Vehicle control method and device, electronic device, and computer readable medium

Abstract

The present disclosure provides a vehicle control method and device, which relate to the fields of autonomous driving and cloud computing technology. The specific implementation scheme is: real-time detection of whether the vehicle meets the planning obstacle conditions, which are conditions under which the vehicle's autonomous driving system cannot effectively plan a path; in response to detecting that the vehicle meets the planning obstacle conditions, based on the vehicle's location, determine the area where the vehicle is located; based on the area, detect whether there is pre-established path planning information, which is vehicle information in different areas collected after manual vehicle operation at historical moments; in response to detecting that there is pre-established path planning information, control the vehicle to operate automatically based on the path planning information. This implementation improves the flexibility of autonomous driving.

Description

Technical Field

[0001] The present disclosure relates to the field of artificial intelligence technology, specifically to the field of autonomous driving and cloud computing technology, and in particular to a vehicle control method and device, electronic equipment, computer-readable medium, and computer program product. Background Art

[0002] When a mine truck is operating in a mining scenario, there may be narrow areas in the loading and unloading area, and the shapes and sizes of the narrow areas cannot be fully enumerated. The mine truck's automatic driving needs to be able to adapt to such scenarios and will not be unable to operate for a long time due to the appearance of narrow areas. Summary of the invention

[0003] A vehicle control method and device, an electronic device, a computer-readable medium, and a computer program product are provided.

[0004] According to a first aspect, a vehicle control method is provided, the method comprising: detecting in real time whether a vehicle satisfies a planning obstacle condition, the planning obstacle condition being a condition under which the vehicle's automatic driving system cannot effectively perform path planning; in response to detecting that the vehicle satisfies the planning obstacle condition, determining a region where the vehicle is located based on the vehicle's location; based on the region, detecting whether there is pre-established path planning information, the path planning information being vehicle information in different regions collected after manual vehicle operation at a historical moment; in response to detecting that there is pre-established path planning information, controlling the vehicle to operate automatically based on the path planning information.

[0005] According to a second aspect, a vehicle control device is provided, which includes: a condition detection unit, configured to detect in real time whether the vehicle satisfies a planning obstacle condition, the planning obstacle condition being a condition under which the vehicle's automatic driving system cannot effectively perform path planning; a determination unit, configured to determine a region where the vehicle is located based on the vehicle's location in response to detecting that the vehicle satisfies the planning obstacle condition; an information detection unit, configured to detect whether there is pre-established path planning information based on the region where the vehicle is located, the path planning information being vehicle information in different regions collected after manual vehicle operation at a historical moment; and a control unit, configured to control the vehicle to automatically operate based on the path planning information in response to detecting that there is pre-established path planning information.

[0006] According to a third aspect, an electronic device is provided, comprising: at least one processor; and a memory communicatively connected to the at least one processor, wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the method described in any implementation manner of the first aspect.

[0007] According to a fourth aspect, a non-transitory computer-readable storage medium storing computer instructions is provided, where the computer instructions are used to cause a computer to execute the method described in any implementation of the first aspect.

[0008] According to a fifth aspect, a computer program product is provided, comprising a computer program, which implements the method described in any implementation manner of the first aspect when executed by a processor.

[0009] The vehicle control method and device provided by the embodiments of the present disclosure first detect in real time whether the vehicle meets the planning obstacle condition, and the planning obstacle condition is a condition under which the vehicle's automatic driving system cannot effectively perform path planning; secondly, in response to detecting that the vehicle meets the planning obstacle condition, the vehicle's location area is determined based on the vehicle's location; thirdly, based on the location area, whether there is pre-established path planning information is detected; finally, in response to detecting that there is pre-established path planning information, the vehicle is controlled to operate automatically based on the path planning information. Thus, when the vehicle's automatic driving system cannot effectively perform path planning, the manual driving experience is determined through the path planning information corresponding to the vehicle's location area, and the vehicle is guided to perform automatic operation based on the manual driving experience, which provides guidance and reference for the vehicle's automatic driving system and improves the flexibility of the vehicle's automatic operation.

[0010] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present disclosure, nor is it intended to limit the scope of the present disclosure. Other features of the present disclosure will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] The accompanying drawings are used to better understand the present solution and do not constitute a limitation of the present disclosure.

[0012] Figure 1 is a flow chart of an embodiment of a vehicle control method according to the present disclosure;

[0013] Figure 2 is a flow chart of another embodiment of a vehicle control method according to the present disclosure;

[0014] Figure 3 is a flow chart of another embodiment of the vehicle control method according to the present disclosure;

[0015] Figure 4 is a structural schematic diagram of an embodiment of a vehicle control device according to the present disclosure;

[0016] Figure 5 It is a block diagram of an electronic device used to implement the vehicle control method of the embodiment of the present disclosure. DETAILED DESCRIPTION

[0017] The following is a description of exemplary embodiments of the present disclosure in conjunction with the accompanying drawings, including various details of the embodiments of the present disclosure to facilitate understanding, which should be considered as merely exemplary. Therefore, it should be recognized by those of ordinary skill in the art that various changes and modifications may be made to the embodiments described herein without departing from the scope and spirit of the present disclosure. Similarly, for the sake of clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.

[0018] In this embodiment, "first" and "second" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly indicating the number of indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features.

[0019] When an autonomous vehicle (such as an autonomous mining vehicle or an autonomous road sweeper) encounters a narrow area or is unable to plan autonomous driving, the autonomous vehicle reports the problem, which is usually solved by manual driving, or by model or algorithm steering improvements based on the characteristics of the faulty area. However, the above-mentioned manual takeover method requires the corresponding driver, which cannot reduce operating costs and cannot achieve the expected benefits of autonomous driving. In addition, the above-mentioned model or algorithm method has a long R&D and testing cycle and cannot solve the problem, or there may be multiple low-efficiency reverse driving situations. There is great uncertainty in the cycle and effect of solving the problem.

[0020] In view of the above-mentioned defects, the present disclosure provides a vehicle control method. Figure 1 A process 100 according to an embodiment of a vehicle control method of the present disclosure is shown. The vehicle control method comprises the following steps:

[0021] Step 101, real-time detection of whether the vehicle meets the planned obstacle conditions.

[0022] In this embodiment, the planning obstacle condition is a condition under which the vehicle's automatic driving system cannot effectively perform path planning.

[0023] In this embodiment, the vehicle may be an autonomous driving vehicle, which can be used to patrol a fixed area and monitor the scene in the fixed area; the vehicle may also be an operating vehicle with an autonomous driving function, that is, an automatic operating vehicle, such as an automatic mining vehicle, an automatic coal mining vehicle, an automatic sweeper, etc. The autonomous driving system on the vehicle performs path planning for the vehicle's autonomous driving. When the vehicle meets the planning obstacle conditions, the autonomous driving system on the vehicle cannot effectively plan the path, and the autonomous driving operation command output by the autonomous driving system to control the vehicle cannot enable the vehicle to complete the autonomous driving task or the automatic operation task; when the vehicle does not meet the planning obstacle conditions, the autonomous driving system on the vehicle can effectively plan the path and control the vehicle to perform automatic operations.

[0024] Step 102 , in response to detecting that the vehicle meets the planning obstacle condition, determining the area where the vehicle is located based on the location of the vehicle.

[0025] In this embodiment, in order to realize the automatic driving of the vehicle, the automatic driving system on the vehicle is provided with a positioning device, through which the location of the vehicle can be determined, and the location is the real-time location of the vehicle at the current moment.

[0026] In this embodiment, the area where the vehicle is located is an area including the location of the vehicle, and the shape of the area can be a regular shape, for example, the area is a circular area, or a square area. The shape of the area can also be an irregular shape, for example, an area without obstacles in the area. The area where the vehicle is located can be a circular area with the location of the vehicle as the center and a preset length as the radius. The area where the vehicle is located can also be the remaining area obtained by removing the area where the obstacles are located in the circular area.

[0027] Step 103: Based on the area, detect whether there is pre-established path planning information.

[0028] In this embodiment, the path planning information may be planning information obtained by pre-operating the same vehicle to perform tasks in the area, and the path planning information may also be planning information obtained by pre-operating different vehicles to perform tasks in the area.

[0029] Optionally, the path planning information may also be planning information obtained by pre-operating the same vehicle to perform tasks in a similar area to the area where the vehicle is located, or planning information obtained by pre-operating different vehicles to perform tasks in similar areas of the area.

[0030] In this embodiment, the path planning information is information that enables the vehicle to move from satisfying the planned obstacle conditions to not satisfying the planned obstacle conditions. Based on the path planning information, the vehicle's automatic driving system can avoid road conditions encountered in the planned obstacle conditions, thereby enabling the vehicle's automatic driving system to effectively plan paths for the vehicle's automatic driving or automatic operation.

[0031] Step 104 , in response to detecting that there is pre-established path planning information, the vehicle is controlled to operate automatically based on the path planning information.

[0032] In this embodiment, the path planning information is the vehicle information of different areas collected after the manual operation of the vehicle at a historical moment, wherein the vehicle information is information related to the vehicle, for example, the vehicle information is the driving state of the manually driven vehicle and the vehicle operation state, and the vehicle is controlled to automatically operate according to the path planning information, so that the operation of the vehicle can achieve the same effect as the manual operation of the vehicle. It should be noted that the path planning information may include information collected after the manual operation of the vehicle under the same planned obstacle conditions; the path planning information may also include information collected after the manual operation of the vehicle under the similar planned obstacle conditions.

[0033] In this embodiment, automatic operation of the vehicle includes: the vehicle performing tasks in the working area, or the vehicle automatically drives to different locations to perform task operations at each location, such as loading objects in the loading area, and automatically driving to move objects between the loading area and the unloading area.

[0034] The vehicle control method provided by the embodiment of the present disclosure first detects in real time whether the vehicle meets the planning obstacle condition, and the planning obstacle condition is a condition under which the vehicle's automatic driving system cannot effectively perform path planning; secondly, in response to detecting that the vehicle meets the planning obstacle condition, the vehicle's location area is determined based on the vehicle's location; thirdly, based on the location area, whether there is pre-established path planning information is detected; finally, in response to detecting that there is pre-established path planning information, the vehicle is controlled to operate automatically based on the path planning information. Thus, when the vehicle's automatic driving system cannot effectively plan a path, the manual driving experience is determined through the path planning information corresponding to the area where the vehicle is located, and the vehicle is guided to perform automatic driving or automatic operation based on the manual driving experience, which provides guidance and reference for the vehicle's automatic driving system and improves the flexibility of the vehicle's automatic operation.

[0035] In another embodiment of the present disclosure, the path planning information may be experience information obtained through manual driving. The vehicle control method provided in this embodiment integrates manual driving and vehicle automatic driving, provides guidance and reference for automatic driving based on the experience of manual driving, and also takes into account the flexibility of the automatic driving system. Figure 2 A process 200 according to another embodiment of a vehicle control method of the present disclosure is shown. The vehicle control method comprises the following steps:

[0036] Step 201, real-time detection of whether the vehicle meets the planned obstacle conditions.

[0037] In this embodiment, the planning obstacle condition is a condition under which the vehicle's automatic driving system cannot effectively perform path planning.

[0038] Step 202 , in response to detecting that the vehicle meets the planning obstacle condition, the area where the vehicle is located is determined based on the location of the vehicle, and then step 203 is executed.

[0039] Step 203, based on the area, detect whether there is pre-established path planning information; if it is detected that there is pre-established path planning information, execute step 204; if it is detected that there is no pre-established path planning information, execute step 206.

[0040] Step 204 , based on the path planning information, control the vehicle to operate automatically, and then execute step 205 .

[0041] It should be understood that the operations and features in the above steps 201-204 correspond to the operations and features in steps 101-104, respectively. Therefore, the above descriptions of the operations and features in steps 101-104 are also applicable to steps 201-204 and will not be repeated here.

[0042] Step 205, end.

[0043] Step 206: Send operation notification information.

[0044] In this embodiment, the operation notification information is used to notify the manual operation of the vehicle to perform the operation. After receiving the operation notification information, the operator drives the vehicle and performs manual control of the vehicle in the area.

[0045] Step 207, in response to receiving the operation start information, recording the vehicle's driving trajectory, vehicle operating status and operation status.

[0046] In this embodiment, when the operator is driving a vehicle and performing automatic operations of a manually controlled vehicle in the area, if it is necessary to record the status of the manually controlled vehicle, the operator clicks the start button on the vehicle to send out an operation start message. Based on the operation start message, it is determined that the current vehicle is being manually operated and all vehicle operating status and operation status need to be recorded.

[0047] The vehicle operation status includes: driving behavior status and surrounding environment status. The driving behavior status includes the driving trajectory, braking, throttle, vehicle speed at different times, acceleration, gear information, etc. when the vehicle is operating automatically. The surrounding environment status includes: temperature and humidity inside and outside the vehicle, etc. The operating status refers to the vehicle components and the working status of the vehicle components when the vehicle is manually operated automatically at different times.

[0048] Optionally, the vehicle control method further comprises: in response to receiving the operation end information, stopping recording the vehicle's driving track, vehicle operating status and operation status, when it is necessary to stop recording the state of the manually controlled vehicle, the operator clicks the end button on the vehicle to issue the operation end information. After receiving the operation end information, the execution subject on which the vehicle control method runs determines to stop recording the vehicle's driving track, vehicle operating status and operation status.

[0049] Step 208 , based on the driving trajectory, vehicle operating status and operating status, path planning information of the area is generated, and then step 205 is executed.

[0050] In this embodiment, based on the timing of the vehicle's operating status and operating status, the behavior trajectory, vehicle operating status and operating status are arranged in chronological order to generate a path planning information that reflects the operation of the vehicle and the status of each component on the vehicle in a certain time period. The path planning information can guide the specific operations of the vehicle's automatic driving system at different times.

[0051] Optionally, the generated path planning information of the area may be stored locally, so that the vehicle can select the path planning information from the local database.

[0052] Optionally, the generated path planning information of the area may also be uploaded to a cloud server so that the cloud server sends the path planning information to all vehicles.

[0053] The vehicle control method provided by the embodiments of the present disclosure has strong environmental adaptability and can be applied to complex operating scenarios of automatic operating vehicles (such as mining scenarios). It is necessary to solve problems through both manual operation means and technical means. The path planning information obtained by the vehicle control method can reach the same level as manual driving. The mining scenario operation is a cyclic operation from the loading area-main road-unloading area. For a long time, only one manual driving is required for the same narrow area, and the manual driving time is very short, which is much lower than the time and cost required for model optimization. Therefore, the vehicle operation method disclosed in the present disclosure has the characteristics of low cost, short time cycle and high reliability.

[0054] The vehicle operation method provided in this embodiment, in the process of controlling the vehicle to perform automatic operation, in response to detecting that the vehicle meets the planned obstacle conditions and there is no pre-established path planning information, sends operation notification information, records the vehicle's form trajectory, vehicle operating status and operating status, and generates path planning information for the area where the vehicle is located, thereby comprehensively and reliably recording the vehicle's operation and operating conditions, and ensuring the reliability of the vehicle's automatic operation.

[0055] In some embodiments of the present disclosure, the area where the vehicle is located may include an operating area of ​​the vehicle. When the vehicle is an automatic mining vehicle, the operating area of ​​the vehicle includes a loading area, a main road, and an unloading area; Figure 3 A process 300 according to another embodiment of a vehicle control method of the present disclosure is shown. The vehicle control method comprises the following steps:

[0056] Step 301, real-time detection of whether the vehicle meets the planned obstacle conditions, then execution of step 302.

[0057] In this embodiment, the planning obstacle condition is a condition under which the vehicle's automatic driving system cannot effectively perform path planning.

[0058] Step 302 , in response to detecting that the vehicle meets the planning obstacle condition, the area where the vehicle is located is determined based on the location of the vehicle, and then step 303 is executed.

[0059] Step 303: Based on the area, detect whether there is pre-established path planning information.

[0060] Step 304 , in response to detecting that there is pre-established path planning information, the vehicle is controlled to operate automatically based on the path planning information, and then step 305 is executed.

[0061] It should be understood that the operations and features in the above steps 301-304 correspond to the operations and features in steps 101-104 respectively. Therefore, the above descriptions of the operations and features in steps 101-104 are also applicable to steps 301-304 and will not be repeated here.

[0062] Step 305 , when the vehicle is operating automatically, detect in real time whether the operating area in the path planning information has changed, and then execute step 306 .

[0063] Step 306, in response to detecting a change in the operating area, optimizing the path planning information to obtain optimized path planning information.

[0064] In this embodiment, the optimization of the path planning information may be an optimization of the driving track in the pre-stored path planning information based on the changed working area, for example, removing the driving track corresponding to the disappeared working area.

[0065] Optionally, the optimization of the path planning information may also be performed by optimizing the driving behavior state in the path planning information based on the changed working area. For example, when the working area becomes smaller, the throttle opening corresponding to the working area in the driving behavior state is reduced.

[0066] For an automatic mining vehicle, when loading minerals in the loading area, the operating area in the path planning information will change as the excavator performs loading operations and moves. The execution entity on which the vehicle control method runs will re-plan the path planning information based on the previously collected path planning information and the vehicle-side autonomous path planning capability to obtain optimized path planning information.

[0067] The vehicle control method provided in this embodiment optimizes the path planning information when the vehicle is operating and detects that the operating area in the path planning information has changed, and obtains the optimized path planning information, thereby providing effective support for the subsequent automatic operation of the vehicle.

[0068] Optionally, the optimized path planning information may also be uploaded to a cloud server, so that when the cloud server receives an acquisition request from other vehicles, it sends the optimized path planning information to all vehicles.

[0069] Specifically, when the next vehicle drives to the area and the automatic driving system of the next vehicle cannot plan a path, the cloud server is requested for previously stored path planning information or optimized path planning information according to the vehicle's position, and based on the path planning information or the optimized path planning information, the next vehicle is controlled to perform automatic operation.

[0070] Optionally, the optimization of the path planning information can also be that the next vehicle optimizes the path planning information of the vehicle based on the changed operating area after obtaining the path planning information of the vehicle. When the next vehicle drives to the area and finds that it cannot plan the route, the autonomous driving system requests the previously stored path planning library to perform driving behavior based on the vehicle position and optimizes the actual driving path according to the changes in the loading and unloading area during the process. The vehicle synchronizes the optimized path planning to the cloud server again for update and sends it to different vehicles.

[0071] In some optional implementations of this embodiment, the above-mentioned path planning information includes: a planned trajectory corresponding to the working area, and in response to detecting a change in the working area, optimizing the path planning information to obtain optimized path planning information, including: splitting the planned trajectory into at least one operating position point of the vehicle; in response to detecting that the working area disappears, determining the first position point corresponding to the working area in the planned trajectory; removing the first position point from at least one operating position point to obtain at least one planned position point; based on the vehicle's working objectives, connecting at least one planned position point to obtain an optimized planned trajectory.

[0072] In this optional implementation, the planned trajectory is the trajectory of the vehicle operation planned for the vehicle, and the vehicle's operation route and operation route can be determined by planning the trajectory. The planned position point is the operation position point after removing the first position point, that is, the planned position point includes multiple operation position points, and the planned position point does not include the first position point.

[0073] In this optional implementation, the types of vehicles are different, the operation objectives are different, and the operation sequence relationship of different position points required by the operation objectives is different. For example, when the vehicle is an automatic mining vehicle, the operation objective is to load minerals from the loading area, run on the main road, and then reach the unloading area to unload the minerals. For this reason, the operating position points corresponding to the loading area are set to take precedence over the operating position points corresponding to the unloading area, and the operating position points corresponding to the loading area and the operating position points corresponding to the unloading area are distributed along the main road.

[0074] In this optional implementation, there can be multiple first position points in the working area. When the working area disappears, all the first position points are removed. Accordingly, the first position points in the planned trajectory are removed to obtain an optimized planned trajectory, which provides reliable path support for the operation of the vehicle.

[0075] Optionally, the path planning information includes: a planned trajectory corresponding to the working area. In response to detecting a change in the working area, the path planning information is optimized to obtain optimized path planning information, including: splitting the planned trajectory into multiple operating position points, in response to detecting that the area of ​​the working area has become smaller, determining the operating position points of a part of the planned trajectory corresponding to the working area, and removing the operating position points of this part from the multiple operating position points to obtain at least one planned position point; based on the vehicle's operating objectives, connecting at least one planned position point to obtain an optimized planned trajectory.

[0076] In some optional implementations of the present embodiment, the above-mentioned planned obstacle conditions include at least one of the following: when the vehicle is driving automatically, the area where it is located is a narrow area, and a narrow area is an area where the vehicle cannot run automatically or has obstacles to running; for different mission stages in the area where it is located, the vehicle has a preset number of reversing times in the current mission stage.

[0077] In this embodiment, planning obstacle means that the vehicle's automatic driving system cannot effectively plan a path. When the vehicle encounters an obstacle road condition, the vehicle's automatic driving system cannot effectively plan a path, or the path planned by the automatic driving system cannot meet the requirements of the vehicle's automatic driving or automatic operation. At this time, the vehicle meets the planning obstacle condition.

[0078] In this embodiment, the cross-sectional area of ​​the narrow area is less than or equal to the maximum cross-sectional area of ​​the vehicle, and the vehicle cannot pass through the narrow area, or precise driving operations are required to pass through the narrow area. When the vehicle is an autonomous mining vehicle, the narrow area refers to an area below 25m*25m. Due to the large size of the autonomous mining vehicle, it is very difficult to reverse, turn, and turn around in a narrow area.

[0079] In this embodiment, the mission phases of the area where the vehicle is located may be different depending on the function of the vehicle. When the vehicle is an autonomous mining vehicle, the mission phases may include: entering the loading area, reversing the loading area, leaving the loading area, heavy-load transportation, entering the unloading area, reversing the unloading area, leaving the unloading area, and empty-load transportation operations.

[0080] In this optional implementation, the above-mentioned preset number of times can be set based on the needs of automatic operation. For example, if the preset number of times is 3 times, when the autonomous driving mining vehicle has 3 reverses in any of the above-mentioned task stages, it is determined that the vehicle meets the planned obstacle conditions.

[0081] The planning obstacle conditions provided by this optional implementation method include: the area where the vehicle is located is a narrow area or the operating path planned by the vehicle's automatic driving system has a preset number of reversing, which provides optional road conditions for the inability of automatic driving to effectively plan the path.

[0082] Optionally, the planning obstacle conditions may also include: when the vehicle is driving automatically, the area where it is located is a road congestion area. The road congestion area is an area where the vehicle cannot move forward on the road, and the vehicle cannot perform path planning in the road congestion area.

[0083] In some optional implementations of this embodiment, the path planning information includes: a driving trajectory, a vehicle operating status, and different operating tasks of the vehicle along the driving trajectory; based on the path planning information, the vehicle is controlled to operate automatically, including: controlling the vehicle to automatically drive along the driving trajectory; when the vehicle runs along the driving trajectory, controlling the vehicle to operate according to the vehicle operating status; when the vehicle runs along the driving trajectory, controlling the vehicle to operate automatically based on different operating tasks.

[0084] In this optional implementation, the driving trajectory refers to a planned vehicle driving route, which includes at least one planned trajectory corresponding to an operating area. All planned trajectories are connected in series according to the vehicle operation requirements. The vehicle's automatic driving system controls the vehicle to perform automatic driving on the driving trajectory. When the vehicle runs on the planned trajectory, the vehicle needs to perform automatic operations while driving automatically to complete the operating tasks in different operating areas.

[0085] In this optional implementation, the vehicle operating status refers to the vehicle's own operation and the environmental status inside and outside the vehicle. Specifically, the vehicle operating status may include: driving status such as vehicle speed, braking, and throttle. The vehicle operating status also includes: environmental status such as temperature and humidity inside and outside the vehicle.

[0086] In this optional implementation, when the vehicle runs along the driving trajectory, the vehicle is controlled to operate automatically based on different work tasks, including: real-time detection of whether different position points on the driving trajectory belong to different work areas, in response to any position point on the driving trajectory belonging to any work area among the different work areas, controlling the vehicle to perform the work task corresponding to the work area at the position point, and when all the work areas corresponding to the vehicle have been detected, determining that the vehicle has completed the automatic operation.

[0087] In this optional implementation, the vehicle's automatic operation is controlled based on the driving trajectory, vehicle operating status and different operating tasks recorded in the path planning information. It has strong environmental adaptability, so that the vehicle's automatic operation can reach the same level as manual driving.

[0088] Optionally, the path planning information includes: a driving trajectory and a vehicle operating status. The above-mentioned controlling the vehicle to operate automatically based on the path planning information includes: controlling the vehicle to automatically drive along the driving trajectory; when the vehicle runs along the driving trajectory, controlling the vehicle to operate according to the vehicle operating status.

[0089] Optionally, the path planning information includes: a task at a task location point, and the above-mentioned controlling the vehicle to automatically operate based on the path planning information includes: when the vehicle is at the task location point, executing the task at the task location point.

[0090] In some optional implementations of the present embodiment, the above-mentioned detection of whether there is pre-established path planning information based on the area includes: sending an information acquisition request to the cloud server, so that the cloud server detects whether a pre-established path planning library has path planning information corresponding to the area based on the information acquisition request, and obtains a detection result; receiving the detection result of the cloud server, and detecting whether there is pre-established path planning information based on the detection result.

[0091] In this optional implementation, the path planning information is uploaded to the cloud server. When the vehicle meets the planning obstacle conditions in the area where it is located, an information acquisition request can be sent to the cloud server in real time. The cloud server can detect whether the area where the vehicle is located corresponds to the path planning information, providing reliable support for the vehicle's path planning.

[0092] Optionally, the above-mentioned detecting whether there is pre-established path planning information based on the area includes: sending an information acquisition request to the cloud server, and receiving initial planning information sent by the cloud server; the information acquisition request includes: the location; based on the initial planning information, determining the changes in the working area of ​​the area, based on the changes in the working area, modifying the initial planning information to obtain the path planning information.

[0093] In this optional implementation, the initial planning information is the path planning information obtained when the historical vehicle was operating in the area at a historical moment. The execution entity on which the vehicle control method runs, after obtaining the initial planning information sent by the cloud server, modifies the initial planning information based on the changes in the current working area, so that the obtained path planning information can be fully adapted to the actual terrain conditions of the area where the vehicle is located, thereby improving the reliability of the vehicle in automatic operation.

[0094] Further references Figure 4 As an implementation of the methods shown in the above figures, the present disclosure provides an embodiment of a vehicle control device, which is similar to Figure 1 Corresponding to the method embodiment shown, the device can be specifically applied to various electronic devices.

[0095] like Figure 4 As shown, the vehicle control device 400 provided in this embodiment includes: a condition detection unit 401, a determination unit 402, an information detection unit 403, and a control unit 404. Among them, the above-mentioned condition detection unit can be configured to detect in real time whether the vehicle meets the planning obstacle condition, and the planning obstacle condition is a condition under which the vehicle's automatic driving system cannot effectively plan the path. The above-mentioned determination unit can be configured to determine the area where the vehicle is located based on the location of the vehicle in response to detecting that the vehicle meets the planning obstacle condition. The above-mentioned information detection unit can be configured to detect whether there is pre-established path planning information based on the area where it is located. The path planning information is the vehicle information of different areas collected after the manual operation of the vehicle at a historical moment. The above-mentioned control unit can be configured to control the automatic operation of the vehicle based on the path planning information in response to detecting that there is pre-established path planning information.

[0096] In this embodiment, the specific processing of the condition detection unit 401, the determination unit 402, the information detection unit 403, and the control unit 404 and the technical effects thereof can be referred to in detail. Figure 1 The relevant descriptions of step 101, step 102, step 103, and step 104 in the corresponding embodiment are not repeated here.

[0097] In some optional implementations of this embodiment, the device 400 further includes: an operation unit (not shown in the figure). The operation unit may be configured to, in response to detecting that there is no pre-established path planning information, send operation notification information, the operation notification information is used to notify the manual operation vehicle to perform the operation; in response to receiving the operation start information, record the vehicle's driving trajectory, vehicle operating status and operation status; based on the driving trajectory, vehicle operating status and operation status, generate path planning information for the area.

[0098] In some optional implementations of this embodiment, the aforementioned area includes an operating area, and the aforementioned device 400 further includes: a planning unit (not shown in the figure). The aforementioned planning unit may be configured to detect in real time whether the operating area in the path planning information has changed when the vehicle is operating automatically; in response to detecting a change in the operating area, the path planning information is optimized to obtain the optimized path planning information.

[0099] In some optional implementations of this embodiment, the above-mentioned path planning information includes: a planned trajectory corresponding to the working area, and the above-mentioned planning unit can be further configured to: split the planned trajectory into at least one operating position point of the vehicle; in response to detecting the disappearance of the working area, determine the first position point corresponding to the working area in the planned trajectory; remove the first position point from at least one operating position point to obtain at least one planned position point; based on the vehicle's operating objectives, connect at least one planned position point to obtain an optimized planned trajectory.

[0100] In some optional implementations of the present disclosure, the above-mentioned planned obstacle conditions include at least one of the following: when the vehicle is driving automatically, the area where it is located is a narrow area, and the narrow area is an area where the vehicle cannot operate automatically or has obstacles to operation; for different mission stages in the area where it is located, the vehicle has a preset number of reversing times in the current mission stage.

[0101] In some optional implementations of the present disclosure, the above-mentioned path planning information includes: a driving trajectory, a vehicle operating status, and different operating tasks of the vehicle on the driving trajectory; the control unit 404 is further configured to: control the vehicle to automatically drive along the driving trajectory; when the vehicle runs along the driving trajectory, control the vehicle to operate according to the vehicle operating status; when the vehicle runs along the driving trajectory, control the vehicle to automatically operate based on different operating tasks.

[0102] In some optional implementations of the present disclosure, the above-mentioned information detection unit 403 is further configured to: send an information acquisition request to the cloud server, so that the cloud server detects whether the pre-established path planning library has path planning information corresponding to the area based on the information acquisition request, and obtains a detection result; receives the detection result of the cloud server, and detects whether there is pre-established path planning information based on the detection result.

[0103] The vehicle control device provided by the embodiment of the present disclosure, first, the condition detection unit 401 detects in real time whether the vehicle meets the planning obstacle condition, and the planning obstacle condition is a condition that the vehicle's automatic driving system cannot effectively perform path planning; secondly, the determination unit 402 determines the area where the vehicle is located based on the location of the vehicle in response to detecting that the vehicle meets the planning obstacle condition; thirdly, the information detection unit 403 detects whether there is pre-established path planning information based on the area; finally, the control unit 404 controls the vehicle to operate automatically based on the path planning information in response to detecting that there is pre-established path planning information. Therefore, when the automatic driving system of the vehicle cannot effectively plan the path, the manual driving experience is determined through the path planning information corresponding to the area where the vehicle is located, and the vehicle is guided to perform automatic driving or automatic operation based on the manual driving experience, which provides guidance and reference for the automatic driving system of the vehicle and improves the flexibility of the vehicle's automatic operation.

[0104] In the technical solution of the present disclosure, the collection, storage, use, processing, transmission, provision and disclosure of user personal information involved are in compliance with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0105] According to an embodiment of the present disclosure, the present disclosure also provides an electronic device, a readable storage medium and a computer program product.

[0106] Figure 5 A schematic block diagram of an example electronic device 500 that can be used to implement an embodiment of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can 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 merely examples and are not intended to limit the implementation of the present disclosure described and / or required herein.

[0107] like Figure 5As shown, the device 500 includes a computing unit 501, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 502 or a computer program loaded from a storage unit 508 into a random access memory (RAM) 503. In the RAM 503, various programs and data required for the operation of the device 500 can also be stored. The computing unit 501, the ROM 502, and the RAM 503 are connected to each other via a bus 504. An input / output (I / O) interface 505 is also connected to the bus 504.

[0108] A number of components in the device 500 are connected to the I / O interface 505, including: an input unit 506, such as a keyboard, a mouse, etc.; an output unit 507, such as various types of displays, speakers, etc.; a storage unit 508, such as a disk, an optical disk, etc.; and a communication unit 509, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 509 allows the device 500 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0109] The computing unit 501 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 501 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, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The computing unit 501 performs the various methods and processes described above, such as a vehicle control method. For example, in some embodiments, the vehicle control method may be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as a storage unit 508. In some embodiments, part or all of the computer program may be loaded and / or installed on the device 500 via ROM 502 and / or a communication unit 509. When the computer program is loaded into RAM 503 and executed by the computing unit 501, one or more steps of the vehicle control method described above may be performed. Alternatively, in other embodiments, the computing unit 501 may be configured to perform the vehicle control method in any other appropriate manner (e.g., by means of firmware).

[0110] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0111] The program code for implementing the method of the present disclosure may be written in any combination of one or more programming languages. The program code may be provided to a processor or controller of a general purpose computer, a special purpose computer, or other programmable vehicle control device, so that when the program code is executed by the processor or controller, the functions / operations specified in the flow chart and / or block diagram are implemented. The program code may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0112] In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A 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, device, or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, 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 disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0113] To provide interaction with a user, the systems and techniques described herein 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 the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the 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 can be received in any form (including acoustic input, voice input, or tactile input).

[0114] The systems and techniques described herein may be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), and the Internet.

[0115] A computer system may include clients and servers. Clients and servers are generally remote from each other and usually interact through a communication network. The relationship of client and server is generated by computer programs running on respective computers and having a client-server relationship to each other.

[0116] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps recorded in this disclosure can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solutions disclosed in this disclosure can be achieved, and this document does not limit this.

[0117] The above specific implementations do not constitute a limitation on the protection scope of the present disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present disclosure shall be included in the protection scope of the present disclosure.

Claims

1. A vehicle control method, the method comprising: Real-time detection of whether the vehicle meets planning obstacle conditions, where the planning obstacle conditions are conditions under which the vehicle's autonomous driving system cannot effectively perform path planning; In response to detecting that the vehicle meets the planning obstacle condition, determining a location of the vehicle based on the location of the vehicle, wherein the location includes an operation area; Based on the area, detecting whether there is pre-established path planning information, the path planning information is vehicle information of different areas collected after manual vehicle operation at a historical moment, and the path planning information includes a planned trajectory corresponding to the operation area; In response to detecting that there is pre-established path planning information, controlling the vehicle to automatically operate based on the path planning information; When the vehicle is operating automatically, detecting whether the operating area in the path planning information changes; In response to detecting a change in the operation area, optimizing the path planning information to obtain optimized path planning information; The step of optimizing the path planning information in response to detecting a change in the operation area to obtain optimized path planning information includes: Splitting the planned trajectory into a plurality of running position points; In response to detecting that the area of ​​the operating area is reduced, determining an operation position point of a portion of the planned trajectory corresponding to the operating area; Removing the determined part of the operating position points from the plurality of operating position points to obtain at least one planned position point; Based on the operation target of the vehicle, the at least one planned location point is connected to obtain an optimized planned trajectory.

2. The method according to claim 1, further comprising: In response to detecting that there is no pre-established path planning information, sending operation notification information, the operation notification information is used to notify a human to operate the vehicle to perform an operation; In response to receiving the operation start information, recording the vehicle's driving trajectory, the vehicle's operating status, and the operation status; Based on the driving trajectory, the vehicle operating status and the operating status, path planning information of the area is generated.

3. The method according to claim 1 or 2, wherein: The planning obstacle conditions include at least one of the following: When the vehicle is automatically operating, the area is a narrow area, and the narrow area is an area where the vehicle cannot automatically operate or has obstacles to operate; For different mission stages in the area, the vehicle has a preset number of reversing times in the current mission stage.

4. The method according to claim 1 or 2, wherein: The path planning information includes: a driving trajectory, a vehicle operating status, and different operating tasks of the vehicle on the driving trajectory; and controlling the vehicle to automatically operate based on the path planning information includes: Control the vehicle to automatically drive along the driving trajectory; When the vehicle runs along the driving trajectory, controlling the vehicle to run according to the vehicle running state; When the vehicle runs along the driving trajectory, the vehicle is controlled to operate automatically based on the different operating tasks.

5. The method according to claim 1, wherein: The detecting whether there is pre-established path planning information based on the area includes: Sending an information acquisition request to a cloud server, so that the cloud server detects whether a pre-established path planning library has path planning information corresponding to the area based on the information acquisition request, and obtains a detection result; Receive the detection result of the cloud server, and detect whether there is pre-established path planning information based on the detection result.

6. A vehicle control device, comprising: a condition detection unit configured to detect in real time whether the vehicle satisfies a planning obstacle condition, wherein the planning obstacle condition is a condition under which the automatic driving system of the vehicle cannot effectively perform path planning; a determination unit configured to, in response to detecting that the vehicle satisfies the planning obstacle condition, determine a location area of ​​the vehicle based on the location of the vehicle, wherein the location area includes an operation area; An information detection unit is configured to detect whether there is pre-established path planning information based on the area, wherein the path planning information is vehicle information of different areas collected after manual vehicle operation at a historical moment, and the path planning information includes a planned trajectory corresponding to the operation area; a control unit configured to, in response to detecting the presence of pre-established path planning information, control the vehicle to automatically operate based on the path planning information; a planning unit configured to detect whether the operating area in the path planning information changes when the vehicle is operating automatically; in response to detecting that the operating area changes, optimize the path planning information to obtain optimized path planning information; Wherein, the planning unit is further configured to: Splitting the planned trajectory into a plurality of running position points; In response to detecting that the area of ​​the operating area is reduced, determining an operation position point of a portion of the planned trajectory corresponding to the operating area; Removing the determined part of the operating position points from the plurality of operating position points to obtain at least one planned position point; Based on the operation target of the vehicle, the at least one planned location point is connected to obtain an optimized planned trajectory.

7. The device according to claim 6, further comprising: An operation unit, configured to send operation notification information in response to detecting that there is no pre-established path planning information, wherein the operation notification information is used to notify a human to operate the vehicle to perform an operation; In response to receiving the operation start information, recording the vehicle's driving trajectory, the vehicle's operating status, and the operation status; Based on the driving trajectory, the vehicle operating status and the operating status, path planning information of the area is generated.

8. The device according to claim 6 or 7, wherein: The planning obstacle conditions include at least one of the following: When the vehicle is automatically operating, the area is a narrow area, and the narrow area is an area where the vehicle cannot automatically operate or has obstacles to operate; For different mission stages in the area, the vehicle has a preset number of reversing times in the current mission stage.

9. The device according to claim 6 or 7, wherein: The path planning information includes: a driving trajectory, a vehicle operating status, and different operating tasks of the vehicle on the driving trajectory; the control unit is further configured to: control the vehicle to automatically drive along the driving trajectory; when the vehicle runs along the driving trajectory, control the vehicle to run according to the vehicle operating status; when the vehicle runs along the driving trajectory, control the vehicle to automatically operate based on the different operating tasks.

10. The device according to claim 6, wherein: The information detection unit is further configured to: send an information acquisition request to the cloud server, so that the cloud server detects whether a pre-established path planning library has path planning information corresponding to the area based on the information acquisition request, and obtains a detection result; Receive the detection result of the cloud server, and detect whether there is pre-established path planning information based on the detection result.

11. An electronic device, characterized in that: include: at least one processor; as well as a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1 to 5.

12. A non-transitory computer-readable storage medium storing computer instructions, characterized in that: The computer instructions are used to cause the computer to execute the method according to any one of claims 1 to 5.

13. A computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the computer program implements the method according to any one of claims 1 to 5.

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