CN114550480A - Method and system for automatic driving path planning using dedicated lanes - Google Patents
Method and system for automatic driving path planning using dedicated lanes Download PDFInfo
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Abstract
The invention relates to a method and a system for automatically planning a driving path using a dedicated lane. The method comprises the following steps: judging whether the traffic lane is a exclusive lane (S1); identifying traffic sign information on the traffic lane if the traffic lane is a dedicated lane, wherein the traffic sign information includes a traffic restriction time period indicating the dedicated lane (S2); comparing the restricted time period with a current time, thereby determining whether the autonomous vehicle permits use of the exclusive lane (S3); if the autonomous vehicle allows use of the dedicated lane, the dedicated lane is introduced into a driving path plan of the autonomous vehicle (S4). In the embodiment of the invention, the advantages of the road resources of the special lane and the automatic driving technology are fully utilized, and the passing efficiency and the experience of the automatic driving vehicle are improved while the passing rule of the special lane is obeyed.
Description
Technical Field
The present invention relates to the field of automated driving, and more particularly to a method for automatically planning a driving path using a dedicated lane, a system for automatically planning a driving path using a dedicated lane, and a computer program product for performing the method.
Background
With the continuous perfection of modern public transport systems, in order to ensure that public transport vehicles can run smoothly and effectively solve the problem of line congestion of public transport vehicles, special lanes for public transport vehicles, such as special bus lanes, are established. For non-public transport vehicles, the bus-only lane has a traffic-restricted time period, in which the non-public transport vehicles are not allowed to enter the bus-only lane, and in which the non-public transport vehicles are allowed to freely utilize the bus-only lane.
On the other hand, the automatic driving technology has been rapidly developed in recent years, and has a great potential in improving road traffic capacity, reducing energy consumption, and the like, because it can automatically drive a vehicle and accurately detect road conditions. However, based on the current automated driving technology, the bus lane cannot be effectively utilized when the automated driving vehicle plans the driving path, which undoubtedly reduces the traffic efficiency and reduces the experience of automated driving.
Therefore, when planning a driving route by an autonomous vehicle, how to automatically utilize a dedicated lane without violating the traffic rules of the dedicated lane becomes a technical problem that is ubiquitous at present.
Disclosure of Invention
It is an object of the present invention to provide a method for automatically driving path planning using a dedicated lane, a system for automatically driving path planning using a dedicated lane and a computer program product for performing the method, to solve the problems of the prior art. The core concept of the invention is that: and recognizing traffic sign information on a traffic lane through a road surface image recorded by a visual sensor to acquire a traffic restriction time period of the special lane, comparing the traffic restriction time period with the current time, and introducing the special lane into a driving path plan of an automatic driving vehicle if the automatic driving vehicle allows the special lane to be used. The configuration scheme of the invention fully utilizes the road resources of the special lane and the advantages of the automatic driving technology, and improves the passing efficiency and experience of the automatic driving vehicle while observing the passing rule of the special lane.
According to a first aspect of the invention, a method for automatic driving path planning with dedicated lanes is provided. The method comprises the following steps:
step S1: judging whether the traffic lane is a special lane or not;
step S2: identifying traffic sign information on the traffic lane if the traffic lane is a dedicated lane, wherein the traffic sign information includes a traffic restriction time period indicating the dedicated lane;
step S3: comparing the restriction time period to a current time, thereby determining whether the autonomous vehicle is permitted to use the dedicated lane;
step S4: introducing the dedicated lane into a driving path plan of the autonomous vehicle if the autonomous vehicle allows use of the dedicated lane.
Optionally, the method may further comprise the steps of:
step S51: after the special lane is introduced, planning a driving path based on the position information and the high-precision map information of the automatic driving vehicle;
step S52: judging whether the planned driving path contains the special lane or not;
step S53: if the planned driving path includes the dedicated lane, then the autonomous vehicle is steered into the dedicated lane.
Optionally, the method may further comprise the steps of:
step S61: determining whether the autonomous vehicle is crossing the dedicated lane or has driven into the dedicated lane based on a road surface image recorded by a vision sensor if the autonomous vehicle is not allowed to use the dedicated lane;
step S62: steering the autonomous vehicle to move away from the dedicated lane if the autonomous vehicle is crossing the dedicated lane or has moved into the dedicated lane.
Alternatively, in step S1, it is determined whether the traffic lane is a dedicated lane by a road surface image recorded by a vision sensor, wherein the determination is performed based on attribute information of the lane line, the attribute information including color, width, and/or length.
Alternatively, in step S1, it is determined whether the traffic lane is a dedicated lane based on the vehicle position information and the high-precision map information.
Alternatively, in step S2, the traffic sign information on the traffic lane is recognized by the road surface image recorded by the vision sensor by an image processing method.
Optionally, the image processing method is a pre-trained object/pattern classifier and/or a pre-trained convolutional neural network.
Optionally, the private lane is a public transit private lane.
Optionally, the vision sensor is an in-vehicle camera.
According to a third aspect of the invention, a system for automatic driving path planning with dedicated lanes is provided for performing the method according to the invention. The system comprises: a vision sensor for recording road surface images of a roadway; a recognition module for recognizing a lane type, traffic sign information on a lane and/or a driving behavior of an autonomous vehicle based on a road surface image of the lane; a positioning module for obtaining position information of an autonomous vehicle; the map module is used for storing high-precision map information; a path planning module to plan a driving path of an autonomous vehicle; a steering module to steer an autonomous vehicle based on the planned driving path.
According to a third aspect of the invention, there is provided a computer program product, such as a computer-readable program carrier, containing computer program instructions which, when executed by a processor, implement the steps of the above-described method.
Drawings
The principles, features and advantages of the present invention will be better understood by describing the invention in more detail with reference to the accompanying drawings. The figures show:
fig. 1 shows a flow chart of a method for automatic driving path planning with dedicated lanes according to an exemplary embodiment of the present invention;
fig. 2 shows a flow chart of a method for automatic driving path planning with dedicated lanes according to another exemplary embodiment of the present invention;
fig. 3 shows a flow chart of a method for automatic driving path planning with dedicated lanes according to another exemplary embodiment of the present invention;
fig. 4 shows a schematic structural diagram of a system for automatically planning a driving path using a dedicated lane according to an exemplary embodiment of the present invention.
Detailed Description
In order to make the technical problems, technical solutions and advantageous technical effects of the present invention more apparent, the present invention will be further described in detail with reference to the accompanying drawings and exemplary embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and do not limit the scope of the invention.
Fig. 1 shows a flow chart of a method for automatic driving path planning with dedicated lanes according to an exemplary embodiment of the present invention. The following exemplary examples describe the process according to the invention in more detail.
In step S1, it is determined whether or not the traffic lane is an exclusive lane. In the present embodiment of the invention, the exclusive lane is especially a bus exclusive lane. Here, whether or not the traffic lane is an exclusive lane may be determined from a road surface image recorded by the vision sensor 21 (e.g., an on-vehicle camera). Since the attribute information of the special lane line is generally different from the lane line of the general-purpose vehicle, it is possible to accurately identify whether the travel lane is the special lane line based on the attribute information of the lane line. The attribute information of the lane lines may include, but is not limited to, the color, width, and/or length of the lane lines, e.g., bus lane lines are typically yellow dashed lines.
Alternatively, it is also possible to determine whether the traffic lane is a dedicated lane based on the vehicle position information and the high-precision map information. High-precision maps provided by map suppliers nowadays usually contain detailed traffic lane information, in particular information about the type of traffic lane, which can be used to carry out the determination. Since the conventional positioning technology has low accuracy and low accuracy of the position information of the vehicle, there is a possibility that the position information is erroneously determined.
In step S2, if the traffic lane is a dedicated lane, traffic sign information on the traffic lane is identified, wherein the traffic sign information may include a traffic restriction period indicating the dedicated lane. In the present embodiment of the invention, the traffic sign information on the traffic lane is recognized by the road surface image recorded by the vision sensor 21 by an image processing method. The image processing method may be, for example, an object/pattern classifier or a convolutional neural network. Inputting a sufficient number of road surface images into the object/pattern classifier and/or convolutional neural network in advance until it is trained to converge; the road surface image currently recorded by the vision sensor 21 is then input into a pre-trained object/pattern classifier and/or convolutional neural network, whereby traffic sign information on the traffic lane can be output. The traffic sign information may include a restriction time period indicating the exclusive lane, for example, the restriction time of a bus exclusive lane is typically 7 to 10 am and 5 to 8 pm.
In step S3, the travel restriction time period is compared with the current time, thereby determining whether the autonomous vehicle is permitted to use the exclusive lane. If the autonomous vehicle allows the exclusive lane to be used at the current time, the exclusive lane is introduced into the driving path plan of the autonomous vehicle in step S4.
It should be noted that "introduction" can be understood as follows: the special lane is taken into consideration of the driving path planning of the automatic driving vehicle, and the special lane can be used as a part of the planned driving path as required when the driving path planning is carried out subsequently by the automatic driving vehicle. By the configuration scheme, road resources of public transportation can be fully utilized, and therefore traffic efficiency and experience of the automatic driving vehicle are improved.
Fig. 2 shows a flow chart of a method for automatic driving path planning with a dedicated lane according to another exemplary embodiment of the present invention. Only the differences from the embodiment shown in fig. 1 are set forth below, and the description of the same steps is not repeated for the sake of brevity.
The method may further include steps S51, S52, and S53. In step S51, after the exclusive lane is introduced, a driving path planning (which may be, for example, a lane-level path planning) is performed based on the position information of the autonomous vehicle and the high-precision map information. Next, it is determined in step S52 whether the planned driving path includes the exclusive lane. If the planned driving path includes the exclusive lane, the autonomous vehicle is steered into the exclusive lane in step S53.
Fig. 3 shows a flow chart of a method for automatic driving path planning with a dedicated lane according to another exemplary embodiment of the present invention. Only the differences from the embodiment shown in fig. 1 are set forth below, and the description of the same steps is not repeated for the sake of brevity.
The method may further include steps S61 and S62. In step S61, if the autonomous vehicle does not permit the exclusive lane to be used, it is determined whether the autonomous vehicle is crossing the exclusive lane or has driven into the exclusive lane based on the road surface image recorded by the vision sensor 21. If the autonomous vehicle is crossing the dedicated lane or has driven into the dedicated lane, the autonomous vehicle is steered to drive out of the dedicated lane in step S62. In the present embodiment of the invention, in this way, it is possible to effectively reduce the violation of the traffic rule of the exclusive lane.
It should be noted that, since the existing positioning technology has low accuracy, if it is determined whether the autonomous vehicle is crossing the exclusive lane or has entered the exclusive lane based on the vehicle position information and the high-accuracy map information, the possibility of erroneous determination is high. For example, a vehicle is simply traveling on another lane parallel to the exclusive lane and is erroneously determined to be traveling on the exclusive lane, which results in a poor autonomous driving experience, and thus such a determination is not employed.
In addition, it should be noted that the sequence numbers of the steps described herein do not necessarily represent a sequential order, but merely one kind of reference numeral, and the order may be changed according to circumstances as long as the technical object of the present invention can be achieved.
Fig. 4 shows a schematic structural diagram of a system for automatically planning a driving path using a dedicated lane according to an exemplary embodiment of the present invention.
As shown in fig. 4, the system 1 includes: a vision sensor 21 for recording a road surface image of a traffic lane; a recognition module 22 for recognizing a traffic lane type, traffic sign information on the traffic lane and/or a driving behavior of the autonomous vehicle based on a road surface image of the traffic lane; a positioning module 23, the positioning module 23 being configured to obtain position information of an autonomous vehicle; a map module 24, in which high-precision map information is stored in the map module 24; a path planning module 25, the path planning module 25 for planning a driving path of an autonomous vehicle; a steering module 26 for steering the autonomous vehicle based on the planned driving path.
It will be appreciated that an object/pattern classifier and/or a convolutional neural network, for example, is constructed in the recognition module 22.
Although specific embodiments of the invention have been described herein in detail, they have been presented for purposes of illustration only and are not to be construed as limiting the scope of the invention. Various alternatives and modifications can be devised without departing from the spirit and scope of the present invention.
Claims (10)
1. A method for automatic driving path planning with dedicated lanes, wherein the method comprises the steps of:
step S1: judging whether the traffic lane is a special lane or not;
step S2: identifying traffic sign information on the traffic lane if the traffic lane is a dedicated lane, wherein the traffic sign information includes a traffic restriction time period indicating the dedicated lane;
step S3: comparing the restriction time period to a current time, thereby determining whether the autonomous vehicle is permitted to use the dedicated lane;
step S4: introducing the dedicated lane into a driving path plan of the autonomous vehicle if the autonomous vehicle allows use of the dedicated lane.
2. The method of claim 1, wherein the method further comprises the steps of:
step S51: after the special lane is introduced, planning a driving path based on the position information and the high-precision map information of the automatic driving vehicle;
step S52: judging whether the planned driving path contains the special lane or not;
step S53: if the planned driving path includes the dedicated lane, then the autonomous vehicle is steered into the dedicated lane.
3. The method according to any of the preceding claims, wherein the method further comprises the step of:
step S61: if the autonomous vehicle does not allow the exclusive lane to be used, determining whether the autonomous vehicle is crossing the exclusive lane or has driven into the exclusive lane based on a road surface image recorded by a vision sensor (21);
step S62: steering the autonomous vehicle to move away from the dedicated lane if the autonomous vehicle is crossing the dedicated lane or has moved into the dedicated lane.
4. The method according to any one of the preceding claims, wherein in step S1 it is determined whether the traffic lane is a dedicated lane by means of a road surface image recorded by a vision sensor (21), wherein said determination is performed on the basis of attribute information of the lane lines, said attribute information comprising color, width and/or length.
5. The method according to any one of the preceding claims, wherein in step S1, it is determined whether the traffic lane is a dedicated lane based on vehicle position information and high-precision map information.
6. The method according to any one of the preceding claims, wherein in step S2 the traffic sign information on the traffic lane is recognized by an image processing method from road surface images recorded by a vision sensor (21).
7. The method according to any of the preceding claims, wherein the image processing method is a pre-trained object/pattern classifier and/or a pre-trained convolutional neural network.
8. The method according to any of the preceding claims, wherein the private lane is a public transit private lane; and/or
The vision sensor (21) is a vehicle-mounted camera.
9. A system (1) for automatic driving path planning with dedicated lanes, the system (1) being adapted to perform the method according to any one of claims 1 to 8, wherein the system (1) comprises:
a vision sensor (21), the vision sensor (21) being configured to record a road surface image of a traffic lane;
a recognition module (22), the recognition module (22) being configured to recognize a type of traffic lane, traffic sign information on the traffic lane and/or a driving behavior of the autonomous vehicle on the basis of a road surface image of the traffic lane;
a positioning module (23), the positioning module (23) being configured to obtain position information of an autonomous vehicle;
a map module (24) in which high-precision map information is stored in the map module (24);
a path planning module (25), the path planning module (25) for planning a driving path of an autonomous vehicle;
a steering module (26) for steering the autonomous vehicle based on the planned driving path.
10. A computer program product, such as a computer-readable program carrier, containing computer program instructions which, when executed by a processor, implement the steps of the method according to any one of claims 1 to 8.
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CN202210206048.2A CN114550480A (en) | 2022-02-28 | 2022-02-28 | Method and system for automatic driving path planning using dedicated lanes |
DE102023000465.0A DE102023000465A1 (en) | 2022-02-28 | 2023-02-13 | Method and system for the automatic use of dedicated lanes for route planning |
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