CN115107803A - Vehicle control method, device, equipment, vehicle and storage medium - Google Patents
Vehicle control method, device, equipment, vehicle and storage medium Download PDFInfo
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W60/00—Drive control systems specially adapted for autonomous road vehicles
- B60W60/001—Planning or execution of driving tasks
- B60W60/0024—Planning or execution of driving tasks with mediation between passenger and vehicle requirements, e.g. decision between dropping off a passenger or urgent vehicle service
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- B60W60/0025—Planning or execution of driving tasks specially adapted for specific operations
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- B—PERFORMING OPERATIONS; TRANSPORTING
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- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
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Abstract
The present disclosure provides a vehicle control method, apparatus, device and storage medium, which relate to the technical field of artificial intelligence, and in particular to the technical fields of automatic driving, intelligent transportation and the like. The vehicle control method includes: controlling the vehicle to travel to a first location, the first location being a starting location determined by the target passenger; responding to the preset distance from the first position, identifying a target passenger, and determining a second position where the target passenger is located currently; determining a third location for parking based on the second location; controlling the vehicle to park to the third position. The present disclosure can improve the rationality of the boarding position of the target passenger.
Description
Technical Field
The present disclosure relates to the field of artificial intelligence technologies, and in particular, to the field of automated driving, intelligent transportation, and the like, and in particular, to a vehicle control method, apparatus, device, vehicle, and storage medium.
Background
An automatic vehicle (Self-driving automatic vehicle), also called as an unmanned vehicle, a computer-driven vehicle or a wheeled mobile robot, is an intelligent vehicle for realizing unmanned driving through a computing platform.
Depending on the mounted object, the autonomous vehicle can be classified into a manned vehicle and a cargo vehicle. For a passenger carrying vehicle, how to determine the boarding position of a passenger is a problem to be solved.
Disclosure of Invention
The disclosure provides an automatic driving system, a vehicle, a detection method, a detection device, detection equipment and a storage medium.
According to an aspect of the present disclosure, there is provided a vehicle control method including: controlling the vehicle to travel to a first location, the first location being a starting location determined by the target passenger; responding to the preset distance from the first position, identifying a target passenger, and determining a second position where the target passenger is located currently; determining a third, parkable location based on the second location; controlling the vehicle to park to the third position.
According to another aspect of the present disclosure, there is provided a vehicle control apparatus including: a first control module for controlling the vehicle to travel to a first location, the first location being a starting location determined by a target passenger; the first determining module is used for responding to the preset distance from the first position, identifying a target passenger and determining a second position where the target passenger is located currently; a second determination module to determine a third location for parking based on the second location; a second control module to control the vehicle to park to the third position.
According to another aspect of the present disclosure, there is provided an electronic device including: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of the above aspects.
According to another aspect of the present disclosure, there is provided a non-transitory computer readable storage medium having stored thereon computer instructions for causing the computer to perform the method according to any one of the above aspects.
According to another aspect of the present disclosure, there is provided a computer program product comprising a computer program which, when executed by a processor, implements the method according to any one of the above aspects.
According to another aspect of the present disclosure, there is provided an autonomous vehicle including: an electronic device as claimed in any one of the preceding aspects.
According to the technical scheme of the disclosure, the rationality of the boarding position of the target passenger can be improved.
It should be understood that the statements in this section are not intended to identify key or critical features of the embodiments of the present disclosure, nor are they intended to limit the scope of the present disclosure. Other features of the present disclosure will become apparent from the following description.
Drawings
The drawings are included to provide a better understanding of the present solution and are not to be construed as limiting the present disclosure. Wherein:
FIG. 1 is a schematic diagram according to a first embodiment of the present disclosure;
fig. 2 is a schematic diagram of an application scenario corresponding to an embodiment of the present disclosure;
FIG. 3 is a schematic diagram according to a second embodiment of the present disclosure;
FIG. 4 is a schematic diagram according to a third embodiment of the present disclosure;
FIG. 5 is a schematic diagram according to a fourth embodiment of the present disclosure;
fig. 6 is a schematic diagram of an electronic device for implementing the vehicle control method of the embodiment of the present disclosure.
Detailed Description
Exemplary embodiments of the present disclosure are described below with reference to the accompanying drawings, in which various details of the embodiments of the disclosure are included to assist understanding, and which are to be considered as merely exemplary. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the present disclosure. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
In the related art, a manned vehicle can be parked at a predetermined fixed position to wait for passengers to get on the vehicle.
However, this method requires passengers to arrive at a fixed position, and is poor in flexibility, and there may be obstacles such as other vehicles, pedestrians, etc. at the fixed position, so that parking at the fixed position cannot be achieved.
In order to reasonably determine the boarding position of the passenger, the present disclosure provides the following embodiments.
Fig. 1 is a schematic diagram according to a first embodiment of the present disclosure, which provides a vehicle control method. As shown in fig. 1, the vehicle control method provided in the present embodiment includes:
101. and determining a first position based on the riding request information, and controlling the vehicle to go to the first position.
102. In response to a preset distance from the first location, a target passenger is identified and a second location of the target passenger is determined.
103. Based on the second location, a third location that is closest to the second location and that can be parked is determined.
104. Controlling the vehicle to park to the third position.
The method provided by the embodiment can be applied to an automatic driving scene, and accordingly, the vehicle is an automatic driving vehicle. In particular a people carrying vehicle.
The target passenger refers to a passenger to be taken by a bus, namely a passenger delivered by the automatic driving vehicle.
When a target passenger needs to take a car, the passenger can initiate the taking request information through a taking type Application program (APP), and when the target passenger takes the car, the information of the starting point position and the information of the target position can be input into the taking type APP, so that the information of the starting point position can be carried in the taking request information, the automatic driving vehicle can obtain the information of the starting point position from the taking request information, and the starting point position corresponding to the information is used as a first position.
The information of the starting point position input by the target passenger may be input by the target passenger according to the requirement, or may be current position information when the terminal device used by the target passenger is positioned to initiate the taking car request information.
After the autonomous vehicle determines the first location, the autonomous vehicle may plan a path using the first location as a destination and travel to the first location along the planned path.
When the distance from the first location is a preset distance, the autonomous vehicle may identify the target passenger among the plurality of pedestrians using algorithms such as image recognition and/or voice recognition.
The second position is a position where the target passenger is located when the target passenger is identified by the autonomous vehicle.
The autonomous vehicle has an obstacle recognition capability, that is, the autonomous vehicle can recognize information such as a position, a posture, a speed, and the like of an obstacle in the surrounding environment, and since the target passenger belongs to one of the obstacles, the autonomous vehicle can recognize a position where the target passenger is located. For example, a camera on the vehicle is used to collect image data of the target passenger, a lidar is used to collect point cloud data of the target passenger, and based on the image data and/or the point cloud data, a second location of the target passenger may be determined.
Since the starting position input by the target passenger may be a more general position, for example, an east door of a certain building, and the second position is a position where the target passenger identified by the autonomous vehicle is located, and is a more accurate position, for example, latitude and longitude information; alternatively, the target passenger may be walking after initiating the ride request message. These all result in a difference between the first position and the second position.
Therefore, the second position of the target passenger is determined, and the position where the target passenger is actually located can be determined more accurately.
Although the second position is a more accurate position where the target passenger is actually located, it is theoretically possible to stop based on the second position. However, since there may be an obstacle near the second location, for example, the target passenger is in an area where the person is dense; alternatively, the vicinity of the second location may be a defined non-dockable area, for which purpose a third location may be determined based on the second location, the third location being a dockable location.
Wherein the third position can be determined by combining the high-precision map and the identification result of the vehicle for the obstacles of the surrounding environment. The region where the obstacle is located can be determined based on the recognition result of the obstacle, and therefore the position point closest to the second position can be found in the region where the obstacle is not located and can be used as the third position. The third location may be the same or different from the second location.
After the third position is determined, the vehicle can be parked at the third position to wait for the target passenger to get on the vehicle.
In this embodiment, the first position is a starting position determined by the target passenger, and the starting position can be specified by the target passenger, so that flexibility can be improved relative to a fixed position mode; since the position of the target passenger may change during the process of the vehicle heading to the first position, the accuracy of identifying the actual position of the target passenger can be improved by identifying the target passenger and determining the current second position of the target passenger; since there may be an obstacle near the second position or belonging to an unpaintable area, by determining a third position where parking is possible based on the second position, the realizability of the vehicle parking operation can be ensured; therefore, by the means, the parking position of the vehicle, namely the boarding position of the target passenger can be flexibly, accurately and feasibly determined, and the rationality of the boarding position of the target passenger is improved.
For better understanding of the embodiments of the present disclosure, application scenarios of the embodiments of the present disclosure are explained. The present embodiment may be applied to an autonomous driving scenario.
The autopilot function of an autonomous vehicle may be implemented by an autopilot system. The automatic driving level realized by the automatic driving system can be divided into the levels of L0-L5 at present. Wherein, the driving of level L0 represents no automatic driving, namely the traditional driver drives manually; the level-L1 driving is also called auxiliary driving, and includes basic functions such as constant-speed cruising, automatic parking, lane keeping and the like; the L2-level driving is also called semi-automatic driving and comprises functions of automatic auxiliary driving, danger pre-judging braking and the like; level L3 driving, also called conditional automatic driving, can realize fully automatic driving under normal road section compared with level L2, but in some emergency situations, still need manual work to carry out auxiliary braking; the L4 level driving belongs to high automatic driving, the overall braking performance and the reaction capability of the automobile reach a higher level, a driver does not need to operate and control the automobile when sitting in the automobile, and the automobile runs smoothly; the automatic driving of the L5 level can realize unconditional full-automatic driving technology, and under any condition, the full-automatic driving is realized without worrying about road conditions and weather.
As shown in fig. 2, the core modules of the autopilot system 200 include: a High Definition map (HD map)201, a positioning system (localization)202, a Perception system (Perception)203, a Prediction system (Prediction)204, a global navigation system (Routing)205, a Planning module (Planning)206 and a Control module (Control) 207.
The high-precision map 201, also called an autonomous map and a high-resolution map, is a new map data paradigm for an autonomous vehicle. The absolute position accuracy of the high-precision map is close to 1m, and the relative position accuracy is in the centimeter level and can reach 10-20 cm.
The positioning system 202 can provide high-precision (centimeter-level) positioning service based on a positioning device and a high-precision map. The Positioning device includes, for example, one or more of a Global Positioning System (GPS), a Global Navigation Satellite System (GNSS), and an Inertial Navigation System (INS).
And the perception system 203 provides all-around environment perception service for the automatic driving vehicle. The method specifically comprises the following steps: cameras, laser radars, millimeter wave radars, ultrasonic radars, and the like.
The prediction system 204 takes the data of the perception system as input, extracts the historical motion parameters of the vehicle and/or the obstacle, and deduces the motion trail of the vehicle and/or the obstacle at the future moment by combining means such as Kalman filtering, neural network and the like. The predicted motion trajectory may be provided to a planning system.
And the global navigation system 205 is configured to obtain an optimal global navigation path according with the performance evaluation index by using a global path search algorithm according to the initial position and the target position of the vehicle and by combining the road network topology structure.
The planning system 206 mainly provides vehicle obstacle avoidance and lane change decision, path planning and speed planning services.
And the control system 207 is used for performing longitudinal and transverse tracking control according to the driving track provided by the decision planning system.
The control system 207 may specifically control a chassis system of the vehicle to perform operations such as steering, throttle, and braking through a Controller Area Network (CAN) bus.
In combination with the application scenario, the disclosure further provides a vehicle control method.
Fig. 3 is a schematic diagram according to a second embodiment of the present disclosure, which provides a vehicle control method. The method of the present embodiment may be performed by an autonomous vehicle.
The present embodiment takes the parking triggering event as an example of an interception instruction generated by a traffic police.
As shown in fig. 3, the vehicle control method provided by the present embodiment includes:
301. a first location is determined, the first location being a starting location determined by the target passenger.
The target passenger refers to a passenger to be taken by a bus, namely a passenger delivered by the automatic driving vehicle.
When a target passenger needs to take a car, the passenger can initiate the taking request information through a taking type Application program (APP), and when the target passenger takes the car, the information of the starting point position and the information of the target position can be input into the taking type APP, so that the information of the starting point position can be carried in the taking request information, the automatic driving vehicle can obtain the information of the starting point position from the taking request information, and the starting point position corresponding to the information is used as a first position.
The automatic driving vehicle can receive the order dispatching information or the order grabbing information of the cloud platform, the order dispatching information or the order grabbing information can carry the riding request information, and the riding request information can carry the information of the first position, so that the automatic driving vehicle can obtain the information of the first position from the riding request information, and further determine the first position.
After the autonomous vehicle determines the first location, the global navigation system 205 may be employed to plan a global navigation path where the target location is the first location, and to drive to the first location based on the global navigation path.
302. In response to being a preset distance from the first location, identifying a target passenger and determining a second location where the target passenger is currently located.
Where the first position may be represented by P1, the preset distance may be represented by D, and the autonomous vehicle may identify the target passenger in the surrounding environment when the distance P1 is D.
The target passenger may be identified as follows: identifying an obstacle category of obstacles in a surrounding environment; if the obstacle type is a pedestrian, acquiring information of the pedestrian; and if the matching degree of the information of the pedestrian and the preset information meets a preset condition, determining that the pedestrian is the target passenger.
The obstacle detection method can detect obstacles in the surrounding environment of the vehicle in real time by adopting a sensor (a camera, a laser radar and the like) on the vehicle, and identify the type of the obstacles through an image or point cloud identification algorithm.
The categories of obstacles may include: a vehicle, a pedestrian, or a bicycle.
For pedestrians within a certain range (e.g., 10 meters) around the vehicle, information of the corresponding pedestrian can be obtained.
The preset information refers to information of a target passenger. The autonomous vehicle may obtain information of the target passenger from information uploaded in advance by the target passenger. The preset information includes, for example: gender, age, location, clothing, waving, facial features, etc.
In the technical scheme of the disclosure, the collection, storage, use, processing, transmission, provision, disclosure and other processing of the personal information of the related user are all in accordance with the regulations of related laws and regulations and do not violate the good customs of the public order.
The pedestrian information may be obtained using a sensor of the vehicle, for example, using a camera on the vehicle to capture an image of the pedestrian, and/or using a microphone on the vehicle to capture the pedestrian's voice.
Taking an image as an example, an image of a pedestrian may be input into a depth neural network model trained in advance, and pedestrian features are extracted by using the depth neural network model, where the pedestrian features include: gender, age, location, clothing, waving, facial features, etc.
Then, the matching degree between the pedestrian features extracted by the vehicle and the preset information can be calculated, and various related similarity calculation algorithms can be adopted for the matching degree. And sequencing according to the sequence of the matching degrees from high to low, and selecting the pedestrians with the preset number (such as 1-3) in the front sequence as the target passengers.
In this embodiment, the obstacle type is identified, and the pedestrian information is acquired for the pedestrian, so that the pedestrian information can be processed in a targeted manner, instead of processing the obstacles of all types, and the efficiency of identifying the target passenger can be improved.
Further, the information of the pedestrian may be obtained based on the perception data of the vehicle itself, and/or the perception data of the roadside apparatus.
As shown in fig. 2, the automatic driving system includes a perception system 203, and the perception system 203 can obtain perception data of the vehicle itself. The perception data may include: the data of the position, speed, acceleration and the like of the vehicle can also comprise: the data of the type, position, speed, acceleration and the like of the obstacle can further comprise: image of an obstacle, voice, and the like.
Since the pedestrian is one of the obstacles, based on the sensing system 203 of the vehicle, information of the pedestrian, such as obtaining the position of the pedestrian, obtaining data of an image, voice, and the like of the pedestrian, can be obtained.
In dense areas such as intersections, stations, cell gates, park gates, company gates and the like, pedestrian information can be obtained by combining with road side equipment. Roadside devices such as cameras, lidar, voice collectors, etc. mounted on roads.
Perception data collected by the roadside device can be transmitted to an automatic driving Vehicle through a Vehicle to outside interaction (V2X) technology and an On Board Unit (OBU).
In this embodiment, the accuracy of the acquired pedestrian information can be improved by combining the sensing data of the vehicle itself and the sensing data of the roadside device.
After the target passenger is determined, the current position of the target passenger can be used as the second position.
If the target passenger is one, the position of the target passenger may be taken as the second position. If there are a plurality of target passengers, the average position of the positions of the plurality of target passengers may be calculated as the second position.
In addition, after the second position is determined, reminding information can be sent to the target passenger, and the reminding information is used for reminding the arrival of the vehicle.
The reminder information may be one or more of the following: the push information is pushed to the terminal equipment used by the target passenger, the reminding information displayed by the external display screen of the vehicle and the voice information played by the vehicle.
In the embodiment, the reminding information is sent to the target passenger, so that the target passenger can know that the vehicle arrives in time, riding preparation is further made, and user experience is improved.
In addition, various reminding modes are adopted, so that the reminding information can be guaranteed to effectively reach the target passenger.
303. Based on the second position, a third, parkable position is determined.
Wherein the third position may be determined in combination with the high-precision map and the recognition result of the vehicle for the obstacles of the surroundings.
The dockable area and the non-dockable area can be identified in the high-precision map 201, and the sensing system 203 can obtain the area where the obstacle is located, so that the position point closest to the second position can be found as the third position in the dockable area but not in the area where the obstacle is located.
The third position P3 and the second position P2 may be the same or different.
304. Controlling the vehicle to park to the third position.
Where the autonomous vehicle determines the third position, the planning system 206 may plan a parking trajectory from the current position (position D from P1) to P3, and the control system 207 may park to the third position based on the parking trajectory.
The planning system 206 may generate the parking trajectory using Dynamic Planning (DP), Quadratic Planning (QP), or a Hybrid a and RS (streams-Shepp) curve.
In addition, after the vehicle stops at the third position, the push information, the display information of a display screen on the vehicle, the voice playing information of the vehicle and the like can be adopted to send reminding information to the target passenger, the reminding information is used for reminding the arrival of the vehicle, and the target passenger can be reminded to prepare for identity verification.
305. And carrying out identity verification on the target passenger.
The target passenger can be authenticated by adopting modes of face recognition, two-dimensional code scanning, verification code, identification card number and the like.
306. And if the target passenger passes the identity authentication, controlling the vehicle to open the vehicle door.
The automatic driving system may further include an authentication module located on the computing platform, and the control system 207 controls the vehicle to open the vehicle door through the CAN bus after the target passenger passes the authentication result of the authentication module.
In the embodiment, the identity of the target passenger is verified, so that the carried passenger can be ensured to be a real target passenger, and the accuracy and the safety of the riding behavior are improved.
In addition, if the target passenger does not pass the authentication, the vehicle door can be controlled to keep the closed state.
307. And controlling the vehicle to close the door and controlling the vehicle to travel to the target position of the target passenger in response to the confirmation instruction of the target passenger.
After the target passenger gets on the bus, the automatic driving vehicle can further verify the identity, the number of people and the like of the target passenger, and the accuracy of the vehicle taken by the target passenger is reminded through modes of voice, screen interaction and the like.
The target passenger may generate the confirmation instruction by means of voice, screen interaction.
Through multiple interactive mode, can make things convenient for target passenger's operation, target passenger can select suitable interactive mode to interact with the vehicle, promotes user experience.
After the automatic driving vehicle is confirmed by the target passenger, a global navigation system can be adopted to plan a navigation path from the current position (third position) to the target position of the target passenger, and the automatic driving vehicle drives to the target position based on the navigation path to complete the receiving and delivering service.
In this embodiment, the autonomous vehicle determines the second position based on the first position, and may determine a reasonable boarding position of the target passenger based on the third position of the second position; the target passenger can be identified from a plurality of pedestrians based on the pedestrian information and the preset information, and the position of the target passenger can be determined; by sending reminding information to the target passenger, the target passenger can know that the vehicle arrives in time conveniently, and riding is accurate; by carrying out identity verification on the target passenger, the accuracy and the safety of the riding behavior can be ensured.
Fig. 4 is a schematic diagram according to a third embodiment of the present disclosure, which provides a vehicle control apparatus. As shown in fig. 4, the vehicle control device 400 includes: a first control module 401, a first determination module 402, a second determination module 403, and a second control module 404.
The first control module 401 is used for controlling the vehicle to go to a first position, wherein the first position is a starting position determined by a target passenger; the first determining module 402 is configured to identify a target passenger in response to a preset distance from the first position, and determine a second position where the target passenger is currently located; a second determining module 403 is configured to determine a third location capable of parking based on the second location; the second control module 404 is configured to control the vehicle to park to the third position.
In this embodiment, the first position is a starting position determined by the target passenger, and the starting position can be specified by the target passenger, so that flexibility can be improved relative to a fixed position mode; since the position of the target passenger may change in the process that the vehicle moves to the first position, the accuracy of identifying the actual position of the target passenger can be improved by identifying the target passenger and determining the current second position of the target passenger; since there may be an obstacle near the second position or belong to an unparalleled area, the realizability of the vehicle parking operation can be ensured by determining the third position where parking is possible based on the second position; therefore, by the means, the parking position of the vehicle, namely the boarding position of the target passenger can be flexibly, accurately and feasibly determined, and the rationality of the boarding position of the target passenger is improved.
In some embodiments, the first determining module 402 is further configured to: identifying an obstacle category of obstacles in a surrounding environment; if the obstacle type is a pedestrian, acquiring information of the pedestrian; and if the matching degree of the information of the pedestrian and the preset information meets a preset condition, determining that the pedestrian is the target passenger.
In this embodiment, the obstacle type is identified, and the pedestrian information is acquired for the pedestrian, so that the pedestrian information can be processed in a targeted manner, instead of processing the obstacles of all types, and the efficiency of identifying the target passenger can be improved.
In some embodiments, the first determining module 402 is further configured to: and acquiring the information of the pedestrian based on the perception data of the vehicle and/or the perception data of the road side equipment.
In this embodiment, the accuracy of the acquired pedestrian information can be improved by combining the sensing data of the vehicle itself and the sensing data of the roadside device.
In some embodiments, the apparatus 400 further comprises: and the reminding module is used for sending reminding information to the target passenger, and the reminding information is used for reminding the arrival of the vehicle.
In the embodiment, the reminding information is sent to the target passenger, so that the target passenger can know that the vehicle arrives in time, riding preparation is further made, and user experience is improved.
In some embodiments, the apparatus 400 further comprises: the verification module is used for verifying the identity of the target passenger; the third control module is used for controlling the vehicle to open the vehicle door if the target passenger passes the identity authentication; and the fourth control module is used for responding to the confirmation instruction of the target passenger, controlling the vehicle to close the door, and controlling the vehicle to run to the target position of the target passenger.
In the embodiment, the identity of the target passenger is verified, so that the carried passenger can be ensured to be a real target passenger, and the accuracy and the safety of the riding behavior are improved.
It is to be understood that in the disclosed embodiments, the same or similar elements in different embodiments may be referenced.
It is to be understood that "first", "second", and the like in the embodiments of the present disclosure are used for distinction only, and do not indicate the degree of importance, the order of timing, and the like.
In the technical scheme of the disclosure, the collection, storage, use, processing, transmission, provision, disclosure and other processing of the personal information of the related user are all in accordance with the regulations of related laws and regulations and do not violate the good customs of the public order.
The present disclosure also provides an electronic device, a readable storage medium, and a computer program product according to embodiments of the present disclosure.
There is also provided, in accordance with an embodiment of the present disclosure, an autonomous vehicle including an electronic device, as shown in fig. 5, an autonomous vehicle 500 including an electronic device 501. For a description of the electronic device, reference may be made to the following embodiments.
FIG. 6 illustrates a schematic block diagram of an example electronic device 600 that can be used to implement embodiments of the present disclosure. The electronic device 600 is intended to represent various forms of digital computers, such as laptops, desktops, workstations, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital assistants, cellular telephones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be examples only, and are not meant to limit implementations of the disclosure described and/or claimed herein.
As shown in fig. 6, the electronic device 600 includes a computing unit 601, which can perform various appropriate actions and processes according to a computer program stored in a Read Only Memory (ROM)602 or a computer program loaded from a storage unit 608 into a Random Access Memory (RAM) 603. In the RAM 603, various programs and data necessary for the operation of the electronic apparatus 600 can also be stored. The calculation unit 601, the ROM 602, and the RAM 603 are connected to each other via a bus 604. An input/output (I/O) interface 605 is also connected to bus 604.
Various components in the electronic device 600 are connected to the I/O interface 605, including: an input unit 606 such as a keyboard, a mouse, or the like; an output unit 607 such as various types of displays, speakers, and the like; a storage unit 608, such as a magnetic disk, optical disk, or the like; and a communication unit 609 such as a network card, modem, wireless communication transceiver, etc. The communication unit 609 allows the electronic device 600 to exchange information/data with other devices through a computer network such as the internet and/or various telecommunication networks.
The computing unit 601 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of the computing unit 601 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various dedicated Artificial Intelligence (AI) computing chips, various computing units running machine learning model algorithms, a Digital Signal Processor (DSP), and any suitable processor, controller, microcontroller, and so forth. The calculation unit 601 executes the respective methods and processes described above, such as the vehicle control method. For example, in some embodiments, the vehicle control method may be implemented as a computer software program tangibly embodied in a machine-readable medium, such as storage unit 606. In some embodiments, part or all of the computer program may be loaded and/or installed onto the electronic device 600 via the ROM 602 and/or the communication unit 609. When the computer program is loaded into the RAM 603 and executed by the computing unit 601, one or more steps of the vehicle control method described above may be performed. Alternatively, in other embodiments, the computing unit 601 may be configured to perform the vehicle control method in any other suitable manner (e.g., by means of firmware).
Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuitry, Field Programmable Gate Arrays (FPGAs), Application Specific Integrated Circuits (ASICs), Application Specific Standard Products (ASSPs), system on a chip (SOCs), Complex Programmable Logic Devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, receiving data and instructions from, and transmitting data and instructions to, a storage system, at least one input device, and at least one output device.
Program code for implementing the methods of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable map data collection apparatus, such that the program codes, when executed by the processor or controller, cause the functions/operations specified in the flowchart and/or block diagram to be performed. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package partly on the machine and partly on a remote machine or entirely on the remote machine or server.
In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which a user can provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic, speech, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a back-end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), Wide Area Networks (WANs), and the Internet.
The computer system may include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The Server may be a cloud Server, also called a cloud computing Server or a cloud host, and is a host product in a cloud computing service system, so as to solve the defects of high management difficulty and weak service extensibility in a traditional physical host and VPS service ("Virtual Private Server", or "VPS" for short). The server may also be a server of a distributed system, or a server incorporating a blockchain.
It should be understood that various forms of the flows shown above, reordering, adding or deleting steps, may be used. For example, the steps described in the present disclosure may be executed in parallel, sequentially, or in different orders, and are not limited herein as long as the desired results of the technical solutions disclosed in the present disclosure can be achieved.
The above detailed description should not be construed as limiting the scope of the disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may be made, depending on design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present disclosure should be included in the scope of protection of the present disclosure.
Claims (15)
1. A vehicle control method comprising:
controlling the vehicle to travel to a first location, the first location being a starting location determined by the target passenger;
in response to a preset distance from the first position, identifying a target passenger and determining a second position where the target passenger is currently located;
determining a third location for parking based on the second location;
controlling the vehicle to park to the third position.
2. The method of claim 1, wherein the identifying a target passenger comprises:
identifying an obstacle category of obstacles in a surrounding environment;
if the obstacle type is a pedestrian, acquiring information of the pedestrian;
and if the matching degree of the information of the pedestrian and the preset information meets a preset condition, determining that the pedestrian is the target passenger.
3. The method of claim 2, wherein the obtaining information of the pedestrian comprises:
and acquiring the information of the pedestrian based on the perception data of the vehicle and/or the perception data of the road side equipment.
4. The method of claim 1, after determining the second location, the method further comprising:
and sending reminding information to the target passenger, wherein the reminding information is used for reminding the arrival of the vehicle.
5. The method of claim 4, wherein the reminder information comprises at least one of:
voice information played by the vehicle;
textual information displayed by the vehicle;
and pushing the push information to the user terminal used by the target passenger.
6. The method of any of claims 1-5, further comprising, after the vehicle is parked to the third location:
performing identity verification on the target passenger;
if the target passenger passes the identity authentication, controlling the vehicle to open a vehicle door;
and controlling the vehicle to close the door and controlling the vehicle to travel to the target position of the target passenger in response to the confirmation instruction of the target passenger.
7. A vehicle control apparatus comprising:
a first control module for controlling the vehicle to travel to a first location, the first location being a starting location determined by a target passenger;
the first determining module is used for responding to the preset distance from the first position, identifying a target passenger and determining a second position where the target passenger is located currently;
a second determination module to determine a third location for parking based on the second location;
a second control module to control the vehicle to park to the third position.
8. The apparatus of claim 7, wherein the first determining means is further configured to:
identifying an obstacle category of obstacles in a surrounding environment;
if the obstacle type is a pedestrian, acquiring information of the pedestrian;
and if the matching degree of the information of the pedestrian and the preset information meets a preset condition, determining that the pedestrian is the target passenger.
9. The apparatus of claim 8, wherein the first determining means is further for:
and acquiring the information of the pedestrian based on the perception data of the vehicle and/or the perception data of the road side equipment.
10. The apparatus of claim 7, further comprising:
and the reminding module is used for sending reminding information to the target passenger, and the reminding information is used for reminding the arrival of the vehicle.
11. The apparatus of any of claims 7-10, further comprising:
the verification module is used for verifying the identity of the target passenger;
the third control module is used for controlling the vehicle to open a vehicle door if the target passenger passes the identity verification;
and the fourth control module is used for responding to the confirmation instruction of the target passenger, controlling the vehicle to close the door, and controlling the vehicle to run to the target position of the target passenger.
12. An electronic device, comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-6.
13. A non-transitory computer readable storage medium having stored thereon computer instructions for causing the computer to perform the method of any one of claims 1-6.
14. A computer program product comprising a computer program which, when executed by a processor, implements the method according to any one of claims 1-6.
15. An autonomous vehicle comprising: the electronic device of claim 12.
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