CN111457931B - Method, device, system and storage medium for controlling local path re-planning of autonomous vehicle - Google Patents
Method, device, system and storage medium for controlling local path re-planning of autonomous vehicle Download PDFInfo
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- CN111457931B CN111457931B CN201910051715.2A CN201910051715A CN111457931B CN 111457931 B CN111457931 B CN 111457931B CN 201910051715 A CN201910051715 A CN 201910051715A CN 111457931 B CN111457931 B CN 111457931B
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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
- G01C21/3407—Route searching; Route guidance specially adapted for specific applications
- G01C21/3415—Dynamic re-routing, e.g. recalculating the route when the user deviates from calculated route or after detecting real-time traffic data or accidents
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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
- G01C21/3446—Details of route searching algorithms, e.g. Dijkstra, A*, arc-flags, using precalculated routes
Abstract
The invention discloses a local path re-planning control method, a device, a system and a storage medium of an automatic driving vehicle, wherein the method comprises the following steps: acquiring current running state information of a vehicle and traffic state information of the vehicle on a planned local path at the last moment; judging whether at least one preset local path re-planning condition is met or not according to the traffic state information and the running state information; when the local path replanning condition is judged to be met, replanning the local path of the vehicle, and controlling the vehicle to run according to the replanned local path; and when judging that any one of the local path re-planning conditions is not met, controlling the vehicle to run according to the planned local path. The invention can effectively reduce the times of re-planning the local path of the vehicle, thereby reducing the difficulty of controlling the automatic driving motion.
Description
Technical Field
The invention relates to the technical field of automatic driving, in particular to a method, a device and a system for controlling local path re-planning of an automatic driving vehicle and a storage medium.
Background
During the driving process of an automobile with an automatic driving function (called an automatic driving automobile for short), the external environment of the automobile changes all the time, and a decision planning system of the automatic driving automobile correspondingly finds out an optimal passable local path starting from the current position of the automobile at each time according to the external environment at the current time.
The current mainstream local path planning method of the automatic driving automobile is based on periodic driving, namely, a decision planning system of the automatic driving automobile plans an optimal local path which can be passed from a sitting automobile in real time according to the perception of the vehicle to the surrounding environment (aiming at judging whether the vehicle can normally pass in the current driving direction) and the driving state of the vehicle (comprising the position of the vehicle, the heading of the vehicle, the speed of the vehicle, the acceleration of the vehicle and the like). Because the vehicle is adjacent to two moments and has unavoidable errors in sensing of the external environment and detection and calculation of the vehicle running state, the vehicle almost always needs to plan a local path at every moment, and the optimal local paths given at the two adjacent moments have certain deviation in the transverse direction and the longitudinal direction, so that the vehicle is always in a changing state along with the target path, and thus when the vehicle motion control does not stably follow the path planned at the previous moment, the target path at the next moment is changed, and the difficulty of automatic driving motion control can be increased.
Disclosure of Invention
The embodiment of the invention provides a method, a device and a system for controlling re-planning of a local path of an automatic driving vehicle and a storage medium, which can effectively reduce the re-planning times of the local path of the vehicle, thereby reducing the difficulty of controlling the automatic driving motion.
An embodiment of the present invention provides a local path re-planning control method for an autonomous vehicle, including:
acquiring current running state information of a vehicle and traffic state information on a planned local path at the last moment;
judging whether at least one preset local path re-planning condition is met or not according to the traffic state information and the running state information; wherein the local path re-planning condition comprises: the traffic state information comprises a traffic state information and a traffic state information, wherein the traffic state information comprises traffic state information and traffic state information;
when the local path replanning condition is judged to be met, replanning the local path of the vehicle, and controlling the vehicle to run according to the replanned local path;
and when judging that any one of the local path re-planning conditions is not met, controlling the vehicle to run according to the planned local path.
As a refinement of the above, the driving state information includes at least one of: the method comprises the following steps of positioning accuracy of a vehicle, positioning accuracy change rate of the vehicle, planned local path on the vehicle at a moment, lane driving state of the vehicle on a global path, transverse distance between the vehicle and the nearest point of the planned local path, longitudinal distance between the vehicle and the nearest point of the planned local path, and included angle between the vehicle and the nearest point direction of the planned local path.
As an improvement of the above, when the running state information includes the positioning accuracy of the vehicle, then the abnormal running state condition includes: and the numerical value of the positioning precision is greater than a preset positioning precision threshold value.
As an improvement of the above, when the running state information includes a rate of change in the positioning accuracy of the vehicle, then the abnormal running state condition includes: and the numerical value of the positioning precision change rate is greater than a preset positioning precision change rate threshold value.
As an improvement of the above solution, when the driving state information includes a planned local path at a time on the vehicle, then the abnormal driving state condition includes: the planned local path is not yet planned or is an invalid path.
As an improvement of the above, when the running state information includes a lane running state of the vehicle on a global path, then the abnormal running state condition includes: the lane driving state of the vehicle on the global path is changed;
wherein the lane driving state includes: normally driving along the original lane, starting to change to the left lane, driving along the left lane, changing the left lane to the original lane, starting to change to the right lane, driving along the right lane, and changing the right lane to the original lane.
As an improvement of the above, when the driving state information includes a lateral distance between the vehicle and a closest point of the planned local path, then the abnormal driving state condition includes: the lateral distance between the vehicle and the closest point of the planned local path is larger than a preset lateral distance threshold value.
As an improvement of the above, when the driving state information includes a longitudinal distance between the vehicle and a closest point of the planned local path, then the abnormal driving state condition includes: the longitudinal distance between the vehicle and the closest point of the planned local path is greater than a preset longitudinal distance threshold value.
As an improvement of the above solution, when the driving state information includes an angle between the vehicle and a direction of a closest point of the planned local path, the abnormal driving state condition includes: and the included angle between the vehicle and the direction of the closest point of the planned local path is greater than a preset included angle threshold value.
As an improvement of the above solution, the traffic status information includes: obstacle information on the planned local path and vehicle following state information of the vehicle;
when the passing state information is acquired, the condition of not passing comprises: an obstacle exists on the planned local path, and the vehicle is currently in a non-following state.
As an improvement of the above solution, before controlling the vehicle to travel along the planned local path when it is determined that any one of the local path re-planning conditions is not satisfied, the method further includes:
obtaining a remaining distance parameter of a planned local path of the vehicle at the previous moment;
and if it is determined that any one of the local path re-planning conditions is not satisfied, controlling the vehicle to travel according to the planned local path, specifically:
when judging that any one of the local path re-planning conditions is not met, judging whether the residual distance parameter is smaller than a preset residual distance threshold value; wherein the magnitude of the remaining distance threshold is proportional to the magnitude of the current vehicle speed of the vehicle;
if so, extending the planned local path, and controlling the vehicle to run according to the extended local path;
and if not, controlling the vehicle to run according to the planned local path.
Another embodiment of the present invention correspondingly provides a partial path re-planning control apparatus for an autonomous vehicle, including:
the information acquisition module is used for acquiring the current running state information of the vehicle and the traffic state information on the planned local path at the last moment;
the judging module is used for judging whether at least one preset local path re-planning condition is met or not according to the traffic state information and the running state information; wherein the local path re-planning condition comprises: the traffic state information comprises a traffic state information and a traffic state information, wherein the traffic state information comprises traffic state information and traffic state information;
the first driving control module is used for replanning the local path of the vehicle and controlling the vehicle to drive according to the replanned local path when judging that at least one local path replanning condition is met;
and the second running control module is used for controlling the vehicle to run according to the planned local path when judging that any one of the local path re-planning conditions is not met.
Another embodiment of the present invention provides a control system of an autonomous vehicle, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor implements the local re-routing control method of the autonomous vehicle according to the above embodiment of the present invention when executing the computer program.
Another embodiment of the present invention provides a storage medium, where the computer-readable storage medium includes a stored computer program, where when the computer program runs, a device on which the computer-readable storage medium is located is controlled to execute the method for controlling re-planning of a local path of an autonomous vehicle according to the embodiment of the present invention.
Compared with the prior art, in the embodiment of the invention, whether at least one preset local path re-planning condition is met is judged according to the current passing state information and the current running state information of the vehicle; if the situation that any local path re-planning condition is not met is judged, the local path is not re-planned, or the vehicle is controlled to continue to run according to the planned local path; and replanning the local path of the vehicle only when judging that at least one local path replanning condition is met, thus avoiding replanning the local path at every moment according to the traffic state information and the running state information of the vehicle, effectively reducing the replanning times of the local path of the vehicle and further reducing the difficulty of automatic driving motion control. In addition, the times of re-planning the local path of the vehicle are effectively reduced, so that the vehicle does not need to change the local path frequently and does not turn frequently, the problem that the vehicle continuously swings due to frequent turning of the vehicle is avoided, and the driving comfort and safety of the vehicle can be improved.
Drawings
FIG. 1 is a schematic flow chart diagram illustrating a method for controlling a partial re-routing of a path of an autonomous vehicle according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a detailed control process of a partial path re-planning control method for an autonomous vehicle according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a partial re-routing control apparatus for an autonomous vehicle according to an embodiment of the present invention;
fig. 4 is a schematic structural diagram of a control system of an autonomous vehicle according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The first embodiment is as follows:
fig. 1 is a schematic flow chart of a method for controlling a local path re-planning of an autonomous vehicle according to an embodiment of the present invention.
The partial path re-planning control method of the autonomous vehicle provided by the embodiment may be executed by an autonomous driving control terminal. In this embodiment, the automatic driving control terminal is preferably a control system of an automatic driving vehicle (even a cloud server, etc.), the control system may be implemented in a software and/or hardware manner, and the control system may be formed by two or more physical entities or may be formed by one physical entity.
Further, the control system is connected to various sensing systems of the autonomous vehicle (e.g., a detection radar, a proximity sensor, an image capturing device, etc.), various driving state information generating devices of the vehicle (e.g., a GPS positioning device, an inertial measurement unit IMU, an acceleration sensor, a steering wheel angle sensor, etc., which are generally connected to the control system through a CAN bus), a wireless communication module, a display system of the vehicle, a driving system of the vehicle, etc. The control system acquires traffic state information such as lane lines, traffic signs, traffic lights, dynamic obstacles (such as pedestrians, animals and the like) and positions thereof, static obstacles (such as roadblocks, large stones, pits and the like) and positions thereof, speeds, positions and headings of traffic participants (such as automobiles) and the like when the vehicle runs currently through the sensing system. The control system acquires the vehicle running state information such as speed, acceleration, steering wheel angle, vehicle positioning information, vehicle course, vehicle positioning precision change rate, vehicle lane running state and the like sent by each running state information generating device of the vehicle through the CAN bus. The control system is connected with the cloud server or is in communication connection with the communication base station through the wireless communication module. The control system controls the display operation of the display system and controls the driving operation of the vehicle by controlling the driving system. In addition, the various information may be directly transmitted to the control system, or may be transmitted to another information processing apparatus, and after corresponding information processing, the information processing apparatus transmits the processed information to the control system.
Specifically, referring to fig. 1, the partial path re-planning control method of the autonomous vehicle includes steps S10 to S13:
s10, acquiring the current running state information of the vehicle and the current passing state information on the planned local path at the previous moment;
specifically, the control system of the autonomous vehicle continuously acquires the current driving state information and the current traffic state information of the vehicle at a predetermined sampling frequency. The control system judges the current passing condition of the vehicle on the running path by analyzing the acquired passing state information, and judges whether the current running state of the vehicle is normal or not by analyzing the acquired running state information.
S11, judging whether at least one preset local path re-planning condition is met according to the traffic state information and the driving state information;
wherein the local path re-planning condition comprises: and the non-passable condition corresponding to the passing state information and the abnormal running state condition corresponding to the running state information. In this embodiment, after acquiring the traffic state information, the control system may determine whether the impassable condition is satisfied according to the traffic state information; similarly, after the control system acquires the driving state information, whether the abnormal driving state condition is met or not is judged according to the driving state information. Wherein, the abnormal driving state can be represented as: the running state of the vehicle is unreasonable, or abnormal change or even sudden change occurs, so that if the vehicle continues to run on the current running path, the problems of running comfort, running control difficulty and even running safety can be caused.
S12, when judging that at least one local path replanning condition is satisfied, replanning the local path of the vehicle, and controlling the vehicle to run according to the replanned local path;
when the control system judges that at least one local path replanning condition is met, the control system indicates that a local path planned at the last moment of the vehicle is no longer suitable for the vehicle to continue running, namely: if the local route planned at the previous time is continued to run, the running safety of the vehicle, even the running comfort and the like are threatened. For example, the partial path planned at the last moment is judged to be not passable according to the passing state information, and/or the current running state of the vehicle is judged to be abnormal according to the running state information. At this time, a suitable local path needs to be re-planned, and then the vehicle is controlled to run according to the re-planned local path, so that the running control difficulty of the vehicle is reduced, the running safety of the vehicle is ensured, and even the running comfort of the vehicle is improved.
In this embodiment, the local route is preferably re-planned according to external perception information (such as obstacle information and lane information) currently acquired by the vehicle and vehicle driving state information (such as the vehicle's own position, the vehicle heading, the vehicle speed, and the vehicle acceleration). Specifically, the re-planning mode may be a bezier curve path planning mode, a Dubins path planning mode, or other existing local path planning modes, and the like, which is not limited herein.
And S13, when judging that any one of the local path replanning conditions is not met, controlling the vehicle to run according to the planned local path.
When the control system judges that any one of the local path re-planning conditions is not met, the control system indicates that the vehicle can continue to normally run on the local path planned at the previous moment, so that continuous re-planning is not needed according to external perception information and vehicle state information currently acquired by the vehicle.
In summary, in the embodiment of the present invention, whether at least one preset local route re-planning condition is satisfied is determined according to the current traffic status information and the current driving status information of the vehicle; if the situation that any local path re-planning condition is not met is judged, the local path is not re-planned, or the vehicle is controlled to continue to run according to the planned local path; and replanning the local path of the vehicle only when judging that at least one local path replanning condition is met, thus avoiding replanning the local path at every moment according to the traffic state information and the running state information of the vehicle, effectively reducing the replanning times of the local path of the vehicle and further reducing the difficulty of automatic driving motion control. In addition, the times of re-planning the local path of the vehicle are effectively reduced, so that the vehicle does not need to change the local path frequently and does not turn frequently, the problem that the vehicle continuously swings due to frequent turning of the vehicle is avoided, and the driving comfort and safety of the vehicle can be improved.
In this embodiment, preferably, the running state information includes at least one of the following seven types: the method comprises the following steps of positioning accuracy of a vehicle, positioning accuracy change rate of the vehicle, planned local path on the vehicle at a moment, lane driving state of the vehicle on a global path, transverse distance between the vehicle and the nearest point of the planned local path, longitudinal distance between the vehicle and the nearest point of the planned local path, and included angle between the vehicle and the nearest point direction of the planned local path. That is, if the driving state information is not reasonable or abnormally changed, a driving comfort problem, a driving control difficulty problem, or a driving safety problem may occur when the vehicle continues to travel on the planned travel route. Of course, the driving state information may be of other types, and is not specifically limited and listed herein as long as it affects the driving comfort and safety of the vehicle.
For example, referring to fig. 2, when the driving state information is the positioning accuracy of the vehicle, the abnormal driving state condition corresponds to: and the numerical value of the positioning precision is greater than a preset positioning precision threshold value. Wherein, the positioning precision is preferably: obtained by the control system from positioning information sent by the GPS positioning device of the vehicle or sent by the inertial measurement unit IMU. More specifically, the abnormal driving state condition may be expressed by the following equation: ACCURAY > ACCURAY. Wherein, ACCURAY represents the positioning accuracy, and ACCURAY represents the preset positioning accuracy threshold.
For example, referring to fig. 2, when the driving state information is a change rate of the positioning accuracy of the vehicle, the abnormal driving state condition corresponds to: and the numerical value of the positioning precision change rate is greater than a preset positioning precision change rate threshold value. Wherein, the change rate of the positioning precision is preferably as follows: the control system is obtained by calculation according to positioning information sent by the GPS positioning device of the vehicle at two adjacent moments or is sent by the inertial measurement unit IMU. More specifically, the abnormal driving state condition may be expressed by the following equation: DELTA _ ACCURAY > DELTA _ ACCURAY. Wherein, DELTA _ ACCURAY represents the positioning precision change rate, and DELTA _ ACCURAY represents the preset positioning precision change rate threshold.
In this embodiment, when the positioning accuracy or the variation rate of the positioning accuracy is obtained and it is determined that the corresponding abnormal driving state condition is satisfied, it indicates that the current positioning accuracy of the vehicle is low or the positioning accuracy is always in an unstable state, and the position of the vehicle on the global path obtained by the GPS positioning device is always in a variation state, so that the vehicle driving position coordinate of the planned local path at the previous time has lost the reference meaning to the next time, and at this time, the local path needs to be re-planned to ensure driving safety. Such unstable positioning scenes often occur in tunnel scenes or scenes of standing high-rise buildings and the like.
For example, referring to fig. 2, when the driving state information is a planned local path at a time on the vehicle, the abnormal driving state condition corresponds to: the planned local path is not yet planned or is an invalid path. The planned local path at a moment on the vehicle is cached in a processor of the control system or stored in a memory of the control system after being planned by the control system.
For example, referring to fig. 2, when the driving state information is a lane driving state of the vehicle on a global path, the abnormal driving state condition corresponds to: the lane driving state of the vehicle on the global path is changed. Wherein the lane driving state includes: normally driving along the original lane, starting to change to the left lane, driving along the left lane, changing the left lane to the original lane, starting to change to the right lane, driving along the right lane, and changing the right lane to the original lane. The lane driving state is preferably: the pose information is analyzed by the control system according to the pose information detected by the relative pose detection system (such as a steering wheel angle sensor) of the vehicle. More specifically, the abnormal driving state condition may be expressed by the following equation: his _ chg _ state! Not equal cur _ chg _ state. Here, his _ chg _ state indicates a lane driving state at the previous time, and cur _ chg _ state indicates a lane driving state at the current time.
In this embodiment, when it is determined that the lane driving state of the vehicle on the global path changes (usually, the driver manually operates the vehicle to perform lane change), it indicates that the vehicle is deviating from the local path planned at the previous time, and at this time, the local path of the vehicle needs to be re-planned, so that the vehicle can respond to the updated vehicle driving state in time, and driving safety is ensured.
For example, referring to fig. 2, when the driving state information is a lateral distance between the vehicle and a closest point of the planned local path, the abnormal driving state condition corresponds to: the lateral distance between the vehicle and the closest point of the planned local path is larger than a preset lateral distance threshold value. Wherein the lateral distance of the vehicle from the closest point of the planned local path is preferably: and the control system calculates the vehicle according to the current position of the vehicle and the planned path. More specifically, the abnormal driving state condition may be expressed by the following equation: path _ LAT _ DIS < LAT _ DIS. Wherein, path _ LAT _ DIS represents the lateral distance between the vehicle and the nearest point of the planned local path, and LAT _ DIS represents a preset lateral distance threshold value.
In this embodiment, due to vehicle control and execution of the vehicle itself, or when the vehicle is driven manually, there may be a case where the planned path cannot be completely followed, for example, the current actual position of the vehicle may be shifted from the closest point of the local path planned at the previous time. When the transverse distance between the vehicle and the closest point of the planned local path at the previous moment is judged to be larger than the preset transverse distance threshold, the transverse distance between the current position of the vehicle and the closest point of the planned local path at the previous moment is over-large, so that the vehicle cannot completely follow the planned local path at the previous moment, or if the vehicle continues to follow the planned local path at the previous moment, the phenomena of violent swing, even rollover and the like of the vehicle due to over-violent and over-large steering can occur. Therefore, at this time, the local path of the vehicle needs to be re-planned (the re-planned local path needs to be effectively linked with the current position of the vehicle) so as to ensure the comfort and safety of driving and reduce the difficulty of driving control of the vehicle.
For example, referring to fig. 2, when the driving state information is a longitudinal distance between the vehicle and a closest point of the planned local path, the abnormal driving state condition corresponds to: the longitudinal distance between the vehicle and the closest point of the planned local path is greater than a preset longitudinal distance threshold value. Wherein the longitudinal distance of the vehicle from the closest point of the planned local path is preferably: and the control system calculates the vehicle according to the current position of the vehicle and the planned path. More specifically, the abnormal driving state condition may be expressed by the following equation: path _ near _ id ═ 0& & fabs (pathdirerr) <90& & dis < 1. The path _ near _ id represents the number of the closest point of the planned local path at the previous moment, the pathdirerr represents the included angle between the connecting line direction of the planned local path and the current position of the vehicle and the driving direction of the vehicle, and the dis represents the longitudinal distance between the vehicle and the closest point of the planned local path.
In this embodiment, when the driver manually operates the vehicle to reverse, the vehicle may be behind the planned local path at the previous time. When the longitudinal distance between the vehicle and the closest point of the planned local path is judged to be larger than a preset longitudinal distance threshold value, the vehicle is shown to be far behind the planned local path, and the vehicle is difficult to follow the planned local path at the moment, so that the local path of the vehicle needs to be re-planned (the re-planned local path needs to be effectively connected with the current position of the vehicle).
For example, referring to fig. 2, when the driving state information is an included angle between the vehicle and a direction of a closest point of the planned local path, the abnormal driving state condition corresponds to: and the included angle between the vehicle and the direction of the closest point of the planned local path is greater than a preset included angle threshold value. The included angle between the vehicle and the direction of the closest point of the planned local path is preferably as follows: and the control system calculates the local path according to the starting point of the planned local path, the connecting line direction of the vehicle and the driving direction of the vehicle. The vehicle running direction is preferably detected by a steering wheel angle sensor. More specifically, the abnormal driving state condition may be expressed by the following equation: path _ DIR _ ERR > DIR _ ERR. And the path _ DIR _ ERR represents an included angle between the vehicle and the direction of the closest point of the planned local path, and the DIR _ ERR represents a preset included angle threshold value.
In this embodiment, due to vehicle control and execution of the vehicle itself, or when the vehicle is driven manually, there may be a case where the planned path cannot be completely followed, for example, the current actual position of the vehicle may be shifted from the closest point of the local path planned at the previous time. When the included angle between the vehicle and the direction of the closest point of the planned local path is judged to be larger than the preset included angle threshold value, the fact that the vehicle cannot completely follow the planned local path at the previous moment is indicated, or if the vehicle continues to follow the planned local path at the previous moment, the phenomena that the vehicle is turned over violently and excessively, the driving is violently swung, even overturned, and the like easily occur. Therefore, at this time, the local path of the vehicle needs to be re-planned (the re-planned local path needs to be effectively linked with the current position of the vehicle) so as to ensure the comfort and safety of driving and reduce the difficulty of driving control of the vehicle.
Illustratively, referring to fig. 2, the traffic status information includes: obstacle information on the planned local path and vehicle following state information of the vehicle; when the passing state information is acquired, the condition of not passing is: obstacles (which may be dynamic obstacles or static obstacles, etc.) exist on the planned local path, and the vehicle is in a non-following state currently. Wherein the obstacle information and the following state information are preferably: detected by the external sensing system of the vehicle and sent. More specifically, the impassable condition may be expressed by the equation: ob _ flag & & (cur _ chg _ STATE | ═ FOLLOW _ STATE). The ob _ flag indicates that an obstacle influencing traffic exists on the planned local path, cur _ chg _ STATE indicates the vehicle driving STATE at the current moment, and the FOLLOW _ STATE indicates the following STATE or the obstacle-encountering parking STATE.
It should be noted that the traffic status information may include only: obstacle information on the planned local path. Or the traffic state information may include traffic light information, traffic sign information, and the like, in addition to the obstacle information on the planned local path, and is not limited specifically herein.
In summary, in the above embodiments, by setting the condition of the impassable state corresponding to the traffic state information and the condition of the abnormal driving state corresponding to the driving state information, while ensuring the driving safety, the number of times of re-planning a local path of the vehicle can be effectively reduced, thereby reducing the difficulty of controlling the automatic driving motion. In addition, the times of re-planning the local path of the vehicle are effectively reduced, so that the vehicle does not need to change the local path frequently and does not turn frequently, the problem that the vehicle continuously swings due to frequent turning of the vehicle is avoided, and the driving comfort and safety of the vehicle can be improved.
Further, in any of the above embodiments, referring to fig. 2, before the step S13, the method further includes a step S12':
s12' obtaining the residual distance parameter of the planned local path of the vehicle at the last moment;
the remaining distance parameter obtaining process of this step may be performed simultaneously with step S10 or separately, and is not limited herein.
Then, the step S13 specifically includes steps S130 to S132:
s130, judging whether the residual distance parameter is smaller than a preset residual distance threshold value or not after judging that any local path re-planning condition is not met;
for example, the judgment equation of the remaining distance parameter may be specifically expressed as: main _ dis < ROAD _ REMAIN _ DISTANCE. The remaining _ dis represents the remaining DISTANCE parameter, and the ROAD _ REMAIN _ DISTANCE represents a preset remaining DISTANCE threshold.
The size of the remaining distance threshold is in direct proportion to the current vehicle speed of the vehicle, so that the vehicle condition of different vehicle speeds can be better adapted.
S131, if yes, prolonging the planned local path, and controlling the vehicle to run according to the prolonged local path;
and S132, if not, controlling the vehicle to run according to the planned local path.
In this embodiment, after it is determined that any one of the local path re-planning conditions is not satisfied, it is determined whether the remaining distance parameter is smaller than a preset remaining distance threshold; if not, controlling the vehicle to run according to the planned local path; if so, the planned local path is prolonged, and the vehicle is controlled to run according to the prolonged local path, so that the local path of the vehicle does not need to be re-planned, the continuity and consistency of the local path of the vehicle are ensured, and the problem that the local paths planned twice are transversely jumped because of re-planning of the local path can be avoided (namely, certain deviation exists in the transverse direction of the local paths planned twice).
It should be noted that, in the above embodiment, since the driving environment of the vehicle is complicated and varied, in order to make the driving of the vehicle more adaptive to different driving environments, the following manner may be adopted: the re-planning condition threshold (e.g., a positioning accuracy threshold or an included angle threshold) and the remaining distance threshold of each piece of driving state information may be set according to the type of the current driving environment of the vehicle. Namely: the driving environments of the vehicle may be classified in advance, each type of driving environment may be preset with a re-planning condition threshold and a remaining distance threshold of the corresponding driving state information, and then the control system of the vehicle may adopt the corresponding re-planning condition threshold and remaining distance threshold according to the detected current driving environment type. The driving environment of the vehicle may be classified according to the type of the road (for example, divided into an expressway, an urban road, a suburban road, etc.), the type of the road condition (for example, divided into a blocked road condition, a clear road condition, a congested road condition, etc.), and the like, which is not limited herein.
Example two:
fig. 3 is a schematic structural diagram of a partial path re-planning control device for an autonomous vehicle according to an embodiment of the present invention. The control device includes:
the information acquisition module 10 is configured to acquire current running state information of the vehicle and current traffic state information on a planned local path of the vehicle at a previous time;
the judging module 11 is configured to judge whether at least one preset local path re-planning condition is met according to the traffic state information and the driving state information; wherein the local path re-planning condition comprises: the traffic state information comprises a traffic state information and a traffic state information, wherein the traffic state information comprises traffic state information and traffic state information;
the first driving control module 12 is configured to replan the local path of the vehicle and control the vehicle to drive according to the replanned local path when it is determined that at least one of the local path replanning conditions is satisfied;
and the second running control module 13 is configured to control the vehicle to run according to the planned local path when it is determined that any one of the local path re-planning conditions is not satisfied.
As a refinement of the above, the driving state information includes at least one of: the method comprises the following steps of positioning accuracy of a vehicle, positioning accuracy change rate of the vehicle, planned local path on the vehicle at a moment, lane driving state of the vehicle on a global path, transverse distance between the vehicle and the nearest point of the planned local path, longitudinal distance between the vehicle and the nearest point of the planned local path, and included angle between the vehicle and the nearest point direction of the planned local path.
As an improvement of the above, when the running state information is the positioning accuracy of the vehicle, the abnormal running state condition includes: and the numerical value of the positioning precision is greater than a preset positioning precision threshold value.
As an improvement of the above, when the running state information is a change rate of the positioning accuracy of the vehicle, the abnormal running state condition includes: and the numerical value of the positioning precision change rate is greater than a preset positioning precision change rate threshold value.
As an improvement of the above solution, when the driving state information is a planned local path at a time on the vehicle, the abnormal driving state condition includes: the planned local path is not yet planned or is an invalid path.
As an improvement of the above, when the driving state information is a lane driving state of the vehicle on a global path, then the abnormal driving state condition includes: the lane driving state of the vehicle on the global path is changed;
wherein the lane driving state includes: normally driving along the original lane, starting to change to the left lane, driving along the left lane, changing the left lane to the original lane, starting to change to the right lane, driving along the right lane, and changing the right lane to the original lane.
As an improvement of the above, when the driving state information is a lateral distance between the vehicle and a closest point of the planned local path, the abnormal driving state condition includes: the lateral distance between the vehicle and the closest point of the planned local path is larger than a preset lateral distance threshold value.
As an improvement of the above solution, when the driving state information is a longitudinal distance between the vehicle and a closest point of the planned local path, the abnormal driving state condition includes: the longitudinal distance between the vehicle and the closest point of the planned local path is greater than a preset longitudinal distance threshold value.
As an improvement of the above solution, when the driving state information is an included angle between the vehicle and a direction of a closest point of the planned local path, the abnormal driving state condition includes: and the included angle between the vehicle and the direction of the closest point of the planned local path is greater than a preset included angle threshold value.
As an improvement of the above solution, the traffic status information includes: obstacle information on the planned local path and vehicle following state information of the vehicle;
when the passing state information is acquired, the condition of not passing comprises: an obstacle exists on the planned local path, and the vehicle is currently in a non-following state.
As an improvement of the above aspect, the control device further includes:
a parameter obtaining module, configured to obtain a remaining distance parameter of the planned local path at a previous time of the vehicle:
the second driving control module specifically includes:
the parameter comparison unit is used for judging whether the residual distance parameter is smaller than a preset residual distance threshold value or not after judging that any local path re-planning condition is not met; wherein the magnitude of the remaining distance threshold is proportional to the magnitude of the current vehicle speed of the vehicle;
the first response unit is used for prolonging the planned local path and controlling the vehicle to run according to the prolonged local path if the planned local path is the local path;
and the second response unit is used for controlling the vehicle to run according to the planned local path if the vehicle does not run according to the planned local path.
In summary, in the embodiment of the present invention, whether at least one preset local route re-planning condition is satisfied is determined according to the current traffic status information and the current driving status information of the vehicle; if the situation that any local path re-planning condition is not met is judged, the local path is not re-planned, or the vehicle is controlled to continue to run according to the planned local path; and replanning the local path of the vehicle only when judging that at least one local path replanning condition is met, thus avoiding replanning the local path at every moment according to the traffic state information and the running state information of the vehicle, effectively reducing the replanning times of the local path of the vehicle and further reducing the difficulty of automatic driving motion control. In addition, the times of re-planning the local path of the vehicle are effectively reduced, so that the vehicle does not need to change the local path frequently and does not turn frequently, the problem that the vehicle continuously swings due to frequent turning of the vehicle is avoided, and the driving comfort and safety of the vehicle can be improved.
Example three:
referring to fig. 4, a schematic diagram of a control system of an autonomous vehicle according to an embodiment of the present invention is shown. The control system of the autonomous vehicle of the embodiment includes: a processor 1, a memory 2 and a computer program stored in said memory 2 and operable on said processor, such as a local re-routing control program for an autonomous vehicle. The processor 1, when executing the computer program, implements the steps in each of the above-described embodiments of the method of local path re-planning control for an autonomous vehicle. Alternatively, the processor 1 implements the functions of the modules/units in the above-mentioned device embodiments when executing the computer program.
Illustratively, the computer program may be partitioned into one or more modules/units that are stored in the memory and executed by the processor to implement the invention. The one or more modules/units may be a series of computer program instruction segments capable of performing specific functions for describing the execution of the computer program in the local re-routing control device of the autonomous vehicle.
The control system of the autonomous vehicle may include, but is not limited to, a processor, a memory. It will be appreciated by those skilled in the art that the schematic diagram is merely an example of a control system for the autonomous vehicle and does not constitute a limitation of the control system for the autonomous vehicle, and may include more or fewer components than shown, or some components in combination, or different components, e.g., the control system for the autonomous vehicle may also include input-output devices, network access devices, a CAN bus, etc.
The Processor may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc. The general purpose processor may be a microprocessor or the processor may be any conventional processor or the like that is the control center of the control system of the autonomous vehicle, with various interfaces and lines connecting the various parts of the control system of the entire autonomous vehicle.
The memory may be used to store the computer programs and/or modules, and the processor may implement various functions of the control system of the autonomous vehicle by running or executing the computer programs and/or modules stored in the memory, as well as invoking data stored in the memory. The memory may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required by at least one function (such as a sound playing function, an image playing function, etc.), and the like; the storage data area may store data (such as audio data, a phonebook, etc.) created according to the use of the cellular phone, and the like. In addition, the memory may include high speed random access memory, and may also include non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), at least one magnetic disk storage device, a Flash memory device, or other volatile solid state storage device.
Wherein the module/unit integrated with the local re-planning control device/control system of the autonomous vehicle may be stored in a computer-readable storage medium if implemented in the form of a software functional unit and sold or used as a stand-alone product. Based on such understanding, all or part of the flow of the method according to the embodiments of the present invention may also be implemented by a computer program, which may be stored in a computer-readable storage medium, and when the computer program is executed by a processor, the steps of the method embodiments may be implemented. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution medium, and the like. It should be noted that the computer readable medium may contain content that is subject to appropriate increase or decrease as required by legislation and patent practice in jurisdictions, for example, in some jurisdictions, computer readable media does not include electrical carrier signals and telecommunications signals as is required by legislation and patent practice.
It should be noted that the above-described device embodiments are merely illustrative, where the units described as separate parts may or may not be physically separate, and the parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. In addition, in the drawings of the embodiment of the apparatus provided by the present invention, the connection relationship between the modules indicates that there is a communication connection between them, and may be specifically implemented as one or more communication buses or signal lines. One of ordinary skill in the art can understand and implement it without inventive effort.
While the foregoing is directed to the preferred embodiment of the present invention, it will be understood by those skilled in the art that various changes and modifications may be made without departing from the spirit and scope of the invention.
Claims (11)
1. A partial path re-planning control method for an autonomous vehicle, comprising:
acquiring current running state information of a vehicle and traffic state information on a planned local path at the last moment;
judging whether at least one preset local path re-planning condition is met or not according to the traffic state information and the running state information; wherein the local path re-planning condition comprises: the traffic state information comprises a traffic state information and a traffic state information, wherein the traffic state information comprises traffic state information and traffic state information;
when the local path replanning condition is judged to be met, replanning the local path of the vehicle, and controlling the vehicle to run according to the replanned local path;
when judging that any one of the local path re-planning conditions is not met, controlling the vehicle to run according to the planned local path;
wherein the traffic status information comprises: obstacle information on the planned local path and vehicle following state information of the vehicle;
when the passing state information is acquired, the condition of not passing comprises: an obstacle exists on the planned local path, and the vehicle is currently in a non-following state.
2. The partial path re-planning control method of an autonomous vehicle as claimed in claim 1, characterized in that the running state information includes at least one of: the method comprises the following steps of positioning accuracy of a vehicle, positioning accuracy change rate of the vehicle, planned local path on the vehicle at a moment, lane driving state of the vehicle on a global path, transverse distance between the vehicle and the nearest point of the planned local path, longitudinal distance between the vehicle and the nearest point of the planned local path, and included angle between the vehicle and the nearest point direction of the planned local path.
3. The partial path re-planning control method for an autonomous vehicle according to claim 2,
when the running state information includes the positioning accuracy of the vehicle, then the abnormal running state condition includes: the numerical value of the positioning precision is greater than a preset positioning precision threshold value;
when the driving state information includes a positioning accuracy change rate of the vehicle, then the abnormal driving state condition includes: and the numerical value of the positioning precision change rate is greater than a preset positioning precision change rate threshold value.
4. The partial path re-planning control method of an autonomous vehicle as claimed in claim 2, wherein when the travel state information includes a planned partial path at a time on the vehicle, then the abnormal travel state condition includes:
the planned local path is not yet planned or is an invalid path.
5. The local path re-planning control method of an autonomous vehicle as set forth in claim 2, wherein when the running state information includes a lane running state of the vehicle on a global path, then the abnormal running state condition includes:
the lane driving state of the vehicle on the global path is changed;
wherein the lane driving state includes: normally driving along the original lane, starting to change to the left lane, driving along the left lane, changing the left lane to the original lane, starting to change to the right lane, driving along the right lane, and changing the right lane to the original lane.
6. The partial path re-planning control method for an autonomous vehicle according to claim 2,
when the driving state information includes a lateral distance of the vehicle from a closest point of the planned local path, then the abnormal driving state condition includes: the transverse distance between the vehicle and the closest point of the planned local path is greater than a preset transverse distance threshold value;
when the driving state information is the longitudinal distance between the vehicle and the closest point of the planned local path, the abnormal driving state condition includes: the longitudinal distance between the vehicle and the closest point of the planned local path is greater than a preset longitudinal distance threshold value.
7. The partial path re-planning control method of an autonomous vehicle according to claim 2, wherein when the driving state information includes an angle of the vehicle to a direction of a closest point of a planned partial path, then the abnormal driving state condition includes:
and the included angle between the vehicle and the direction of the closest point of the planned local path is greater than a preset included angle threshold value.
8. The partial path re-planning control method for an autonomous vehicle according to any of claims 1 to 7, wherein before controlling the vehicle to travel along the planned partial path when it is determined that any of the partial path re-planning conditions is not satisfied, further comprising:
obtaining a remaining distance parameter of a planned local path of the vehicle at the previous moment;
and if it is determined that any one of the local path re-planning conditions is not satisfied, controlling the vehicle to travel according to the planned local path, specifically:
when judging that any one of the local path re-planning conditions is not met, judging whether the residual distance parameter is smaller than a preset residual distance threshold value; wherein the magnitude of the remaining distance threshold is proportional to the magnitude of the current vehicle speed of the vehicle;
if so, extending the planned local path, and controlling the vehicle to run according to the extended local path;
and if not, controlling the vehicle to run according to the planned local path.
9. A partial re-routing control apparatus for an autonomous vehicle, comprising:
the information acquisition module is used for acquiring the current running state information of the vehicle and the traffic state information on the planned local path at the last moment;
the judging module is used for judging whether at least one preset local path re-planning condition is met or not according to the traffic state information and the running state information; wherein the local path re-planning condition comprises: the traffic state information comprises a traffic state information and a traffic state information, wherein the traffic state information comprises traffic state information and traffic state information;
the first driving control module is used for replanning the local path of the vehicle and controlling the vehicle to drive according to the replanned local path when judging that at least one local path replanning condition is met;
the second driving control module is used for controlling the vehicle to drive according to the planned local path when judging that any one of the local path re-planning conditions is not met;
wherein the traffic status information comprises: obstacle information on the planned local path and vehicle following state information of the vehicle;
when the passing state information is acquired, the condition of not passing comprises: an obstacle exists on the planned local path, and the vehicle is currently in a non-following state.
10. A control system for an autonomous vehicle comprising a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, the processor when executing the computer program implementing a method of local re-routing control for an autonomous vehicle as claimed in any of claims 1 to 8.
11. A computer-readable storage medium, comprising a stored computer program, wherein the computer program, when executed, controls an apparatus in which the computer-readable storage medium is located to perform the method of controlling partial re-routing of a path for an autonomous vehicle as recited in any one of claims 1 to 8.
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