CN114572245A

CN114572245A - Station stop control method, device and equipment based on automatic driving vehicle

Info

Publication number: CN114572245A
Application number: CN202210193359.XA
Authority: CN
Inventors: 王泽旭; 刘涛
Original assignee: Apollo Zhilian Beijing Technology Co Ltd; Apollo Zhixing Technology Guangzhou Co Ltd
Current assignee: Apollo Zhilian Beijing Technology Co Ltd; Apollo Zhixing Technology Guangzhou Co Ltd
Priority date: 2022-02-28
Filing date: 2022-02-28
Publication date: 2022-06-03

Abstract

The disclosure provides a station parking control method, device and equipment based on an automatic driving vehicle, and relates to the field of artificial intelligence, in particular to the fields of automatic driving, autonomous parking, a vehicle network, an intelligent cabin, intelligent traffic and the like. The specific implementation scheme is as follows: acquiring obstacle information corresponding to a current station on a driving path, wherein the obstacle information is information of obstacles in a preset geographical range corresponding to the current station; determining an optimal parking area according to the barrier information corresponding to the current station and a preset parking area set; the parking area set comprises a plurality of adjacent parking areas, and the parking areas are determined based on the vehicle information of the current automatic driving vehicle and the lane line information corresponding to the current station; and determining a parking path according to the optimal parking area and the current position of the current automatic driving vehicle, and controlling the current automatic driving vehicle to park to the optimal parking area according to the parking path.

Description

Station stop control method, device and equipment based on automatic driving vehicle

Technical Field

The disclosure relates to the fields of automatic driving, autonomous parking, vehicle networks, intelligent cabins, intelligent transportation and the like in artificial intelligence, in particular to a station parking control method, device and equipment based on an automatic driving vehicle.

Background

With the development of the automatic driving technology, the automatic driving vehicle has been applied to life. The automatic driving vehicle can be used as a public transport means to facilitate the life of people.

In the related art, when an autonomous vehicle is used as a public transportation means, the autonomous vehicle needs to stop at a station so that a passenger can ride the autonomous vehicle.

However, in the above manner, the stop situations at the station are different every day, and the automatically-driven vehicle needs to wait for the free space at the station and then drive to the station to stop when stopping at the station every time; such a method may cause that the automatic driving vehicle needs to spend a long time to stop at the station, and the passenger needs to wait for a long time, resulting in an ultra-poor riding experience of the passenger.

Disclosure of Invention

The disclosure provides a station stop control method, device and equipment based on an automatic driving vehicle.

According to a first aspect of the present disclosure, there is provided an autonomous vehicle-based station stop control method, including:

obtaining obstacle information corresponding to a current station on a driving path, wherein the obstacle information is information of obstacles in a preset geographical range corresponding to the current station.

Determining an optimal parking area according to the barrier information corresponding to the current station and a preset parking area set; the parking area set comprises a plurality of adjacent parking areas, and the parking areas are determined based on the vehicle information of the current automatic driving vehicle and the lane line information corresponding to the current station.

And determining a parking path according to the optimal parking area and the current position of the current automatic driving vehicle, and controlling the current automatic driving vehicle to park to the optimal parking area according to the parking path.

According to a second aspect of the present disclosure, there is provided an automated vehicle-based station stop control apparatus including:

the system comprises a first acquisition unit, a second acquisition unit and a third acquisition unit, wherein the first acquisition unit is used for acquiring obstacle information corresponding to a current station on a driving path, and the obstacle information is information of obstacles in a preset geographical range corresponding to the current station.

The first determining unit is used for determining an optimal parking area according to the barrier information corresponding to the current station and a preset parking area set; the parking area set comprises a plurality of adjacent parking areas, and the parking areas are determined based on the vehicle information of the current automatic driving vehicle and the lane line information corresponding to the current station.

And the second determining unit is used for determining a parking path according to the optimal parking area and the current position of the current automatic driving vehicle.

And the third determining unit is used for controlling the current automatic driving vehicle to park in the optimal parking area according to the parking path.

According to a third aspect of the present disclosure, there is provided an electronic device comprising:

at least one processor; and

a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,

the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of the first aspect.

According to a fourth aspect of the present disclosure, there is provided a non-transitory computer readable storage medium having stored thereon computer instructions for causing the computer to perform the method of the first aspect.

According to a fifth aspect of the present disclosure, there is provided a computer program product comprising: a computer program, stored in a readable storage medium, from which at least one processor of an electronic device can read the computer program, execution of the computer program by the at least one processor causing the electronic device to perform the method of the first aspect.

According to a sixth aspect of the present disclosure, there is provided an autonomous vehicle comprising: the apparatus as described in the second aspect of the disclosure.

The technology according to the present disclosure solves the problem that the riding experience of the passenger is too poor because the passenger needs to wait for a long time.

It should be understood that the statements in this section do not necessarily identify key or critical features of the embodiments of the present disclosure, nor do they limit the scope of the present disclosure. Other features of the present disclosure will become apparent from the following description.

Drawings

The drawings are included to provide a better understanding of the present solution and are not to be construed as limiting the present disclosure. Wherein:

FIG. 1 is a scene diagram of an autonomous vehicle based stop control method that may implement an embodiment of the present disclosure;

FIG. 2 is a schematic diagram according to a first embodiment of the present disclosure;

FIG. 3 is a schematic diagram according to a second embodiment of the present disclosure;

FIG. 4 is a diagram of still another application scenario of the station stop control method based on an autonomous vehicle according to the present disclosure;

FIG. 5 is a diagram of another application scenario of the disclosed autonomous vehicle based stop control method;

FIG. 6 is a schematic diagram according to a third embodiment of the present disclosure;

FIG. 7 is a schematic diagram according to a third embodiment of the present disclosure;

FIG. 8 is a schematic diagram according to a fifth embodiment of the present disclosure;

fig. 9 is a block diagram of an electronic device for implementing a method of an autonomous vehicle based station stop control method of an embodiment of the present disclosure.

Detailed Description

Exemplary embodiments of the present disclosure are described below with reference to the accompanying drawings, in which various details of the embodiments of the disclosure are included to assist understanding, and which are to be considered as merely exemplary. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the present disclosure. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.

Currently, with the continuous development of the automatic driving technology, the automatic driving vehicle has been gradually applied to life. Also, the automatic driving technique can be applied to public transportation means, such as automatically driving a bus, and the like.

In the prior art, when the autonomous vehicle is a public transportation vehicle with an autonomous driving technology, the autonomous vehicle needs to stop at a station where passengers can conveniently get on the vehicle or get off the vehicle, wherein the station is the stop position of the autonomous vehicle.

Fig. 1 is a scene diagram of an autonomous vehicle-based station stop control method in which an embodiment of the present disclosure may be implemented. As shown in fig. 1, the figure includes a stop 101, a road edge 102, an autonomous vehicle 103, a first road centerline 104, a first lane line 105, a second road centerline 106, and a second lane line 107. When the autonomous vehicle 103 is operating as a public transportation means in the first lane line 101 and the road edge 102, when the autonomous vehicle 103 is approaching the stop 101, the autonomous vehicle 103 needs to stop at the stop 101 according to a stop request so that passengers get on and off the vehicle.

However, in a road, traffic conditions at a station where vehicles stop every day are different, and when an autonomous vehicle needs to stop at the station, the autonomous vehicle needs to wait for enough space at the station so that the autonomous vehicle can stop, and the autonomous vehicle eventually stops at the station. That is, when the stop at which the automatic driving vehicle needs to stop is occupied by other vehicles, pedestrians and other obstacles, at this time, the automatic driving vehicle waits for other vehicles or pedestrians to leave the stop, and then the automatic driving vehicle stops at the stop, so that passengers get on or off the vehicle at the stop.

In another possible case, when the autonomous vehicle needs to stop at a certain station, in this case, in order to avoid an obstacle at the station, the autonomous vehicle randomly selects the rest of the stop points to stop for passengers to get on or off, and the randomly selected stop points may be far away from the original station, which may result in poor riding experience for the passengers.

In order to avoid at least one of the above technical problems, the inventors of the present disclosure have made creative efforts to obtain the inventive concept of the present disclosure: determining a plurality of adjacent parking areas based on the vehicle information of the current automatic driving vehicle and the lane line information corresponding to the stop, taking the plurality of adjacent parking areas as a preset parking area set, selecting an optimal parking area according to the obstacle information corresponding to the current stop and the preset parking area set, and determining a parking path to enable the vehicle to park in the optimal parking area by combining the optimal parking area and the current position of the current automatic driving vehicle.

Based on the invention concept, the invention provides a station parking control method, a station parking control device and station parking control equipment based on an automatic driving vehicle, which belong to the fields of automatic driving, autonomous parking, vehicle networks, intelligent cabins, intelligent transportation and the like in artificial intelligence, so that the automatic driving vehicle can park in an optimal parking area, and the riding experience of passengers is improved.

Fig. 2 is a schematic diagram of an autonomous vehicle-based station stop control method according to a first embodiment of the present disclosure, including:

s201, obtaining obstacle information corresponding to a current station on a driving path, wherein the obstacle information is information of obstacles in a preset geographical range corresponding to the current station.

For example, the execution subject of this embodiment may be a station stop control device based on an autonomous vehicle, where the station stop control device may be a server (such as a cloud-end server or a local server), a processor, a chip, and the like, and this embodiment is not limited thereto. The embodiment takes an execution main body as an electronic device as an example for description.

In the process of driving the automatic driving vehicle, the current station of the driving path of the automatic driving vehicle is a parking position where the automatic driving vehicle needs to stop currently.

When the automatic driving vehicle needs to stop at the current station, the electronic equipment can acquire the obstacle information in the preset geographic range at the current station. The obstacle information refers to data of other objects within a preset geographic range, for example, data of vehicles driving on a road, and the vehicle data may include data of vehicle volume, position, and the like.

S202, determining an optimal parking area according to the barrier information corresponding to the current station and a preset parking area set; the parking area set comprises a plurality of adjacent parking areas, and the parking areas are determined based on vehicle information of the current automatic driving vehicle and lane line information corresponding to the current station.

For example, the vehicle information of the current autonomous vehicle refers to data of the current autonomous vehicle itself, for example, data such as a vehicle volume of the current autonomous vehicle, a vehicle speed during driving, and the like, and the vehicle information of the current autonomous vehicle may be data stored in the autonomous vehicle in advance, or may be data acquired by a sensor on the current autonomous vehicle in real time during driving of the autonomous vehicle.

The lane line information corresponding to the current station may be lane line shape information (for example, the current lane line is a straight line or a curved line when turning, etc.) included in the road where the current station is located, and the distance information between the lane lines and the station, the distance information between different lane lines, etc., and is not limited in particular here.

The preset parking area set comprises a plurality of adjacent parking areas, and each parking area is determined based on the vehicle information of the current automatic driving vehicle and the lane line information corresponding to the current station, wherein the occupied area of each parking area is larger than or equal to that of the current automatic driving vehicle, namely, each parking area can meet the requirement that the current automatic driving vehicle parks. It should be noted that the preset parking area set herein may be calculated by the electronic device in real time when the autonomous vehicle needs to park, or may be a parking area set corresponding to the current station that is pre-stored, and is not limited herein. Also, the parking areas of the preset set of parking areas may be set before the station, i.e. areas where the autonomous vehicle has not yet driven to the horizontal line where the station is located. It is also possible to set an area beyond the horizontal line of the stop, i.e. the line running along the lane line in a direction perpendicular to and passing through the stop, after the stop, i.e. when the autonomous vehicle is driving.

The electronic device may determine an optimal parking area in the preset parking area set based on the acquired obstacle information of the current station and the preset parking area set, where the optimal parking area is a station that can accommodate the current autonomous driving vehicle and is closest to the current station.

In an example, the obstacle information in the preset address range acquired by the electronic device includes obstacle information in each parking area in a preset parking area set corresponding to the current station and obstacle information outside the preset parking area set. For example, if a part of an area occupied by an obstacle is located in a certain parking area in the preset parking area set, and another part of the area is not located in any parking area in the preset parking set, when determining whether the certain parking area is an optimal parking area, not only the area occupied by the obstacle in the certain parking area but also the area occupied by any parking area not located in the preset parking set need to be considered, so as to avoid that the subsequent obstacle completely enters the certain parking area, which cannot accommodate the current autonomous vehicle.

S203, determining a parking path according to the optimal parking area and the current position of the current automatic driving vehicle.

For example, after the electronic device determines the optimal parking area, the electronic device may determine a parking path of the current vehicle based on the current position of the current autonomous vehicle and the position of the optimal parking area.

In one example, when the electronic device determines a stopping path, a plurality of paths can be planned with the current position of the current autonomous vehicle as a starting point and the optimal stopping area as a finishing point, and the optimal stopping area and the path with the shortest time consumption of the current autonomous vehicle are preferentially selected as the stopping path by combining lane line information in the current driving path.

And S204, controlling the current automatic driving vehicle to park to the optimal parking area according to the parking path.

For example, after determining the parking path through step S203, the electronic device may control the current autonomous vehicle to park in the optimal parking area according to the parking path.

In one example, in the process that the electronic device controls the current automatic driving vehicle to stop according to the determined stopping path, the electronic device may also adjust the determined stopping path in real time, so as to control the current automatic driving vehicle to stop in the optimal stopping area.

In the embodiment, the optimal parking area is selected from the plurality of parking areas as the parking area of the current automatic driving vehicle through the preset parking area set formed by the plurality of parking areas determined based on the vehicle information of the current automatic driving vehicle and the lane line information corresponding to the current station and the acquired barrier information corresponding to the current station, so that the problems that in the related art, the time consumed for the automatic driving vehicle to park and park when the automatic driving vehicle waits for the empty space at the station all the time is long, and the user experience is poor are solved.

Fig. 3 is a schematic diagram of an autonomous vehicle-based station stop control method according to a second embodiment of the present disclosure, including:

s301, a docking area set is obtained.

For example, the execution subject of this embodiment may be a station parking control device based on an autonomous vehicle, where the station parking control device may be a server (such as a cloud-end server or a local server), a processor, a chip, and the like, and this embodiment is not limited thereto. The embodiment takes an execution main body as an electronic device as an example for description.

In the running process of the current automatic driving vehicle, the electronic equipment can acquire a parking area set on a running path of the current automatic driving vehicle.

In one example, step S301 includes the following implementation manners:

step S301, in a first implementation manner, obtaining lane line information corresponding to each station on a driving path, where the lane line information includes a lane line position of a lane line adjacent to the station; acquiring the site type corresponding to each site on the driving path; determining a parking area set corresponding to a station according to the lane line information, the station type and the vehicle occupied area in the vehicle information of the current automatic driving vehicle; and the parking areas in the parking area set are larger than or equal to the vehicle floor area of the current automatic driving vehicle.

Illustratively, the site category is used to indicate the shape of the road edge line to which the current site corresponds. For example, the site category may be divided into a walk-through site and an estuary site.

In this embodiment, the vehicle floor area in the vehicle information of the current autonomous vehicle.

For each station on the driving path, the electronic device determines a set of parking areas corresponding to the station based on the lane line position of the lane line adjacent to the station, the station category, and the vehicle floor area of the current autonomous vehicle, and the parking area corresponding to each parking area in the set of parking areas needs to satisfy the vehicle floor area of the current autonomous vehicle.

When the electronic device acquires the lane line information, the lane line information may be determined by combining with the road network device, or may be determined based on map information stored in the current electronic device.

By the determination method of the parking area set in the embodiment, the problem that the subsequent current automatic driving vehicle cannot park in the parking area set due to the fact that the parking area in the parking area set does not conform to the vehicle floor area of the current automatic driving vehicle can be avoided. In addition, in the embodiment, when determining the docking area set, the site type is also considered, so that the manner of determining the docking area set can be applied to different site types.

The "determining a parking area set corresponding to a station according to the lane line information, the station category, and the vehicle floor area in the vehicle information of the current automatic driving vehicle" includes: determining a parking area including a station according to the lane line information, the station type and the vehicle floor area in the vehicle information of the current automatic driving vehicle; and determining an area adjacent to the parking area including the station as other parking areas according to the lane line information and the vehicle floor area in the vehicle information of the current automatic driving vehicle so as to obtain a parking area set.

For example, in this embodiment, when determining the set of docking areas corresponding to the sites, first, determining the docking areas including the sites is considered. When the parking area containing the station is determined, the parking area containing the station and capable of containing the current automatic driving vehicle is determined based on the station type of the current station, the floor area of the current automatic driving vehicle and the lane line information. After the parking area including the station is determined, based on the lane information and the vehicle area of the current autonomous vehicle, the area adjacent to the parking area including the station is continuously determined as another parking area, and then the parking area including the station and the another parking area are used as a set of parking areas when the current autonomous vehicle needs to park at the current station, that is, when the another parking area is determined, the another parking area including the station is determined.

For example, when determining a parking area including a station, a parking area adjacent to the parking area including the station may be selected as another parking area in a neighboring lane or the same lane in which the parking area is located.

In this embodiment, when determining the parking area set, first, a parking area including a station is determined based on the station type, lane line information, and a floor area of the current autonomous vehicle, and then, other parking areas are determined in an area adjacent to the parking area including the station based on the lane line information and the floor area of the current autonomous vehicle, so that the current autonomous vehicle can finally park in the station or an area adjacent to the station by the determination method of the parking area set, and passenger riding experience is improved.

Step S301, receiving a docking area set sent by a remote device in a second implementation manner; the parking area set is determined according to lane line information corresponding to each station on the driving path, station types corresponding to each station on the driving path and vehicle floor areas in the vehicle information of the current automatic driving vehicle.

For example, in the present embodiment, a set of parking areas of the current autonomous vehicle in the travel path is stored in advance in the remote device, wherein the travel path of the current autonomous vehicle includes a plurality of stations. The set of stop areas for each stop is determined based on the stop category corresponding to the stop and the vehicle footprint in the vehicle information of the current autonomous vehicle.

When the current autonomous driving vehicle needs to stop at a certain station, the electronic device may request the remote device for a stopping area set corresponding to the station, and then the electronic device may receive the stopping area set of the station returned by the remote device. In addition, if the current autonomous driving vehicle drives away from the station, the electronic device may also delete the set of parking areas corresponding to the station.

In this embodiment, when the electronic device obtains the docking area set corresponding to each site, the docking area set sent by the electronic device may be directly received, thereby avoiding occupying computing resources of the electronic device.

S302, obstacle information corresponding to a current station on a driving path is obtained, wherein the obstacle information is information of obstacles in a preset geographical range corresponding to the current station.

In one example, step S302 includes the following implementation manners:

in a first implementation manner of step S302, obstacle information corresponding to a current station on a travel path is acquired by a millimeter wave radar on the current autonomous vehicle.

In a second implementation manner of step S302, the obstacle information corresponding to the current station on the driving path, which is sent by the acquisition device located on the current station, is received.

In this embodiment, when obtaining the obstacle information corresponding to the current station, in a first implementation manner, a millimeter wave radar is installed on the current autonomous vehicle, and the electronic device may determine the obstacle information corresponding to the current station on the driving path by obtaining data sensed by the millimeter wave radar in real time. Or the obstacle information may be acquired by an acquisition device installed at a station corresponding to the station, and the acquisition device transmits the obstacle information to the electronic device in real time after the electronic device requests the acquisition device to acquire the obstacle information.

S303, the docking areas in the docking area set have priority; the obstacle information comprises data information of obstacles in the parking areas with the ith priority in the parking area set; and repeating the steps S304-S305 until an optimal parking area is determined, wherein i is a positive integer greater than or equal to 1, and the initial value of i is 1.

The parking area set comprises a plurality of adjacent parking areas, and the parking areas are determined based on vehicle information of the current automatic driving vehicle and lane line information corresponding to the current station.

Illustratively, the priority of the docking areas refers to a determination sequence for determining whether the docking areas in the docking area set of the current site are the optimal docking areas when the optimal docking areas are determined.

In one example, the center point of the parking areas in the parking area set is located on a line along a preset direction, and the preset direction is a direction opposite to the driving direction along the driving path.

Illustratively, in the present example, when determining a parking area of the set of parking areas, the center point of the parking area is located on a line in a direction opposite to the traveling direction of the current autonomous vehicle traveling path. That is, under the same coordinate system, the coordinate value of the center point of any one of the set of parking areas in the driving direction of the current autonomous vehicle is located between the coordinate value of the station in the driving direction and the coordinate value of the current autonomous vehicle in the driving direction. Furthermore, when the coordinate value of the center point of the parking area in the traveling direction of the current autonomous vehicle exceeds the interval formed by the coordinate value of the station in the traveling direction and the coordinate value of the current autonomous vehicle in the traveling direction, at this time, the current autonomous vehicle can pass through the station in the parking process and stop after continuously traveling for a long distance, and a passenger needing to take the autonomous vehicle at the station may mistakenly think that the autonomous vehicle does not stop at the station and misses taking a bus, so that the riding experience of the user is not high.

S304, if the fact that the current automatic driving vehicle can be parked into the parking area with the ith priority is determined according to the data information of the obstacles in the parking area with the ith priority and the vehicle floor area of the current automatic driving vehicle, determining the parking area with the ith priority as the optimal parking area.

For example, the data information of the obstacle in the obstacle information may include data of a shape, a volume, and the like of the obstacle.

When the parking areas have the priorities, when the optimal parking area is determined, whether the current automatic driving vehicle can park in the parking area with the highest priority is judged at first. In this embodiment, the smaller the value of i, the higher the priority. And, when determining whether the autonomous vehicle can park, it is also necessary to combine the data information of the obstacles in the currently determined parking area and the vehicle floor area of the current autonomous vehicle to determine whether the autonomous vehicle can be accommodated in the current parking area. In a possible case, it is also considered whether or not the requirement for a forward turning of the vehicle or the like at the time of the entry and exit of the autonomous vehicle can be satisfied. In one example, the closer to the station, the higher the priority of the parking area.

In one example, in the step S304 of performing "determining that the current autonomous vehicle can be parked into the parking area of the ith priority according to the data information of the obstacles within the parking area of the ith priority and the vehicle floor area of the current autonomous vehicle", the following implementation may be adopted:

first implementation in step S304: the data information includes an obstacle footprint; determining the remaining area of the parking area with the ith priority according to the area of the parking area with the ith priority and the occupied area of the obstacles in the parking area with the ith priority; and if the remaining area of the parking area with the ith priority is determined to be larger than or equal to the vehicle floor area of the current automatic driving vehicle, determining that the current automatic driving vehicle can park in the parking area with the ith priority.

For example, when determining whether the current autonomous vehicle can park into the parking area of the ith priority, the remaining area in the parking area of the ith priority, that is, the area not occupied by the obstacle, may be obtained after performing the subtraction processing based on the area of the parking area of the ith priority and the obstacle occupation area of the obstacle in the parking area of the ith priority. Then, whether the vehicle can be parked in the parking area of the ith priority is determined by comparing the unoccupied remaining area in the parking area of the ith priority with the occupied area of the current autonomous vehicle. And when the remaining area of the parking area with the ith priority is determined to be larger than or equal to the vehicle floor area of the current automatic driving vehicle, determining that the parking area can be parked, otherwise, determining that the parking area can not be parked.

In this embodiment, if it is determined that the remaining area of the floor area not occupied by the obstacle in the parking area is greater than or equal to the vehicle floor area of the current autonomous vehicle, it is determined that the current autonomous vehicle can park. The method provided by the embodiment is easy to implement and occupies less computing resources.

Second implementation in step S304: the data information comprises the occupied area of the obstacle and the moving speed of the obstacle; determining the remaining area of the parking area with the ith priority according to the area of the parking area with the ith priority and the occupied area of the obstacles in the parking area with the ith priority; if the remaining area of the parking area of the ith priority is smaller than the vehicle floor area of the current automatic driving vehicle, determining the moving distance of the obstacle within the preset time according to the moving speed of the obstacle; determining the vacant area after the preset time according to the moving distance and the residual area of the parking area with the ith priority; and if the vacant area is determined to be larger than or equal to the vehicle floor area of the current automatic driving vehicle, determining that the current automatic driving vehicle can stop in the stopping area with the ith priority.

In this embodiment, the obstacle information includes a floor area of the obstacle and a moving speed of the obstacle.

After determining the remaining area of the parking area, if it is determined that the remaining area of the parking area is smaller than the vehicle floor area of the current autonomous vehicle, the electronic device further considers the moving speed of the obstacle in this embodiment. In this embodiment, the electronic device may determine the moving distance of the obstacle within the preset time based on the moving speed of the obstacle. And after the moving distance of the obstacle is determined, the electronic device may further determine a free area in the parking area within the parking area after a preset time based on the moving distance of the obstacle and the remaining area of the parking area. Then, if the electronic device determines that the free area in the parking area is greater than or equal to the floor area of the current autonomous vehicle, it may be determined that the current autonomous vehicle may park in the parking area. And if the vacant area in the parking area is determined to be smaller than or equal to the floor area of the current automatic driving vehicle, continuously judging the parking area with the priority level lower by one level.

In one example, if all of the parking areas are determined to be non-parking areas, the electronic device may notify a manager or driver of the autonomous vehicle to manually control the current autonomous vehicle to park.

For example, if there is an obstacle that is driving away from the parking area in the parking area, after the moving speed of the obstacle is determined, the current moving speed and the preset time value may be directly multiplied to obtain the moving distance in the preset time. And then, determining an idle area which the barrier can idle after the preset time according to the moving distance and the current occupied area of the barrier in the parking area, wherein the idle area is used for representing the difference value of the occupied area of the barrier in the parking area compared with the occupied area of the barrier in the parking area after the preset time. And then summing the free area and the residual area to obtain the free area of the staying area after the preset time.

In one possible case, when determining the movement speed, it may also be determined whether the obstacle is currently moving into the parking area or is driving out of the parking area. If the obstacle is driving into the parking area and the remaining area in the current parking area is smaller than the vehicle floor area of the autonomous vehicle, the electronic device can directly determine that the parking area cannot be parked. If the obstacle is driving away from the parking area, the electronic device may determine the moving distance within the preset time based on the moving speed. That is, it may be determined whether it is necessary to determine the moving distance of the obstacle and the vacant area of the parking area according to the moving direction of the obstacle.

In this embodiment, when determining whether the parking area can park, when determining that the remaining area in the parking area is smaller than the vehicle floor area of the current autonomous vehicle, the moving speed of the obstacle in the parking area is further considered, the moving distance of the obstacle within the preset time is determined based on the moving speed of the obstacle, and then the free area in the parking area after the preset time is determined based on the moving distance, the remaining area in the parking area, and the vehicle floor area of the current autonomous vehicle. It is further determined whether a stop is available based on the free area and the vehicle footprint of the current autonomous vehicle. Furthermore, based on the mode, the movement of the barrier in the stay area is considered, so that the optimal stay area is more accurately selected, and the user experience is improved.

When acquiring the moving speed of the obstacle, the following embodiments may be adopted:

the first embodiment: acquiring the barrier type of the barriers in the parking area with the ith priority; and determining the moving speed of the obstacle in the data information according to the corresponding relation between the preset obstacle type and the moving speed of the obstacle.

In the present embodiment, for example, when the obstacle category may indicate vehicles of different models, the correspondence between the vehicles of different models and the moving speed may be set. For example, the moving speed between vehicles of different models can satisfy the following conditions: the moving speed of the double-layer bus is lower than that of a single-layer bus, and the moving speed of the multiple buses is lower than that of a single bus. For another example, the obstacle category may also be indicated as a pedestrian, which may also be specifically classified as an elderly person, a young person, a child, and the like.

In one example, when determining the obstacle category, the obstacle category may be further determined based on the acquired image information of the obstacle.

In this embodiment, since the moving speeds of the obstacles of different categories are different, the moving speed can be determined directly based on the correspondence between the category of the obstacle and the moving speed, and the efficiency of obtaining the optimal parking area is improved.

The second embodiment: acquiring road condition information corresponding to a current station, and acquiring the barrier type of a barrier in a parking area with the ith priority; and determining the barrier moving speed in the data information according to the preset corresponding relation among the road condition information, the barrier type and the barrier moving speed.

In the embodiment, the corresponding relation among the road condition information of the current station, the obstacle category and the obstacle moving speed can be combined, so that the determined obstacle moving speed is more consistent with the real driving scene, and the obtained optimal parking area is more accurate.

S305, if the current automatic driving vehicle cannot be parked into the parking area with the ith priority according to the data information of the obstacles in the parking area with the ith priority and the vehicle floor area of the current automatic driving vehicle, determining that i is accumulated to be 1.

For example, when the parking area of the i-th priority is judged, if it is determined that the vehicle cannot park based on the data information of the obstacle in the parking area and the vehicle floor area of the current autonomous vehicle, the vehicle continues to go to the parking area of the i + 1-th priority for judgment.

In this embodiment, it is determined that the current autonomous vehicle can be parked in the currently determined parking area based on the order of the priorities of the parking areas from high to low, and if the current autonomous vehicle can be parked, the parking area is determined to be the optimal parking area, and determination of the remaining parking areas is not required, thereby improving the determination efficiency. For each parking area, whether the current automatic driving vehicle can park in the current parking area or not can be judged based on the data information in the parking area and the floor area of the current automatic driving vehicle, the judgment mode is simple, the realization is easy, and the judgment time is short.

And S306, acquiring the road condition information corresponding to the current station.

For example, after the electronic device obtains the optimal parking area, in order to determine the parking path of the current autonomous vehicle, first, the road condition information corresponding to the current station needs to be obtained. The traffic information is used to represent relevant data of road traffic at the current station, such as vehicle information, traffic jam information, traffic light information, and the like in each lane.

And S307, generating a parking path according to the road condition information corresponding to the current station by taking the current position of the current automatic driving vehicle as a starting point and the optimal parking area as a terminal point.

For example, when a parking path is generated, the current position of the current autonomous vehicle is required to be used as a starting point, the optimal parking area is used as a terminal point, and the parking path of the current autonomous vehicle is automatically planned in combination with the acquired road condition information of the current station where the current autonomous vehicle is required to park, so that the current autonomous vehicle can park to the determined optimal parking area.

In this embodiment, the parking path of the autonomous vehicle is determined by acquiring the road condition information of the current station in combination with the road condition information, so as to improve the effectiveness of parking control on the current autonomous vehicle.

And S308, controlling the current automatic driving vehicle to park to the optimal parking area according to the parking path.

For example, this step may refer to step S104 described above, and is not described again.

In this embodiment, it is determined that the current autonomous vehicle can be parked in the currently determined parking area based on the order of the priorities of the parking areas from high to low, and if the current autonomous vehicle can be parked, the parking area is determined to be the optimal parking area, and determination of the remaining parking areas is not required, thereby improving the determination efficiency. In addition, if the remaining area of the parking area is determined to be smaller than the vehicle floor area of the current automatic driving vehicle, the moving distance of the obstacle within the preset time is also determined according to the moving speed of the obstacle; determining the vacant area after the preset time according to the moving distance and the residual area of the parking area with the ith priority; if the vacant area is larger than or equal to the vehicle floor area of the current automatic driving vehicle, the current automatic driving vehicle is determined to be capable of parking in the parking area with the ith priority, the accuracy of determining the optimal parking area is improved through the method, and the riding experience of a user is improved.

For example, fig. 4 is a diagram of another application scenario of the station stop control method based on an autonomous vehicle according to the present disclosure. As shown in fig. 4, the diagram includes: a first lane line 401 (shown by a dotted line), a second lane line 402, a third lane line 403, a first parking area 404, a second parking area 405, a third parking area 406, a station 407, and a station bay boundary 408 (shown by a solid line), and a first lane 409 (shown as an area between the first lane line 401 and the second lane line 402). When determining the set of docking areas corresponding to the station 407, first, the largest rectangular area including the station 407 can be found in the first lane line 401 and the bay boundary 408 as the first docking area 404, and the priority of the first docking area 404 is the 1 st priority. In determining the remaining parking areas, the determination may be made within the first lane 401 near the first parking area 404. For example, in the figure, the upper boundary 4041 and the lower boundary 4042 of the first docking area 404 are extended into the first lane 409, so as to obtain the second docking area 405, and the priority of the second docking area 405 is the 2 nd priority; then, a third parking area 406 is also provided in the first lane 409, and the third parking area 406 is provided in the opposite direction of the second parking area 405 in the vehicle traveling direction, and the priority of this third parking area 406 is 3 rd priority. When the autonomous vehicle needs to stop at the station 407 shown in fig. 4, it is determined preferentially whether the first stop area 404 can stop. If not, then a determination is continued as to whether the second docking area 405 is docked. By analogy, if it is determined that the third parking area 406 cannot be parked, the autonomous vehicle is controlled to park by human.

For example, fig. 5 is a diagram of another application scenario of the station stop control method based on the autonomous vehicle according to the present disclosure. As shown in fig. 5, the diagram includes: a road edge line 501, a first lane line 502, a second lane line 503, a first parking area 504, a second parking area 505, a third parking area 506, a stop 507, a first lane 508 (the area between the first lane line 502 and the road edge line 501 in the figure), and a second lane 509 (the area between the first lane line 502 and the second lane line 503 in the figure). The first parking area 504 is obtained by extending the same distance to the station 507 in the vehicle driving direction and the opposite direction to the vehicle driving direction respectively by using the center of the station 507, and the priority of the first parking area 504 is the 1 st priority. The second parking area 505 is formed by extending the upper boundary 5041 and the lower boundary 5042 of the first parking area to the second lane line 503, respectively, and the priority of the second parking area 505 is the 2 nd priority. The third parking area 506 is obtained by moving the lower boundary 5042 of the first parking area 505 a distance in the opposite direction of the vehicle traveling direction in the first lane 508, and the priority of the third parking area 506 is 3 rd priority. In one possible scenario, the distance between the upper boundary 5041 and the lower boundary 5042 of the first docking area 505 is 30 meters. The third parking area 507 has a length of 20 meters in the vehicle traveling direction. In this example, it can be seen that, when determining the parking areas, the center points of the parking areas in the set of parking areas are located on a line in a direction opposite to the travel direction of the travel path.

Fig. 6 is a schematic diagram according to a third embodiment of the present disclosure, and as shown in fig. 6, the station stop control apparatus based on an autonomous vehicle according to the embodiment of the present disclosure includes:

the first obtaining unit 601 is configured to obtain obstacle information corresponding to a current station on a driving path, where the obstacle information is information of an obstacle within a preset geographic range corresponding to the current station.

A first determining unit 602, configured to determine an optimal parking area according to the obstacle information corresponding to the current station and a preset parking area set; the parking area set comprises a plurality of adjacent parking areas, and the parking areas are determined based on vehicle information of the current automatic driving vehicle and lane line information corresponding to the current station.

A second determining unit 603, configured to determine a parking path according to the optimal parking area and the current position of the current autonomous vehicle.

And a third determining unit 604, configured to control the current autonomous vehicle to park to the optimal parking area according to the parking path.

For example, the apparatus of this embodiment may execute the technical solution in the method, and the specific implementation process and the technical principle are the same, which are not described herein again.

Fig. 7 is a schematic diagram according to a third embodiment of the present disclosure, and as shown in fig. 7, the station stop control apparatus based on an autonomous vehicle according to the embodiment of the present disclosure includes:

a first obtaining unit 701, configured to obtain obstacle information corresponding to a current station on a driving path, where the obstacle information is information of an obstacle within a preset geographic range corresponding to the current station.

A first determining unit 702, configured to determine an optimal parking area according to the obstacle information corresponding to the current station and a preset parking area set; the parking area set comprises a plurality of adjacent parking areas, and the parking areas are determined based on vehicle information of the current automatic driving vehicle and lane line information corresponding to the current station.

The second determining unit 703 is configured to determine a parking path according to the optimal parking area and the current position of the current autonomous vehicle.

And a third determining unit 704 for controlling the current autonomous vehicle to park into the optimal parking area according to the parking path.

In one example, the center point of the parking areas in the set of parking areas is located on a line along a preset direction, which is a direction opposite to the driving direction along the driving path.

In one example, the docked areas in the set of docked areas have priorities; the obstacle information includes data information of obstacles within a parking area of an ith priority in the set of parking areas; the first determination unit 702 includes:

an executing module 7021, configured to repeat the following modules until an optimal parking area is determined, where i is a positive integer greater than or equal to 1, and an initial value of i is 1.

The first determining module 7022 is configured to determine that the current autonomous driving vehicle can park in the parking area of the ith priority according to the data information of the obstacles in the parking area of the ith priority and the vehicle floor area of the current autonomous driving vehicle.

A second determining module 7023, configured to determine the parking area with the ith priority as the optimal parking area.

A third determining module 7024, configured to determine that the current autonomous vehicle may not be parked into the parking area of the ith priority, if according to the data information of the obstacles in the parking area of the ith priority and the vehicle floor area of the current autonomous vehicle.

A fourth determining module 7025, configured to determine i-add 1.

In one example, the data information includes an obstacle footprint; a first determining module 7022 comprising:

the first determining submodule 70221 is configured to determine the remaining area of the parking area of the ith priority based on the area of the parking area of the ith priority and the occupied area of the obstacle in the parking area of the ith priority.

The second determining sub-module 70222 is configured to determine that the current autonomous vehicle can park in the parking area of the ith priority if it is determined that the remaining area of the parking area of the ith priority is greater than or equal to the vehicle floor area of the current autonomous vehicle.

In one example, the data information includes an obstacle footprint and an obstacle movement speed; a first determining module 7022 comprising:

the third determining submodule 70223 is configured to determine the remaining area of the parking area of the ith priority according to the area of the parking area of the ith priority and the occupied area of the obstacle in the parking area of the ith priority.

The fourth determining submodule 70224 is configured to determine, according to the moving speed of the obstacle, the moving distance of the obstacle within the preset time if it is determined that the remaining area of the parking area of the i-th priority is smaller than the vehicle floor area of the current autonomous vehicle.

A fifth determining submodule 70225 is configured to determine an area left after a preset time, based on the moving distance and the remaining area of the parking area of the ith priority.

A sixth determining submodule 70226, configured to determine that the current autonomous vehicle can park in the parking area of the ith priority level if it is determined that the free area is greater than or equal to the vehicle footprint of the current autonomous vehicle.

In an example, the apparatus provided in this embodiment further includes:

a second obtaining unit 705, configured to obtain the obstacle category of the obstacle in the parking area of the ith priority.

A fourth determining unit 706, configured to determine the moving speed of the obstacle in the data information according to a corresponding relationship between preset obstacle categories and moving speeds of the obstacle.

In an example, the apparatus provided in this embodiment further includes:

a third obtaining unit 707, configured to obtain road condition information corresponding to the current station.

A fourth obtaining unit 708, configured to obtain the obstacle category of the obstacle within the parking area of the ith priority.

A fifth determining unit 709, configured to determine a moving speed of the obstacle in the data information according to a corresponding relationship between the preset road condition information, the obstacle category, and the moving speed of the obstacle.

In an example, the apparatus provided in this embodiment further includes:

a fifth obtaining unit 710, configured to obtain lane line information corresponding to each station on the travel path, where the lane line information includes a lane line position of a lane line adjacent to the station.

A sixth obtaining unit 711, configured to obtain a station category corresponding to each station on the travel path.

A sixth determining unit 712, configured to determine a parking area set corresponding to the station according to the lane line information, the station category, and a vehicle floor area in the vehicle information of the current autonomous vehicle; and the parking areas in the parking area set are larger than or equal to the vehicle floor area of the current automatic driving vehicle.

In an example, the sixth determining unit 712 includes:

a fifth determining module 7121, configured to determine a parking area including a station according to the lane line information, the station category, and a vehicle floor area in the vehicle information of the current autonomous vehicle.

A sixth determining module 7122, configured to determine, according to the lane line information and a vehicle floor area in the vehicle information of the current autonomous vehicle, an area adjacent to a parking area including the station as another parking area, so as to obtain a parking area set.

In an example, the apparatus provided in this embodiment further includes:

a receiving unit 713, configured to receive the docking area set sent by the remote device.

The parking area set is determined according to lane line information corresponding to each station on the driving path, station types corresponding to each station on the driving path and vehicle floor areas in the vehicle information of the current automatic driving vehicle.

In an example, the second determining unit 703 includes:

the first obtaining module 7031 is configured to obtain road condition information corresponding to the current station.

The generating module 7032 is configured to generate a stopping path according to the road condition information corresponding to the current station, with the current position of the current autonomous driving vehicle as a starting point and the optimal stopping area as an ending point.

In one example, the first obtaining unit 701 includes:

a second obtaining module 7011, configured to obtain, through a millimeter wave radar on the current autonomous vehicle, obstacle information corresponding to a current station on the driving path.

Or, the receiving module 7012 is configured to receive the obstacle information, which is sent by the acquisition device located on the current station and corresponds to the current station on the driving path.

For example, the apparatus of this embodiment may execute the technical solution in the method, and the specific implementation process and technical principle are the same, which are not described herein again.

Fig. 8 is a schematic diagram according to a fifth embodiment of the present disclosure, and as shown in fig. 8, an electronic device 800 in the present disclosure may include: a processor 801 and a memory 802.

A memory 802 for storing programs; the Memory 802 may include a volatile Memory (RAM), such as a Static Random Access Memory (SRAM), a Double Data Rate Synchronous Dynamic Random Access Memory (DDR SDRAM), and the like; the memory may also include a non-volatile memory, such as a flash memory. The memory 802 is used to store computer programs (e.g., applications, functional modules, etc. that implement the above-described methods), computer instructions, etc., which may be stored in partitions in one or more of the memories 802. And the above-described computer programs, computer instructions, data, and the like can be called by the processor 801.

The computer programs, computer instructions, etc. described above may be stored in one or more memories 802 in partitions. And the above-described computer program, computer data, or the like can be called by the processor 801.

A processor 801 for executing the computer program stored in the memory 802 to implement the steps of the method according to the above embodiments.

Reference may be made in particular to the description relating to the preceding method embodiment.

The processor 801 and the memory 802 may be separate structures or may be integrated structures integrated together. When the processor 801 and the memory 802 are separate structures, the memory 802 and the processor 801 may be coupled by a bus 803.

The electronic device of this embodiment may execute the technical solution in the method, and the specific implementation process and the technical principle are the same, which are not described herein again.

The present disclosure also provides an electronic device, a readable storage medium, and a computer program product according to embodiments of the present disclosure.

According to an embodiment of the present disclosure, the present disclosure also provides a computer program product comprising: a computer program, stored in a readable storage medium, from which at least one processor of the electronic device can read the computer program, the at least one processor executing the computer program causing the electronic device to perform the solution provided by any of the embodiments described above.

FIG. 9 illustrates a schematic block diagram of an example electronic device 900 that can be used to implement embodiments of the present disclosure. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be examples only, and are not meant to limit implementations of the disclosure described and/or claimed herein.

As shown in fig. 9, the apparatus 900 includes a computing unit 901 which can perform various appropriate actions and processes in accordance with a computer program stored in a Read Only Memory (ROM)902 or a computer program loaded from a storage unit 908 into a Random Access Memory (RAM) 903. In the RAM 903, various programs and data required for the operation of the device 900 can also be stored. The calculation unit 901, ROM 902, and RAM 903 are connected to each other via a bus 904. An input/output (I/O) interface 905 is also connected to bus 904.

A number of components in the device 900 are connected to the I/O interface 905, including: an input unit 906 such as a keyboard, a mouse, and the like; an output unit 907 such as various types of displays, speakers, and the like; a storage unit 908 such as a magnetic disk, optical disk, or the like; and a communication unit 909 such as a network card, a modem, a wireless communication transceiver, and the like. The communication unit 909 allows the device 900 to exchange information/data with other devices through a computer network such as the internet and/or various telecommunication networks.

The computing unit 901 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of the computing unit 901 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various dedicated Artificial Intelligence (AI) computing chips, various computing units running machine learning model algorithms, a Digital Signal Processor (DSP), and any suitable processor, controller, microcontroller, and so forth. The calculation unit 901 performs the respective methods and processes described above, such as the station stop control method based on the autonomous vehicle. For example, in some embodiments, the autonomous vehicle based station stop control method may be implemented as a computer software program tangibly embodied in a machine-readable medium, such as storage unit 908. In some embodiments, part or all of the computer program may be loaded and/or installed onto device 900 via ROM 902 and/or communications unit 909. When the computer program is loaded into the RAM 903 and executed by the computing unit 901, one or more steps of the above-described method based on the station stop control method of the autonomous vehicle may be executed. Alternatively, in other embodiments, the computing unit 901 may be configured in any other suitable way (e.g., by means of firmware) to perform the method based station parking control method of the autonomous vehicle.

Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuitry, Field Programmable Gate Arrays (FPGAs), Application Specific Integrated Circuits (ASICs), Application Specific Standard Products (ASSPs), system on a chip (SOCs), Complex Programmable Logic Devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, receiving data and instructions from, and transmitting data and instructions to, a storage system, at least one input device, and at least one output device.

Program code for implementing the methods of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the program codes, when executed by the processor or controller, cause the functions/operations specified in the flowchart and/or block diagram to be performed. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package partly on the machine and partly on a remote machine or entirely on the remote machine or server.

In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which a user can provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic, speech, or tactile input.

The systems and techniques described here can be implemented in a computing system that includes a back-end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), Wide Area Networks (WANs), and the Internet.

The computer system may include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The Server can be a cloud Server, also called a cloud computing Server or a cloud host, and is a host product in a cloud computing service system, so as to solve the defects of high management difficulty and weak service expansibility in the traditional physical host and VPS service ("Virtual Private Server", or simply "VPS"). The server may also be a server of a distributed system, or a server incorporating a blockchain.

The present disclosure provides an autonomous vehicle comprising: an autonomous vehicle based station stop control apparatus as in any embodiment of the present disclosure.

It should be understood that various forms of the flows shown above, reordering, adding or deleting steps, may be used. For example, the steps described in the present disclosure may be executed in parallel, sequentially, or in different orders, as long as the desired results of the technical solutions disclosed in the present disclosure can be achieved, and the present disclosure is not limited herein.

The above detailed description should not be construed as limiting the scope of the disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may be made in accordance with design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present disclosure should be included in the scope of protection of the present disclosure.

Claims

1. A station stop control method based on an automatic driving vehicle comprises the following steps:

acquiring obstacle information corresponding to a current station on a driving path, wherein the obstacle information is information of obstacles in a preset geographical range corresponding to the current station;

determining an optimal parking area according to the barrier information corresponding to the current station and a preset parking area set; the parking area set comprises a plurality of adjacent parking areas, and the parking areas are determined based on the vehicle information of the current automatic driving vehicle and the lane line information corresponding to the current station;

2. The method of claim 1, wherein a center point of a docking area of the set of docking areas is located on a line along a preset direction, the preset direction being a direction opposite to a direction of travel along the travel path.

3. The method of claim 1 or 2, wherein a docking area in the set of docking areas has a priority; the obstacle information comprises data information of obstacles in a parking area of an ith priority in the set of parking areas; determining an optimal parking area according to the obstacle information corresponding to the current station and a preset parking area set, wherein the determining comprises the following steps:

repeating the following steps until an optimal parking area is determined, wherein i is a positive integer greater than or equal to 1, and the initial value of i is 1:

if the current automatic driving vehicle can be determined to be parked in the parking area with the ith priority according to the data information of the obstacles in the parking area with the ith priority and the vehicle floor area of the current automatic driving vehicle, determining the parking area with the ith priority as the optimal parking area;

and if the current automatic driving vehicle cannot be parked into the parking area with the ith priority according to the data information of the obstacles in the parking area with the ith priority and the vehicle floor area of the current automatic driving vehicle, determining that i is accumulated to be 1.

4. The method of claim 3, wherein the data information comprises an obstacle footprint; determining that the current autonomous vehicle can be parked into the parking area with the ith priority according to the data information of the obstacles in the parking area with the ith priority and the vehicle floor area of the current autonomous vehicle, wherein the determining comprises the following steps:

determining the remaining area of the parking area with the ith priority according to the area of the parking area with the ith priority and the occupied area of the obstacles in the parking area with the ith priority;

and if the remaining area of the parking area of the ith priority is determined to be larger than or equal to the vehicle floor area of the current automatic driving vehicle, determining that the current automatic driving vehicle can park in the parking area of the ith priority.

5. The method of claim 3, wherein the data information includes an obstacle footprint and an obstacle movement speed; determining that the current autonomous vehicle can be parked into the parking area with the ith priority according to the data information of the obstacles in the parking area with the ith priority and the vehicle floor area of the current autonomous vehicle, wherein the determining comprises the following steps:

if the remaining area of the parking area of the ith priority is smaller than the vehicle floor area of the current automatic driving vehicle, determining the moving distance of the obstacle within the preset time according to the moving speed of the obstacle;

determining the vacant area after the preset time according to the moving distance and the residual area of the parking area with the ith priority; and if the vacant area is determined to be larger than or equal to the vehicle floor area of the current automatic driving vehicle, determining that the current automatic driving vehicle can be parked into the parking area of the ith priority.

6. The method of claim 5, further comprising:

obtaining the obstacle category of the obstacles in the parking area with the ith priority;

and determining the moving speed of the obstacle in the data information according to the corresponding relation between the preset obstacle type and the moving speed of the obstacle.

7. The method of claim 5, further comprising:

acquiring road condition information corresponding to the current station, and acquiring the barrier type of the barrier in the parking area with the ith priority;

and determining the moving speed of the obstacle in the data information according to the corresponding relation among the preset road condition information, the obstacle category and the moving speed of the obstacle.

8. The method of any of claims 1-7, further comprising:

acquiring lane line information corresponding to each station on the driving path, wherein the lane line information comprises lane line positions of lane lines adjacent to the stations; acquiring the site type corresponding to each site on the driving path;

determining a parking area set corresponding to the station according to the lane line information, the station type and the vehicle floor area in the vehicle information of the current automatic driving vehicle; wherein a parking area in the set of parking areas is greater than or equal to a vehicle footprint of the current autonomous vehicle.

9. The method of claim 8, wherein determining the set of parking areas corresponding to the station based on the lane line information, the station category, and a vehicle footprint in the vehicle information for the current autonomous vehicle comprises:

determining a parking area comprising the station according to the lane line information, the station category and the vehicle floor area in the vehicle information of the current automatic driving vehicle;

and determining an area adjacent to a parking area including the station as other parking areas according to the lane line information and the vehicle floor area in the vehicle information of the current automatic driving vehicle, so as to obtain the parking area set.

10. The method of any of claims 1-7, further comprising:

receiving the docking area set sent by the remote equipment;

the parking area set is determined according to lane line information corresponding to each station on the driving path, station types corresponding to each station on the driving path, and vehicle floor areas in the vehicle information of the current automatic driving vehicle.

11. The method of any of claims 1-10, wherein determining a parking path based on the optimal parking area and a current location of the current autonomous vehicle comprises:

acquiring road condition information corresponding to the current station;

and generating the parking path according to the road condition information corresponding to the current station by taking the current position of the current automatic driving vehicle as a starting point and the optimal parking area as a terminal point.

12. The method of any one of claims 1-10, wherein obtaining obstacle information corresponding to a current station on the travel path comprises:

acquiring obstacle information corresponding to a current station on a driving path through a millimeter wave radar on the current automatic driving vehicle;

or receiving the barrier information which is sent by the acquisition equipment positioned on the current station and corresponds to the current station on the driving path.

13. An automatic-driving-vehicle-based station stop control device comprising:

the system comprises a first acquisition unit, a second acquisition unit and a control unit, wherein the first acquisition unit is used for acquiring obstacle information corresponding to a current station on a driving path, and the obstacle information is information of obstacles in a preset geographical range corresponding to the current station;

the first determining unit is used for determining an optimal parking area according to the barrier information corresponding to the current station and a preset parking area set; the parking area set comprises a plurality of adjacent parking areas, and the parking areas are determined based on the vehicle information of the current automatic driving vehicle and the lane line information corresponding to the current station;

the second determining unit is used for determining a parking path according to the optimal parking area and the current position of the current automatic driving vehicle;

14. The apparatus of claim 13, wherein a center point of a docking area of the set of docking areas is located on a line along a preset direction, the preset direction being a direction opposite to a travel direction along the travel path.

15. The apparatus of claim 13 or 14, wherein a docking area of the set of docking areas has a priority; the obstacle information comprises data information of obstacles in a parking area of an ith priority in the set of parking areas; the first determination unit includes:

the execution module is used for repeating the following modules until an optimal parking area is determined, wherein i is a positive integer greater than or equal to 1, and the initial value of i is 1:

the first determining module is used for determining that the current automatic driving vehicle can be parked into the parking area with the ith priority according to the data information of the obstacles in the parking area with the ith priority and the vehicle floor area of the current automatic driving vehicle;

the second determining module is used for determining the parking area with the ith priority as the optimal parking area;

a third determining module, configured to determine that the current autonomous driving vehicle cannot be parked in the parking area of the ith priority according to the data information of the obstacles in the parking area of the ith priority and the vehicle floor area of the current autonomous driving vehicle;

a fourth determining module to determine i-add 1.

16. The apparatus of claim 15, wherein the data information comprises an obstacle footprint; the first determining module includes:

the first determining submodule is used for determining the remaining area of the parking area with the ith priority according to the area of the parking area with the ith priority and the occupied area of the obstacles in the parking area with the ith priority;

and the second determining submodule is used for determining that the current automatic driving vehicle can be parked into the parking area with the ith priority if the remaining area of the parking area with the ith priority is determined to be larger than or equal to the vehicle floor area of the current automatic driving vehicle.

17. The apparatus of claim 15, wherein the data information comprises an obstacle footprint and an obstacle movement speed; the first determining module includes:

a third determining submodule, configured to determine a remaining area of the parking area of the ith priority according to an area of the parking area of the ith priority and an obstacle floor area of an obstacle in the parking area of the ith priority;

a fourth determining submodule, configured to determine, according to the movement speed of the obstacle, a movement distance of the obstacle within a preset time if it is determined that the remaining area of the parking area of the i-th priority is smaller than a vehicle floor area of the current autonomous vehicle;

a fifth determining submodule, configured to determine, according to the moving distance and the remaining area of the parking area of the ith priority, an empty area after the preset time;

and the sixth determining submodule is used for determining that the current automatic driving vehicle can stop in the stopping area with the ith priority if the vacant area is determined to be larger than or equal to the vehicle floor area of the current automatic driving vehicle.

18. The apparatus of claim 17, further comprising:

a second obtaining unit, configured to obtain an obstacle category of an obstacle in the parking area of the ith priority;

and the fourth determining unit is used for determining the barrier moving speed in the data information according to the corresponding relation between the preset barrier type and the barrier moving speed.

19. The apparatus of claim 17, further comprising:

a third obtaining unit, configured to obtain road condition information corresponding to the current station;

a fourth obtaining unit, configured to obtain an obstacle category of an obstacle in the parking area of the ith priority;

and the fifth determining unit is used for determining the barrier moving speed in the data information according to the preset corresponding relation among the road condition information, the barrier type and the barrier moving speed.

20. The apparatus of any of claims 13-19, further comprising:

a fifth obtaining unit, configured to obtain lane line information corresponding to each station on the travel path, where the lane line information includes a lane line position of a lane line adjacent to the station;

a sixth obtaining unit, configured to obtain a site category corresponding to each site on the travel path;

a sixth determining unit, configured to determine a parking area set corresponding to the station according to the lane line information, the station category, and a vehicle floor area in the vehicle information of the current autonomous vehicle; wherein a parking area in the set of parking areas is greater than or equal to a vehicle footprint of the current autonomous vehicle.

21. The apparatus of claim 20, wherein the sixth determining unit comprises:

a fifth determining module, configured to determine a parking area including the station according to the lane line information, the station category, and a vehicle floor area in the vehicle information of the current autonomous vehicle;

and the sixth determining module is used for determining an area adjacent to the parking area including the station as other parking areas according to the lane line information and the vehicle floor area in the vehicle information of the current automatic driving vehicle so as to obtain the parking area set.

22. The apparatus of any of claims 13-19, further comprising:

a receiving unit, configured to receive the docking area set sent by the remote device;

23. The apparatus according to any of claims 13-22, wherein the second determining unit comprises:

the first acquisition module is used for acquiring the road condition information corresponding to the current station;

and the generating module is used for generating the parking path according to the road condition information corresponding to the current station by taking the current position of the current automatic driving vehicle as a starting point and the optimal parking area as a terminal point.

24. The apparatus according to any one of claims 13-23, wherein the first obtaining unit comprises:

the second acquisition module is used for acquiring the obstacle information corresponding to the current station on the running path through the millimeter wave radar on the current automatic driving vehicle;

or the receiving module is used for receiving the barrier information which is sent by the acquisition equipment positioned on the current station and corresponds to the current station on the driving path.

25. An electronic device, comprising:

at least one processor; and

a memory communicatively coupled to the at least one processor; wherein, the first and the second end of the pipe are connected with each other,

the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-12.

26. A non-transitory computer readable storage medium having stored thereon computer instructions for causing the computer to perform the method of any one of claims 1-12.

27. A computer program product comprising a computer program which, when executed by a processor, carries out the steps of the method of any one of claims 1 to 12.

28. An autonomous vehicle comprising: the apparatus of any one of claims 13 to 24.