CN109765903B - Automatic driving planning method - Google Patents
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Abstract
The embodiment of the invention relates to an automatic driving planning method, which comprises the following steps: the automatic driving system generates characteristic area coordinate data of the characteristic mark and controls the vehicle to park; when the state data of the characteristic mark of the system and the state data of the characteristic mark of the image are first state data, controlling the vehicle to run according to the current path planning data and the speed control data; when the state data of the characteristic mark of the system is not the first state data and the state data of the characteristic mark of the image is the first state data, determining whether the movement speed of the characteristic mark is less than the preset lifting speed; when the movement speed of the characteristic mark is less than the preset lifting speed, controlling the vehicle to run according to the current path planning data and the speed control data; and when the movement speed of the characteristic mark is not less than the preset lifting speed or when the state data of the characteristic mark of the image is not the first state data, controlling the vehicle to run according to the backing path planning data and the backing speed control data.
Description
Technical Field
The invention relates to the field of automatic driving, in particular to an automatic driving planning method.
Background
With the development of economy and the rise of artificial intelligence technology, the automatic driving automobile is more and more concerned by the market. The automatic driving of the automobile refers to that a computer can automatically and safely operate the motor vehicle without any active operation of human beings by means of cooperative cooperation of artificial intelligence, visual calculation, radar, a monitoring device and a global positioning system.
And the valet parking is one of the key technologies of automatically driving the vehicle. In the current research technology, there is less research on the middle section of a vehicle entering the parking lot from outside the parking lot, and there are many problems to be solved. For example, how to determine parking lot entry landing bar traffic logic. The control of the lifting rod of the existing parking lot is mature, the control technology of the lifting rod in the parking lot management system is mature, the control of the lifting rod is realized through visual recognition of a license plate, and the technology is mature. However, the existing automatic driving technology lacks an automatic driving path planning scheme aiming at a lifting rod, and meanwhile, the technology which can be matched with a parking lot management system to realize that a vehicle automatically drives into the parking lot does not exist.
Disclosure of Invention
The invention aims to provide an automatic driving planning method aiming at the defects of the prior art, an automatic driving path planning scheme is determined aiming at the state of a lifting rod in a parking lot, and the automatic driving planning method is combined with a parking lot management system and the recognition of the state of the lifting rod by a vehicle, so that the vehicle can automatically and safely drive into the parking lot, and the blank of the related field is filled.
In order to achieve the above object, an embodiment of the present invention provides an automatic driving planning method, including:
the automatic driving system monitors image data of a vehicle running environment;
when the automatic driving system extracts image data of a characteristic mark from the image data of the vehicle running environment, generating characteristic area coordinate data of the characteristic mark;
when the coordinate data of the characteristic area is coincident with the current path planning data, monitoring the current vehicle position data, and controlling the vehicle to park according to the current vehicle position data and the preset deceleration;
acquiring state data of a characteristic mark of a system from a parking lot management system, and extracting the state data of the characteristic mark of the image from image data of the current characteristic mark;
when the state data of the characteristic mark of the system and the state data of the characteristic mark of the image are first state data, controlling the vehicle to run according to the current path planning data and the speed control data;
when the state data of the characteristic mark of the system is not the first state data and the state data of the characteristic mark of the image is the first state data, determining whether the movement speed of the characteristic mark in a preset time is less than a preset lifting speed;
when the movement speed of the characteristic mark is smaller than the preset lifting speed within the preset time, controlling the vehicle to run according to the current path planning data and the speed control data;
and when the movement speed of the characteristic mark is not less than the preset lifting speed within the preset time or when the state data of the characteristic mark of the image is not the first state data, generating backing path planning data and backing speed control data, and controlling the vehicle to run according to the backing path planning data and the backing speed control data.
Preferably, the feature region coordinate data for generating the feature flag specifically includes:
determining local coordinate data of the position of the characteristic mark and the current vehicle position;
and obtaining the coordinate data of the characteristic area according to the local coordinate data and the electronic map.
Preferably, when the image data of the feature mark is extracted from the image data of the vehicle running environment by the automatic driving system, the running speed of the automatic driving system does not exceed a preset running speed.
Preferably, when the feature area coordinate data coincide with the current path planning data, monitoring the current vehicle position data, and controlling the parking of the vehicle according to the current vehicle position data and the preset deceleration specifically includes:
obtaining starting position data and end position data of the characteristic area according to the coordinate data of the characteristic area;
determining whether the coordinate data of the characteristic region is coincident with the current path planning data;
and when the characteristic area coordinate data do not coincide with the current path planning data, updating the current path planning data according to the current vehicle position data and the new characteristic area starting position data, so that the updated path planning data coincide with the characteristic area coordinate data.
Further preferably, when the feature area coordinate data does not coincide with the current path planning data, the updating the current path planning data according to the current vehicle position data and the new feature area start position data specifically includes:
when the coordinate data of the characteristic area is not coincident with the current path planning data, obtaining a plurality of alternative position data according to the width of the vehicle, the width of the characteristic identification area and preset precision;
determining new feature area starting position data from the multiple candidate position data according to a depth-first search algorithm;
and updating the current path planning data according to the current vehicle position data and the new characteristic region starting point position data.
Preferably, the monitoring the current vehicle position data and controlling the parking of the vehicle according to the current vehicle position data and the preset deceleration specifically comprises:
when the coordinate data of the characteristic area is coincident with the current path planning data, monitoring the current vehicle position data;
and when the current vehicle position data correspond to the characteristic region starting point position data, controlling the vehicle to park before the characteristic region end point according to a preset deceleration.
Preferably, after the generating of the reverse path planning data and the reverse speed control data and the controlling of the vehicle driving according to the reverse path planning data and the reverse speed control data, the method further includes:
continuing to monitor the image data of the feature marks;
when the state data of the feature marks of the images extracted from the image data of the current feature marks is changed from second state data to first state data, determining whether the current vehicle position reaches an end point in the backing path planning data;
and when the current vehicle position does not reach the end point in the reversing path planning data, continuing to monitor the image data of the vehicle running environment by the vehicle, and extracting the image data of the characteristic mark from the image data of the vehicle running environment.
Further preferably, when the state data of the feature marker of the image extracted from the image data of the current feature marker is changed from the second state data to the first state data, and the current vehicle position reaches the end point in the reverse path planning data, the method further includes:
determining whether the entrance passing time is less than the preset passing time and whether the reversing times are less than the preset times;
and when the entrance passing time is less than the preset passing time and the backing-up times are less than the preset times, controlling the vehicle to run according to the current path planning data and the speed control data.
Further preferably, when the entry passing time is not less than the preset passing time, or the number of times of reversing is not less than the preset number of times, the method further includes:
and generating and outputting alarm information.
Further preferably, when the state data of the feature marker of the image extracted from the image data of the current feature marker is changed from the second state data to the first state data, and the current vehicle position has not reached the end point in the reverse path planning data, the method further includes:
and continuing to monitor the image data of the running environment of the vehicle by the vehicle, and determining the state data of the characteristic mark of the image as the first state data.
According to the automatic driving planning method provided by the embodiment of the invention, an automatic driving path planning scheme is determined according to the state of the lifting rod in the parking lot, and the automatic and safe driving of the vehicle into the parking lot is realized by combining the parking lot management system and the recognition of the state of the lifting rod by the vehicle, so that the blank of the related field is filled.
Drawings
FIG. 1 is a flow chart of an automated driving planning method provided by an embodiment of the present invention;
fig. 2 is a schematic diagram of the coordinate positions of the feature areas in the automatic driving planning method according to the embodiment of the present invention.
Detailed Description
The technical solution of the present invention is further described in detail by the accompanying drawings and embodiments.
The automatic driving planning method provided by the embodiment of the invention is realized in an automatic driving vehicle and used for processing the automatic driving method of the vehicle when the automatic driving vehicle encounters a lifting rod in the road driving process, and the flow chart of the method is shown in figure 1, and the method comprises the following steps:
specifically, the automatic driving system is implemented in an automatic driving vehicle, and includes a camera device, an infrared device, a laser radar device, and other monitoring devices for monitoring the driving environment around the vehicle in real time, so as to ensure the safe implementation of the automatic driving vehicle. The camera device collects images of the surrounding environment of the automatic driving vehicle to obtain image data of the driving environment of the vehicle.
in particular, the set characteristic marking can be understood as a lifting bar marking. When the vehicle runs to the front of the lifting rod, the vehicle can continue to move forwards after the lifting rod is required to be parked and waited for lifting.
When the image data of the feature mark is extracted from the image data of the vehicle running environment by the autonomous vehicle, it is described that the autonomous vehicle has a lifting bar in front of the current autonomous vehicle, and the vehicle can continue to run after the state of the lifting bar needs to be determined, that is, the following step 103 needs to be performed. When the image data of the feature marker is not extracted from the image data of the vehicle running environment by the autonomous vehicle, it is indicated that there is no drop bar before the current autonomous vehicle, the step 101 needs to be executed again, that is, the image data of the vehicle running environment is continuously monitored.
In some preferred embodiments, when the image data of the characteristic mark is extracted from the image data of the vehicle running environment by the automatic driving vehicle, which indicates that a lifting rod exists in front of the current automatic driving vehicle, the automatic driving system controls the maximum running speed of the current vehicle not to exceed a preset running speed, so as to ensure that a camera in a parking lot can identify the license plate number of the current vehicle.
103, generating feature area coordinate data of the feature marks;
specifically, when the image data of the feature mark is extracted from the image data of the vehicle running environment by the autonomous driving vehicle, it is described that there is a lifting lever in front of the current autonomous driving vehicle, and the autonomous driving system generates the feature area coordinate data of the feature mark. The feature region coordinate data may be understood as coordinates identifying the region in which the current feature tag is located.
More specifically, the automatic driving system first needs to determine the position of the feature mark and the local coordinate data of the current vehicle position, and then obtains the coordinate data of the feature area according to the local coordinate data and a preset electronic map. This process may be understood as a process of determining the position of the area where the feature marker is located and the relative coordinates from the current vehicle, and then converting the relative coordinates into global coordinates in the map coordinate system.
And after the characteristic region coordinate data is obtained by the automatic driving system, the start position data and the end position data of the characteristic region need to be obtained according to the characteristic region coordinate data. Fig. 2 is a schematic diagram of a coordinate position of a feature area in the automatic driving planning method provided in the embodiment of the present invention, and as shown in fig. 2, coordinates of a lifting rod represented by feature area coordinate data are P (x, y, θ), and according to P (x, y, θ), an automatic driving system can calculate and obtain start point position data P of the feature areaS(xS，yS，θS) And feature area end position data Pe(xe，ye，θe). The current vehicle needs to stop at the characteristic region end point PeSo that the parking lot management system can identify the current license plate. To ensure this, the automatic driving system needs to control the vehicle to start at the characteristic region PSThe vehicle speed control is started.
In a specific embodiment, when the coordinate data of the characteristic region is P (x, y, theta), the automatic driving system determines that the current vehicle needs to park at 1 meter before P, and the final position data P of the characteristic region is obtained according to P (x, y, theta) and 1 metere(xe，ye，θe). The autonomous driving system then determines that the vehicle needs to be at PeStarting to control the speed of the vehicle at the position 5 m before the vehicle, and then controlling the speed of the vehicle according to Pe(xe，ye，θe) And 5 m obtaining the starting point position data P of the characteristic regionS(xS，yS，θS)。
104, determining whether the coordinate data of the characteristic area is coincident with the current path planning data;
specifically, when there is a lifting bar in front of the current autonomous vehicle, it is further required to determine whether the original path of the vehicle passes through the area where the lifting bar is located, that is, whether the coordinate data of the characteristic area coincides with the current path planning data. If the characteristic area coordinate data does not coincide with the current path planning data, indicating that the original path of the vehicle does not pass through the area where the lifting bar is located, the following step 105 is performed. If the characteristic area coordinate data coincides with the current path planning data, indicating that the original path of the vehicle passes through the area where the lift pins are located, the following step 106 is performed.
105, updating the current path planning data according to the current vehicle position data and the new characteristic area starting point position data, so that the updated path planning data is overlapped with the characteristic area coordinate data;
specifically, when the feature area coordinate data does not coincide with the current path planning data, the automatic driving system needs to select a new feature area start position, so that the current path planning data coincides with the feature area coordinate data. That is, even if the original path of the vehicle passes through the area where the drop-off pole is located, the automatic driving system controls the vehicle to pass through the area where the drop-off pole is located as long as the drop-off pole is recognized in the image of the vehicle traveling environment.
Further specifically, the automatic driving system may calculate a plurality of candidate position data according to the vehicle width, the feature tag area width, and the preset precision, then determine new feature area start position data from the plurality of candidate position data according to a depth-first search algorithm, and finally update the current path planning data according to the current vehicle position data and the feature area start position data.
When calculating the candidate position data, the number of the candidate position data can be obtained according to equation 1:
i ═ H/Δ L (formula 1)
Where i is the number of candidate locations, Ht is the feature tag region width, H is vehicle width data, Δ L is the selection accuracy, Ht may be obtained by recognizing image data of the feature flag, and Δ L may be set to 1 meter or less in general.
specifically, when the current path planning data coincides with the feature area coordinate data (or the current path planning data coincides with the feature area coordinate data due to the path change in step 105), that is, when the current vehicle traveling path passes through the area where the lifting lever is located, the automatic driving system monitors the current vehicle position data, and when the current vehicle position data corresponds to the feature area starting point position data, it indicates that the vehicle has reached a position where deceleration is needed, the automatic driving system needs to control the vehicle to park before the feature area end point according to the preset deceleration.
In one specific example, and as further shown in FIG. 2, when the autonomous vehicle reaches a starting point PSAnd if the current actual vehicle speed is greater than the preset running speed, controlling the current actual vehicle speed to decelerate to the preset running speed, otherwise, keeping the vehicle speed unchanged. Vehicle arrival starting point PSThereafter, the vehicle is controlled to stop at the end point P according to the preset decelerationeAnd the parking lot management system can conveniently identify the current license plate and control the lifting rod.
in particular, the status data of the feature flags may be understood as status data of the lifting lever, including a first status data representing the lifting of the lifting lever (the lifting lever being perpendicular to the ground) and a second status data representing the falling of the lifting lever (the lifting lever being parallel to the ground). The manner in which the automatic driving system acquires the status data of the feature flags includes the following two:
in a first mode, the automatic driving system acquires status data of the system's signature from the parking lot management system. More specifically, the automatic driving system first attempts to connect to the current parking lot management system, and if connection to the current parking lot management system is possible, the status data of the system's feature flags are acquired from the current parking lot management system. It will be appreciated that the status data of the system's characteristic signs is determined by the parking manager management system.
In the second mode, the automatic driving system extracts the state data of the feature flag of the image from the image data of the current feature flag. More specifically, regardless of whether the automatic driving system is connected to the current parking lot management system in the first mode, the automatic driving system determines the status data of the feature marks by means of visual recognition, that is, the status data of the feature marks of the image is determined by extracting the status data of the feature marks of the image from the image data of the current feature marks.
specifically, first, in order to prevent erroneous determination that the preceding vehicle has not fallen after passing through the rear landing bar, the automatic driving system defaults the state data of the feature mark of the image determined by visual recognition to the second state data, and sets the state data of the feature mark of the image to the first state data when the state of the landing bar is recognized to be changed from the horizontal state to the vertical state. And then, the automatic driving system is connected with the current parking lot management system in a background communication mode to check the state data and determine whether the state data of the characteristic marks of the system obtained by the parking lot management system are the first state data.
When the state data of the characteristic mark of the system and the state data of the characteristic mark of the image are both the first state data, it is indicated that the state of the lifting rod determined by the automatic driving system through the parking lot management system is consistent with the state of the lifting rod determined through visual recognition, and both the states are the lifting state. The following step 111 is performed. If any one of the state data of the system feature mark and the state data of the image feature mark is not the first state data, it means that the state of the lifting lever determined by the automatic driving system through the parking lot management system and the state of the lifting lever determined by the visual recognition are in conflict with each other and further confirmation is required, and the following step 109 is executed.
specifically, when the state data of the characteristic mark of the system is not the first state data and the state data of the characteristic mark of the image is the first state data, it indicates that the automatic driving system obtains that the lifting lever is in the falling state through the parking lot management system, but obtains that the lifting lever is in the lifting state through visual recognition, and at this time, it is necessary to determine the movement speed of the lifting lever, that is, it is determined whether the lifting lever is being changed from the lifting state to the falling state, and then the following step 110 is executed.
When the status data of the system feature flag is the first status data and the status data of the image feature flag is not the first status data, or the status data of the system feature flag and the status data of the image feature flag are not the first status data, the following step 112 is executed.
specifically, when the state data of the feature flag of the system is not the first state data and the state data of the feature flag of the image is the first state data, it may be caused by whether the drop bar is being changed from the lifted state to the fallen state (the state data of the feature flag of the system has been set as the second state data in the parking lot management system, but it takes a certain time for the drop bar to land, so the state data of the feature flag of the image that the automatic driving system visually recognizes is still the first state data), or it may be caused by a failure of the parking lot management system, so the automatic driving system needs to determine the movement speed of the drop bar.
If the movement speed of the feature mark is less than the preset lifting speed within the preset time, it indicates that the movement state of the current lifting and lowering rod is a static state, that is, the current lifting and lowering rod is not changed from the lifting state to the falling state, then the following step 111 is executed. If the movement speed of the feature mark is not less than the preset lifting speed within the preset time, it indicates that the current lifting and lowering rod is in a moving state, that is, the current lifting and lowering rod is actually changed from the lifting state to the falling state currently, the following step 112 is executed.
The preset lifting speed may be set to approach zero.
specifically, when the state data of the system feature marker and the state data of the image feature marker are first state data, or when the state data of the system feature marker and the state data of the image feature marker are first state data, it indicates that the vehicle can pass through the current take-off and landing lever, the automatic driving system enters path planning and speed planning, controls the vehicle to run according to the current path planning data and speed control data, and passes through the current take-off and landing lever.
specifically, when the state data of the characteristic mark of the system is the first state data, and the state data of the characteristic mark of the image is not the first state data, or the state data of the characteristic mark of the system and the state data of the characteristic mark of the image are not the first state data, or the movement speed of the characteristic mark is not less than the preset lifting speed, it indicates that the vehicle cannot pass through the current lifting and lowering rod, the automatic driving system generates the backing path planning data and the backing speed control data, and controls the backing of the vehicle according to the backing path planning data and the backing speed control data.
specifically, in the process of controlling the vehicle to reverse by the automatic driving system, the state of the lifting rod is still monitored, that is, the image data of the characteristic mark is continuously monitored. When the automatic driving system monitors that the state data of the characteristic mark of the image is changed from the second state data to the first state data through visual recognition, which indicates that the current vehicle still possibly can pass through the lifting rod, step 111 is executed, that is, the automatic driving system enters path planning and speed planning, and controls the vehicle to run according to the current path planning data and speed control data, and the vehicle passes through the current lifting rod. When the automatic driving system monitors that the state data of the feature mark of the image is not changed from the second state data to the first state data through visual recognition, further judgment is needed according to the situation, and the following step 114 is executed.
specifically, when the automatic driving system monitors that the state data of the feature marks of the image is changed from the second state data to the first state data through visual recognition, the automatic driving system needs to determine whether the current reversing process is finished, that is, whether the current vehicle position reaches the end point in the reversing path planning data. When the current vehicle position has reached the end point in the reverse path planning data, which indicates whether the current reverse process has ended, the following step 115 needs to be executed. And if the current vehicle position does not reach the end point in the reverse path planning data, returning to step 113, namely, continuing to monitor the image data of the vehicle running environment by the vehicle, extracting the image data of the characteristic mark from the image data of the vehicle running environment, and further determining that the state data of the characteristic mark of the current image is changed from the second state data to the first state data, namely, further determining whether the current lifting rod can pass through.
specifically, when the automatic driving system monitors that the state data of the feature marks of the image is changed from the second state data to the first state data through visual recognition, and the current vehicle position reaches the end point in the reversing path planning data, the automatic driving system needs to determine whether the parking lot entrance passing time consumed by the current vehicle is less than the preset passing time or not, and whether the reversing frequency is less than the preset frequency or not. If the current vehicle consumes the parking lot entrance transit time less than the preset transit time and the number of times of reversing is less than the preset number of times, the method returns to step 102, namely the vehicle continues to monitor the image data of the vehicle running environment and determines whether the set characteristic mark is identified in the image of the vehicle running environment. If the current vehicle consumes the parking lot entrance passage time not less than the preset passage time or the number of times of reversing is not less than the preset number, the following step 116 is performed.
specifically, when the current passing time of the parking lot entrance consumed by the vehicle is not less than the preset passing time or the number of backing times is not less than the preset number of times, the current planning of automatically driving into the parking lot entrance through the lifting rod fails, and the automatic driving system generates alarm information to prompt a driver to take over driving.
It can be understood that, in the embodiment of the present invention, if the automatic driving system cannot be connected to the current parking lot management system, it is only determined whether the status data of the feature flags are the first status data in a visual recognition manner, and the embodiment of the present invention may also be implemented.
According to the automatic driving planning method provided by the embodiment of the invention, an automatic driving path planning scheme is determined according to the state of the lifting rod in the parking lot, and the automatic and safe driving of the vehicle into the parking lot is realized by combining the parking lot management system and the recognition of the state of the lifting rod by the vehicle, so that the blank of the related field is filled.
Those of skill would further appreciate that the various illustrative components and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the various illustrative components and steps have been described above generally in terms of their functionality in order to clearly illustrate this interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied in hardware, a software module executed by a processor, or a combination of the two. A software module may reside in Random Access Memory (RAM), memory, Read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM powertrain control method, or any other form of storage medium known in the art.
The above-mentioned embodiments are intended to illustrate the objects, technical solutions and advantages of the present invention in further detail, and it should be understood that the above-mentioned embodiments are merely exemplary embodiments of the present invention, and are not intended to limit the scope of the present invention, and any modifications, equivalent substitutions, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (10)
1. An automated driving planning method, the method comprising:
the automatic driving system monitors image data of a vehicle running environment;
when the automatic driving system extracts image data of a characteristic mark from the image data of the vehicle running environment, generating characteristic area coordinate data of the characteristic mark of an image; wherein the characteristic mark of the image is specifically a lifting rod mark;
when the coordinate data of the characteristic area is matched with the current path planning data, monitoring the current vehicle position data, and controlling the vehicle to park according to the current vehicle position data and the preset deceleration;
acquiring state data of a characteristic mark of a system from a parking lot management system, and extracting the state data of the characteristic mark of the image from image data of the current characteristic mark;
when the state data of the characteristic mark of the system and the state data of the characteristic mark of the image are first state data, controlling the vehicle to run according to the current path planning data and the speed control data; wherein the first state data is state data of the lifting rod mark being lifted;
when the state data of the characteristic mark of the system is not the first state data and the state data of the characteristic mark of the image is the first state data, determining whether the movement speed of the characteristic mark of the image in a preset time is less than a preset lifting speed;
when the movement speed of the characteristic mark of the image is smaller than the preset lifting speed within the preset time, controlling the vehicle to run according to the current path planning data and the speed control data;
and when the movement speed of the characteristic mark of the image is not less than the preset lifting speed within the preset time, or when the state data of the characteristic mark of the image is not the first state data, generating backing path planning data and backing speed control data, and controlling the vehicle to run according to the backing path planning data and the backing speed control data.
2. The automated driving planning method according to claim 1, wherein the feature region coordinate data of the feature marker of the generated image is specifically:
determining local coordinate data of the position of the feature mark of the image and the current vehicle position;
and obtaining the coordinate data of the characteristic area according to the local coordinate data and the electronic map.
3. The automated driving planning method according to claim 1, wherein when the automated driving system extracts image data of a feature sign in the image data of the vehicle running environment, a running speed of the automated driving system does not exceed a preset running speed.
4. The automated driving planning method according to claim 1, wherein the monitoring of the current vehicle position data and the controlling of the parking of the vehicle according to the current vehicle position data and the preset deceleration when the characteristic region coordinate data matches the current path planning data is:
obtaining starting position data and end position data of the characteristic area according to the coordinate data of the characteristic area;
determining whether the feature area coordinate data matches current path planning data;
and when the characteristic area coordinate data are not matched with the current path planning data, updating the current path planning data according to the current vehicle position data and the new characteristic area starting point position data, so that the updated path planning data are matched with the characteristic area coordinate data.
5. The autopilot planning method of claim 4, wherein, when the feature area coordinate data does not match the current path planning data, the updating of the current path planning data based on the current vehicle position data and the new feature area start position data is specifically:
when the coordinate data of the characteristic area is not matched with the current path planning data, obtaining a plurality of alternative position data according to the width of the vehicle, the width of the characteristic identification area and preset precision;
determining new feature area starting position data from the multiple candidate position data according to a depth-first search algorithm;
and updating the current path planning data according to the current vehicle position data and the new characteristic region starting point position data.
6. The automated driving planning method according to claim 1, wherein the monitoring of the current vehicle position data and the controlling of the parking of the vehicle based on the current vehicle position data and the preset deceleration are specifically:
when the coordinate data of the characteristic area is matched with the current path planning data, monitoring the current vehicle position data;
and when the current vehicle position data correspond to the characteristic region starting point position data, controlling the vehicle to park before the characteristic region end point according to a preset deceleration.
7. The automated driving planning method of claim 1, wherein after the generating reverse path planning data and reverse speed control data and controlling vehicle travel according to the reverse path planning data and the reverse speed control data, the method further comprises:
continuing to monitor the image data of the feature marks;
when the state data of the feature marks of the images extracted from the image data of the current feature marks is changed from second state data to first state data, determining whether the current vehicle position reaches an end point in the backing path planning data; wherein the second state data is state data of the falling of the lifting rod mark;
and when the current vehicle position does not reach the end point in the reversing path planning data, continuing to monitor the image data of the vehicle running environment by the vehicle, and extracting the image data of the characteristic mark from the image data of the vehicle running environment.
8. The automated driving planning method according to claim 7, wherein when the state data of the feature marks of the image extracted from the image data of the current feature marks is changed from the second state data to the first state data, and the current vehicle position reaches an end point in the reverse path planning data, the method further comprises:
determining whether the entrance passing time is less than the preset passing time and whether the reversing times are less than the preset times;
and when the entrance passing time is less than the preset passing time and the backing-up times are less than the preset times, controlling the vehicle to run according to the current path planning data and the speed control data.
9. The automated driving planning method according to claim 8, wherein when the entrance passage time is not less than the preset passage time or the number of reversing is not less than the preset number, the method further comprises:
and generating and outputting alarm information.
10. The automated driving planning method according to claim 7, wherein when the state data of the feature marks of the image extracted from the image data of the current feature marks is changed from the second state data to the first state data, and the current vehicle position has not reached the end point in the reverse path planning data, the method further comprises:
and continuing to monitor the image data of the running environment of the vehicle by the vehicle, and determining the state data of the characteristic mark of the image as the first state data.
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| CN201910148615.1A CN109765903B (en) | 2019-02-28 | 2019-02-28 | Automatic driving planning method |
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