastructure is selected from the group consisting of traffic lights, street lights, illegal cameras, street signs, roadside utility poles, and bridges.
- 根据权利要求8所述的分布式存储***,其中所述高精度地图包括:高精度的地理位置坐标,以及道路形状、车道的数目、各车道的坡度、曲率、航向、和侧倾信息的一种,多种或者全部。The distributed storage system according to claim 8, wherein said high-precision map comprises: high-precision geographic location coordinates, and one of a road shape, a number of lanes, a gradient of each lane, a curvature, a heading, and a roll information. Kind, multiple or all.
- 根据权利要求8所述的分布式存储***,还包括应急站点,其特征在于每个存储节点中存储从当前存储节点到最近的应急站点路线的高精度地图子图,所述最近的应急站点至少存储当前存储节点的所有直接后续存储节点所存储的高精度地图子图。The distributed storage system of claim 8 further comprising an emergency site, wherein each storage node stores a high precision map submap from the current storage node to the nearest emergency site route, said recent emergency site being at least A high-precision map submap stored by all direct subsequent storage nodes of the current storage node.
- 根据权利要求12所述的分布式存储***,其中所述应急站点具有以网线和/或USB通讯方式访问并下载高精度地图子图的接口。The distributed storage system of claim 12 wherein said emergency site has an interface for accessing and downloading high precision map submaps in a network cable and/or USB communication mode.
- 根据权利要求8所述的分布式存储***,其中所述多个存储节点在地面的设置稠密程度根据高精度地图的信息存储密度与包括带宽和延时在内的通讯效率设置,使得:每个存储节点的存储容量能够容纳所存储的高精度地图子图集的大小,并且每个存储节点能够满足高精度地图子图传输的带宽和延时需求。The distributed storage system according to claim 8, wherein the density of the plurality of storage nodes in the ground is set according to the information storage density of the high-precision map and the communication efficiency including the bandwidth and the delay, so that: The storage capacity of the storage node can accommodate the size of the stored high-precision map sub-atlas, and each storage node can meet the bandwidth and delay requirements of high-precision map sub-picture transmission.
- 根据权利要求12或13所述的分布式存储***,其中所述应急站点是根据权利要求1至7中任一项所述的存储节点,其中所述应急站点还存储其周围的存储节点中所存储的高精度地图的子图集。A distributed storage system according to claim 12 or 13, wherein said emergency site is a storage node according to any one of claims 1 to 7, wherein said emergency site further stores a storage node therearound A sub-atlas of stored high-resolution maps.
- 根据权利要求8所述的分布式存储***,其中所述主节点是云端***,其中所述云端***包括云端通讯模块。The distributed storage system of claim 8, wherein the primary node is a cloud system, and wherein the cloud system comprises a cloud communication module.
- 一种将高精度地图部署在权利要求8-16中任一项所述的分布式存储***中的方法,包括如下步骤:A method of deploying a high-precision map in the distributed storage system of any one of claims 8-16, comprising the steps of:在主节点中存储全局高精度地图;Store a global high-precision map in the primary node;对于每个存储节点(称为当前存储节点),执行如下过程:For each storage node (called the current storage node), perform the following process:搜索出所有直接前序节点和每个直接前序节点所确定的当前存储节点的所有直接后续节点,对于每个直接前序节点到当前存储节点的行驶方向,构造出从该直接前序节点通过当前存储节点至其所有直 接后续节点的高精度地图子图,Searching all the direct subsequent nodes of the current storage node determined by all the direct preamble nodes and each direct preamble node, for each direct preamble node to the current storage node's traveling direction, constructing a pass from the direct preamble node Current storage node to all its straight a high-resolution map sub-picture of the subsequent node,将所有构造的高精度地图子图存储于存储节点中,形成所述子图集。All constructed high precision map subgraphs are stored in a storage node to form the sub-atlas.
- 根据权利要求17的方法,还包括:The method of claim 17 further comprising:形成存储节点的位置拓扑图,Forming a location topology map of the storage node,其中,“搜索出所有直接前序节点和每个直接前序节点所确定的的此存储节点的所有直接后续节点”的步骤根据存储节点的位置拓扑图进行。The step of "searching out all direct preamble nodes and all direct subsequent nodes of this storage node determined by each direct preamble node" is performed according to the location topology map of the storage node.
- 根据权利要求17的方法,其中所述分布式存储***还包括应急站点,所述方法还包括:在每个存储节点中存储从当前存储节点到最近的应急站点路线的高精度地图子图,和在所述最近的应急站点中至少存储当前存储节点的所有直接后续存储节点所存储的高精度地图子图。The method of claim 17 wherein said distributed storage system further comprises an emergency site, said method further comprising: storing, in each storage node, a high precision map submap from the current storage node to the nearest emergency site route, and At least the high-precision map sub-picture stored by all direct subsequent storage nodes of the current storage node is stored in the nearest emergency site.
- 根据权利要求17的方法,其中包括:The method of claim 17 comprising:地图更新过程:Map update process:在主节点中使用更新区域的高精度地图替换该区域中原有的高精度地图;Replace the original high-precision map in the area with the high-precision map of the update area in the master node;对更新区域中的每个存储节点,执行如下过程:For each storage node in the update area, perform the following process:搜索出当前存储节点的所有直接前序节点和每个直接前序节点所确定的当前存储节点的所有直接后续节点,对于每个直接前序节点到当前存储节点的行驶方向,构造出从当前存储节点的该直接前序节点通过当前存储节点至当前存储节点的所有直接后续节点的高精度地图子图,Searching all direct immediate nodes of the current storage node and all direct subsequent nodes of the current storage node determined by each direct preamble node, constructing a current storage from each direct preamble node to the current storage node The high-precision map sub-graph of the direct pre-node of the node through the current storage node to all direct subsequent nodes of the current storage node,将所有构造的高精度地图子图存储于存储节点中,形成所述子图集。All constructed high precision map subgraphs are stored in a storage node to form the sub-atlas.
- 根据权利要求17的方法,其中包括:The method of claim 17 comprising:存储节点部署更新过程:Storage node deployment update process:对于新的存储节点集合中的每个存储节点,重新搜索出它的所有直接前序节点和每个直接前序节点所确定的所有直接后续节点,将重新搜索到的结果与更新前的结果进行对比,For each storage node in the new storage node set, re-search all its direct pre-order nodes and all direct subsequent nodes determined by each direct pre-order node, and re-search the results and the pre-update results. Compared,对于“所有直接前序节点和每个直接前序节点所确定的所有直接后续节点”有变化的存储节点,执行如下过程:For a storage node that has a change in "all direct preamble nodes and all direct subsequent nodes determined by each direct preamble node", the following process is performed:对于每个直接前序节点到当前存储节点的行驶方向,构造出从该 直接前序节点通过当前存储节点至其所有直接后续节点的高精度地图子图,For each direct preamble node to the current storage node's direction of travel, construct from The high-precision map subgraph of the direct pre-order node through the current storage node to all its immediate subsequent nodes,将所有构造的高精度地图子图存储于存储节点中,形成所述子图集。All constructed high precision map subgraphs are stored in a storage node to form the sub-atlas.
- 一种使用高精度地图的智能驾驶***,包括:An intelligent driving system that uses high-precision maps, including:智能驾驶信息收发模块;Intelligent driving information transceiver module;控制设备,其用于控制车辆运动;和a control device for controlling vehicle motion; and智能驾驶存储设备,其用于存储当前高精度地图,所述当前高精度地图包括高精度地图的子图集,和任选的每个高精度地图的子图所对应的使用频次;An intelligent driving storage device for storing a current high-precision map, the current high-precision map including a sub-atlas of a high-precision map, and optionally a frequency of use corresponding to each sub-graph of the high-precision map;所述智能驾驶***配置为执行如下步骤:The intelligent driving system is configured to perform the following steps:接收步骤:在安装有所述智能驾驶***的车辆从直接前序存储节点驶向当前存储节点的过程中,所述智能驾驶信息收发模块从当前存储节点接收高精度地图的子图,其为从直接前序存储节点驶向当前存储节点的行驶方向的高精度地图的子图;Receiving step: in the process of driving the vehicle with the intelligent driving system from the direct pre-order storage node to the current storage node, the smart driving information transceiver module receives a sub-graph of the high-precision map from the current storage node, which is a slave a subgraph of a high-precision map of the direct pre-order storage node heading for the direction of travel of the current storage node;地图更新步骤:将接收到的高精度地图的子图更新到当前高精度地图中;和Map update step: update the subgraph of the received high precision map to the current high precision map; and执行步骤:控制设备根据当前的高精度地图控制车辆进行智能驾驶。Execution step: The control device controls the vehicle to perform intelligent driving according to the current high-precision map.
- 根据权利要求22所述的智能驾驶***,其中在所述接收步骤中,所述智能驾驶信息收发模块首先从当前存储节点接收高精度地图的子图的版本信息,判断“智能驾驶存储设备”中是否存在相同的高精度地图的子图,如果不存在相同的高精度地图的子图,则继续进行高精度地图的子图的接收,如果存在相同的高精度地图的子图,则停止接收高精度地图的子图;The intelligent driving system according to claim 22, wherein in said receiving step, said smart driving information transmitting and receiving module first receives version information of a subgraph of a high-precision map from a current storage node, and judges that "smart driving storage device" Whether there is a subgraph of the same high-precision map, if there is no subgraph of the same high-precision map, the subgraph of the high-precision map is continued to be received, and if there is a subgraph of the same high-precision map, the reception is stopped high. Subgraph of the accuracy map;更新所述高精度地图的子图的使用频次信息。The usage frequency information of the subgraph of the high precision map is updated.
- 根据权利要求23所述的智能驾驶***,其中所述版本信息包括以下的至少一种,多种或者全部:该高精度地图的子图的从直接前序存储节点驶向当前存储节点的行驶方向,更新日期,和更新的版本号。The intelligent driving system according to claim 23, wherein said version information comprises at least one, a plurality or all of: a traveling direction of a sub-picture of the high-precision map from a direct pre-order storage node to a current storage node , update date, and updated version number.
- 根据权利要求22所述的智能驾驶***,其中所述地图更新步骤还包括:判断所述智能驾驶存储设备的存储空间是否足够,如果足够,则继续进行存储,如果不够,则删除一个或多个高精度地图的子图直到存储空间足够为止。 The intelligent driving system according to claim 22, wherein said map updating step further comprises: determining whether a storage space of said smart driving storage device is sufficient, if sufficient, continuing to store, if not, deleting one or more Subgraphs of high-precision maps until the storage space is sufficient.
- 根据权利要求25所述的智能驾驶***,其中在所述“删除一个或多个高精度地图的子图”的步骤中,根据高精度地图的子图的使用频次信息,优先删除使用频次较低的高精度地图的子图。The intelligent driving system according to claim 25, wherein in said step of "deleting a sub-picture of one or more high-precision maps", the frequency of priority deletion is lower according to the frequency of use of the sub-picture of the high-precision map Subgraph of a high precision map.
- 根据权利要求22所述的智能驾驶***,其中接收步骤还包括:所述智能驾驶信息收发模块从当前存储节点接收当前存储节点驶向最近的应急站点的行驶方向的高精度地图的子图。The intelligent driving system according to claim 22, wherein the receiving step further comprises: the smart driving information transceiving module receiving, from the current storage node, a sub-picture of the high-precision map of the current storage node traveling to the nearest emergency station.
- 根据权利要求27所述的智能驾驶***,其中所述驾驶***还配置为当所述安装有所述智能驾驶***的车辆接近当前存储节点的位置仍然没有从当前存储节点接收到信息时,控制车辆根据从直接前序存储节点驶向最近的应急站点的行驶方向的高精度地图的子图驶向应急站点。The intelligent driving system according to claim 27, wherein said driving system is further configured to control the vehicle when said vehicle in which said intelligent driving system is installed close to a current storage node has not received information from a current storage node A subgraph of a high-precision map that travels from the immediate pre-order storage node to the direction of travel of the nearest emergency site to the emergency site.
- 根据权利要求22所述的智能驾驶***,其中所述智能驾驶***还配置为执行如下步骤:The intelligent driving system of claim 22, wherein the intelligent driving system is further configured to perform the following steps:存储节点更新步骤:在所述车辆驶过当前存储节点后并且驶向一个直接后续存储节点时,将该当前存储节点更新为直接前序节点,并且将该直接后续存储节点更新为当前结点。The storage node update step: after the vehicle drives past the current storage node and heads to a direct subsequent storage node, updates the current storage node to a direct preamble node, and updates the direct subsequent storage node to the current node.
- 安装有权利要求22至29中任一项所述的智能驾驶***的车辆。 A vehicle equipped with the intelligent driving system according to any one of claims 22 to 29.
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