Collision risk assessment method and device, electronic equipment and storage medium

Abstract

The invention provides a collision risk assessment method. The method comprises the steps of obtaining a to-be-assessed trajectory of a vehicle and predicted trajectories of other vehicles in a preset range; the to-be-evaluated track and the predicted track are converted to the same S-T coordinate system, S is the driving distance of the vehicle on the current lane where the vehicle runs, and T is time; and according to the to-be-evaluated trajectory and the predicted trajectory in the S-T coordinate system, determining whether the vehicle has a collision risk. In the embodiment of the invention, the to-be-assessed trajectory of the vehicle and the predicted trajectory of other vehicles in the preset range are converted into the same S-T coordinate system, and whether the vehicle has a collision risk is determined according to the to-be-assessed trajectory and the predicted trajectory in the S-T coordinate system. According to the embodiment of the invention, the S-T coordinate system is the corresponding relation between the driving distance of the vehicle in the current lane and the time, and the trajectory of the vehicle in the S-T coordinate system appears in a rectangular form, so that the problem of contradiction between the detection density and the detection accuracy is solved.

Description

Technical Field

[0001] The present application relates to the field of assisted driving technology, and specifically to a collision risk assessment method, device, electronic device and storage medium. Background Art

[0002] With the continuous development of automobile technology, more and more cars are equipped with intelligent driving functions, and driving safety is the primary consideration of automobile intelligent driving functions. Driving safety includes not only preventing the vehicle from colliding with other vehicles and obstacles during driving, but also avoiding collisions with other vehicles. Therefore, the assessment of collision risk has become a top priority.

[0003] In the related art, the predicted obstacle trajectory and the planned vehicle trajectory are obtained at preset time intervals. At the same time, it is determined whether there is an intersection between the predicted obstacle trajectory and the planned vehicle trajectory in the XY plane projection, so as to determine whether there is a collision risk.

[0004] However, the size of the time interval in the related art will directly affect the accuracy of collision risk detection. If the time interval is too large, it will lead to missed detection, and if the time interval is too small, it will lead to excessive calculation load.

[0005] It should be pointed out that the information disclosed in the background technology section of this application is only intended to deepen the understanding of the general background technology of this application, and should not be regarded as an admission or suggestion in any form that the information constitutes prior art already known to those skilled in the art. Summary of the invention

[0006] In view of this, the present application provides a collision risk assessment method, device, electronic device and storage medium to help solve the problem in the related art that the time interval directly affects the accuracy of collision risk detection, too large a time interval will lead to missed detection, and too small a time interval will lead to excessive computing load.

[0007] In a first aspect, an embodiment of the present application provides a collision risk assessment method, comprising: Obtain the trajectory of the vehicle to be evaluated and the predicted trajectories of other vehicles within the preset range; Convert the trajectory to be evaluated and the predicted trajectory to the same ST coordinate system, where S is the distance traveled by the vehicle in the current lane of the vehicle, and T is the time; Determine whether the ego-vehicle has a collision risk based on the to-be-evaluated trajectory and the predicted trajectory in the ST coordinate system.

[0008] In the embodiment of the present application, the trajectory to be evaluated of the vehicle and the predicted trajectory of other vehicles within the preset range are converted to the same ST coordinate system, and based on the trajectory to be evaluated and the predicted trajectory in the ST coordinate system, it is determined whether the vehicle is at risk of collision. The ST coordinate system of the embodiment of the present application is the correspondence between the driving distance and time of the vehicle in the current lane, and the trajectory of the vehicle in the ST coordinate system appears in the form of a rectangle, which solves the problem of the contradiction between detection density and detection accuracy.

[0009] In a possible implementation, determining whether the ego-vehicle has a collision risk according to the to-be-evaluated trajectory and the predicted trajectory in the ST coordinate system includes: Determine whether the collision detection unit of the trajectory to be evaluated and the collision detection unit of the predicted trajectory corresponding to the same time period in the ST coordinate system overlap, and the collision detection unit is a trajectory within a preset time length; If the collision detection unit of the to-be-evaluated trajectory and the collision detection unit of the predicted trajectory corresponding to the same time period in the ST coordinate system overlap, it is determined that the ego-vehicle has a collision risk; If the collision detection unit of the trajectory to be evaluated and the collision detection unit of the predicted trajectory corresponding to the same time period in the ST coordinate system do not overlap, it is determined that there is no collision risk for the ego vehicle.

[0010] In the embodiment of the present application, whether the vehicle has a collision risk is determined by whether the collision detection unit of the trajectory to be evaluated and the collision detection unit of the predicted trajectory corresponding to the same time period in the ST coordinate system overlap. It can be understood that the collision detection unit is a trajectory within a preset time length, and if the collision detection units overlap, it can be determined that there is a collision risk.

[0011] In a possible implementation, the preset duration is a minimum step update duration, and before determining whether the collision detection unit of the trajectory to be evaluated in the ST coordinate system coincides with the collision detection unit of the predicted trajectory, the method further includes: The minimum step update duration is calculated based on the preset decision cycle and the maximum number of decision updates, where the maximum number of decision updates is the maximum number of times a decision is changed within the preset decision cycle.

[0012] In the embodiment of the present application, the preset duration is the minimum step update duration. It is understandable that the minimum step update duration can ensure that each decision step of the vehicle is recorded, and each decision of the vehicle can be accurately recorded.

[0013] In a possible implementation, the method further includes: Determine the driving style according to the number of decision updates, where the number of decision updates is the number of times the decision is changed within the preset decision cycle; Based on the described driving style, driving decisions are adjusted.

[0014] In the embodiment of the present application, the driving style is determined based on the number of decision updates, and the driving decision is adjusted based on the driving style. It can be understood that determining the driving style helps to plan multiple behaviors within the decision cycle, thereby controlling the vehicle more flexibly and efficiently and avoiding overly conservative driving.

[0015] In a possible implementation, judging the driving style according to the decision update number includes: If the decision update number is greater than or equal to a first preset number, determining that the driving style is an aggressive type; If the decision update number is less than or equal to a second preset number, determining that the driving style is conservative; Wherein, the first preset number of times is greater than the second preset number of times.

[0016] In the embodiment of the present application, if the number of decision updates is greater than or equal to the first preset number, the driving style is determined to be aggressive; if the number of decision updates is less than or equal to the second preset number, the driving style is determined to be conservative. It can be understood that if the decision is updated too quickly, the driving style is more aggressive; if the decision is updated too slowly, the driving style is more conservative.

[0017] In a possible implementation, the determining whether the collision detection unit of the trajectory to be evaluated in the ST coordinate system coincides with the collision detection unit of the predicted trajectory includes: If the distance between the predicted trajectory and the trajectory to be evaluated is less than or equal to a preset distance threshold at the same time, it is determined whether the collision detection unit of the trajectory to be evaluated in the ST coordinate system overlaps with the collision detection unit of the predicted trajectory.

[0018] In the embodiment of the present application, only when the distance between the predicted trajectory and the trajectory to be evaluated at the same time is less than or equal to the preset distance threshold, is it determined whether the collision detection units in the ST coordinate system overlap. It can be understood that if the distance between the predicted trajectory and the trajectory to be evaluated at the same time is greater than the preset distance threshold, there is no risk of collision between the vehicle and other vehicles. Therefore, judging the distance in advance can avoid some unnecessary calculation loads.

[0019] In a possible implementation, the method further includes: Determine whether the distance between the predicted trajectory and the trajectory to be evaluated at the same time is less than or equal to a preset distance threshold; If the distance between the predicted trajectory and the trajectory to be evaluated at the same time is greater than a preset distance threshold, it is determined that there is no collision risk for the vehicle.

[0020] In the embodiment of the present application, if the distance between the predicted trajectory and the trajectory to be evaluated at the same time is greater than a preset distance threshold, it can be directly determined that there is no collision risk for the vehicle, thus avoiding some unnecessary calculation load.

[0021] In a second aspect, an embodiment of the present application provides a collision risk assessment device, comprising: The trajectory acquisition module is used to obtain the trajectory of the vehicle to be evaluated and the predicted trajectories of other vehicles within a preset range; A coordinate conversion module, used for converting the trajectory to be evaluated and the predicted trajectory into the same ST coordinate system, wherein S is the distance traveled by the vehicle in the current lane of the ego vehicle, and T is the time; A collision risk determination module is used to determine whether the vehicle has a collision risk based on the trajectory to be evaluated and the predicted trajectory in the ST coordinate system.

[0022] In a third aspect, an embodiment of the present application provides an electronic device, including: processor; Memory; And a computer program, wherein the computer program is stored in the memory, and the computer program includes instructions, and when the instructions are executed by the processor, the electronic device executes any one of the methods described in the first aspect.

[0023] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, characterized in that the computer-readable storage medium includes a stored program, wherein when the program is running, the device where the computer-readable storage medium is located is controlled to execute any one of the methods described in the first aspect.

[0024] It is understandable that the collision risk assessment device provided in the second aspect, the electronic device provided in the third aspect, and the computer-readable storage medium provided in the fourth aspect are used to execute the method provided in the present application. Therefore, the beneficial effects that can be achieved can refer to the beneficial effects in the corresponding method, which will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0026] Figure 1 A schematic diagram of a grid map in the first type of related technology; Figure 2 A schematic diagram of the corresponding relationship between the detection density and the detection result provided in an embodiment of the present application; Figure 3 A schematic diagram of a flow chart of a collision risk assessment method provided in an embodiment of the present application; Figure 4 A schematic diagram of a trajectory to be evaluated and a predicted trajectory in an ST coordinate system provided in an embodiment of the present application; Figure 5 A schematic diagram of a trajectory to be evaluated and a predicted trajectory in another ST coordinate system provided in an embodiment of the present application; Figure 6 A schematic diagram of a trajectory to be evaluated and a predicted trajectory in another ST coordinate system provided in an embodiment of the present application; Figure 7 A schematic diagram of a trajectory to be evaluated and a predicted trajectory in another ST coordinate system provided in an embodiment of the present application; Figure 8 A schematic diagram of the structure of a collision risk assessment device provided in an embodiment of the present application; Fig. 9 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0027] In order to better understand the technical solution of the present application, the embodiments of the present application are described in detail below with reference to the accompanying drawings.

[0028] It should be clear that the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without creative work are within the scope of protection of the present application.

[0029] The terms used in the embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to limit the present application. The singular forms "a", "said" and "the" used in the embodiments of the present application and the appended claims are also intended to include plural forms, unless the context clearly indicates other meanings.

[0030] It should be understood that the term "and / or" used in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship.

[0031] With the continuous development of automobile technology, more and more cars are equipped with intelligent driving functions, and driving safety is the primary consideration of automobile intelligent driving functions. Driving safety includes not only preventing the vehicle from colliding with other vehicles and obstacles during driving, but also avoiding collisions with other vehicles. Therefore, the assessment of collision risk has become a top priority.

[0032] In the first category of related technologies, the motion trajectory of the vehicle is based on a two-dimensional occupancy grid map. The autonomous driving vehicle knows the grid map of obstacles that exist at the current moment, and then determines the collision risk of the planned trajectory by sampling and querying whether there are obstacles occupied on the planned trajectory of the vehicle. In order to simplify the calculation of the grid covered by the vehicle along the planned trajectory, the outline of the vehicle is generally abstracted into a simple regular geometric object such as a circle or rectangle. For ease of understanding, the embodiment of the present application also provides a schematic diagram of a grid map in a related technology.

[0033] See also Figure 1 , is a schematic diagram of a grid map in the first category of related technologies. Figure 1 As shown, the dotted line in the grid map is the planned trajectory of the vehicle. Figure 1 In the grid map of , the vehicle outline is a rectangular outline. In practical applications, the vehicle outline can also be abstracted into other geometric objects, such as a circular outline and a three-circle outline. When there is an obstacle, the corresponding position in the grid map will mark the obstacle position. By judging whether the planned trajectory of the vehicle coincides with the obstacle, it can be determined whether the vehicle and the obstacle will collide.

[0034] However, the above method only considers the obstacle occupation status at the current time, and does not involve the future movement trend of the obstacle, which leads to short-sightedness of the autonomous driving vehicle. For example, at the current moment, there is no obstacle occupying the second half of the planned trajectory of the vehicle, but this does not mean that there will still be no obstacles when the vehicle moves to the second half of the trajectory according to the planned trajectory.

[0035] To address this problem, the second type of related technology usually predicts the future movement trajectory of the obstacle and adds it to the collision risk detection. Compared with the method provided by the first type of related technology, the second type of related technology adds a time dimension to dynamically consider the movement trend of the obstacle. At the same time, it is determined whether the vehicle and the obstacle will collide by checking whether there is an intersection between the predicted obstacle trajectory and the planned trajectory of the vehicle in the XY plane projection. If there is an intersection, it means there is a collision risk.

[0036] In the second type of related technology, it is necessary to obtain the obstacle prediction trajectory and the vehicle trajectory at a preset time interval. However, the size of the time interval will directly affect the accuracy of collision risk detection. Too long a time interval (i.e., too low a detection density) will lead to missed detections, while too short a time interval (i.e., too high a detection density) will lead to excessive computational load.

[0037] See also Figure 2 , is a schematic diagram of the corresponding relationship between the detection density and the detection result provided in the embodiment of the present application. Figure 2 As shown in the figure, the red vehicle is the neighboring vehicle (i.e., obstacle), the blue vehicle is the vehicle itself, the red line corresponding to the red vehicle is the predicted trajectory of the neighboring vehicle, the blue line corresponding to the blue vehicle is the candidate set of the planned trajectory of the vehicle itself, and the intersection point P (x, y, t) of the two lines is the collision point. When the detection density is high, the collision point can be clearly obtained, such as Figure 2 As shown in a in , it will lead to excessive computational load, because each sampling point on each trajectory needs to calculate the grid occupancy of its geometric contour; when the detection density is low, it will be missed, such as Figure 2 As shown in b in Figure , although the two trajectories intersect at time t, due to the sparse sampling points, no sampling is performed at time t, and thus no collision is detected.

[0038] In response to the above problems, an embodiment of the present application provides a collision risk assessment method, which converts the trajectory to be evaluated of the vehicle and the predicted trajectory of other vehicles within a preset range into the same ST coordinate system, and determines whether the vehicle has a collision risk based on the trajectory to be evaluated and the predicted trajectory in the ST coordinate system. The ST coordinate system of the embodiment of the present application is the correspondence between the driving distance and time of the vehicle in the current lane, and the trajectory of the vehicle in the ST coordinate system appears in the form of a rectangle, which solves the problem of the contradiction between detection density and detection accuracy. It is described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0039] See also Figure 3 , is a flow chart of a collision risk assessment method provided in an embodiment of the present application. Figure 3 As shown, it mainly includes the following steps.

[0040] Step S301: Obtain the trajectory to be evaluated of the vehicle and the predicted trajectories of other vehicles within a preset range.

[0041] Specifically, the collision risk assessment device can obtain the trajectory to be assessed of the vehicle and the predicted trajectory of other vehicles within the preset range from other modules. In the embodiment of the present application, the preset range is the perception range of the vehicle. Because the perception range of the vehicle is limited, the vehicle cannot obtain the predicted trajectory of vehicles outside the perception range.

[0042] Of course, in actual applications, it can be determined that there is no collision risk for vehicles outside the preset range, so the preset range can be smaller than the perception range of the vehicle itself, and the embodiments of the present application do not impose specific restrictions on this.

[0043] Step S302: converting the trajectory to be evaluated and the predicted trajectory into the same ST coordinate system.

[0044] Specifically, because the trajectory to be evaluated and the predicted trajectory are usually in the XY Cartesian coordinate system, in order to more reliably and efficiently judge the spatiotemporal relationship between the two trajectories, the present application first converts the trajectory to be evaluated and the predicted trajectory in the XY coordinate system to the ST coordinate system to obtain a trajectory diagram in the ST coordinate system, wherein S is the distance traveled by the vehicle in the current lane in which the vehicle is traveling, and T is the time.

[0045] It is understandable that different driving decisions correspond to different trajectories, and the trajectory to be evaluated in the embodiment of the present application is one of a plurality of different trajectories.

[0046] For ease of understanding, an embodiment of the present application provides a schematic diagram of a trajectory to be evaluated and a predicted trajectory in an ST coordinate system.

[0047] See also Figure 4 , is a schematic diagram of a trajectory to be evaluated and a predicted trajectory in an ST coordinate system provided in an embodiment of the present application. Figure 4 As shown in the figure, the red vehicle is another vehicle, the blue vehicle is the self-vehicle, the red dotted line corresponding to the red vehicle is the driving trajectory of the other vehicle, the blue dotted line corresponding to the blue vehicle is the driving trajectory of the self-vehicle, the red rectangle corresponding to the red vehicle is the predicted trajectory ST projection, and the blue rectangle corresponding to the blue vehicle is the ST projection of the trajectory to be evaluated. This is the case in the following text and will not be described in detail below. Figure 4 As shown on the left, the black dotted line is the current lane of the ego vehicle, and other vehicles are driving in front of the ego vehicle. When obtaining the predicted trajectory of other vehicles, the collision risk assessment device can predict the driving distance of other vehicles in the next 6 seconds based on the current driving speed of other vehicles, thereby obtaining Figure 4 The predicted trajectory ST projection in the ST coordinate system on the right. At the same time, the collision risk assessment device obtains the driving decision of the vehicle in the next 6 seconds from other modules of the vehicle, and determines the relationship between the driving distance and time of the vehicle in the next 6 seconds based on the driving decision, that is, the ST projection of the trajectory to be assessed. It can be understood that Figure 4 The slope of the long side of each rectangle in the ST diagram on the right is the speed of the corresponding vehicle.

[0048] It should be pointed out that Figure 4 The 6 seconds, the speed of the vehicle, the speed of other vehicles, and the number of other vehicles shown in the figure are merely exemplary descriptions and should not be regarded as limiting the scope of protection of the present application.

[0049] Step S303: Determine whether the vehicle has a collision risk based on the trajectory to be evaluated and the predicted trajectory in the ST coordinate system.

[0050] Specifically, after obtaining the trajectory to be evaluated and the predicted trajectory in the ST coordinate system, the collision risk assessment device determines whether the vehicle has a collision risk according to the ST coordinate system.

[0051] In one possible implementation, it is determined whether the collision detection unit of the trajectory to be evaluated corresponding to the same time period in the ST coordinate system overlaps with the collision detection unit of the predicted trajectory, and the collision detection unit is a trajectory within a preset time length; if the collision detection unit of the trajectory to be evaluated corresponding to the same time period in the ST coordinate system overlaps with the collision detection unit of the predicted trajectory, it is determined that the vehicle is at risk of collision; if the collision detection unit of the trajectory to be evaluated corresponding to the same time period in the ST coordinate system does not overlap with the collision detection unit of the predicted trajectory, it is determined that the vehicle is not at risk of collision.

[0052] In the embodiment of the present application, the collision detection unit is a trajectory within a preset time length, and the trajectory is a trajectory to be evaluated or a predicted trajectory. It can be understood that the trajectory within the preset time length in the trajectory to be evaluated is the collision detection unit of the trajectory to be evaluated, and the trajectory within the preset time length in the predicted trajectory is the collision detection unit of the predicted trajectory. Among them, the preset time length can be any time length, and the embodiment of the present application does not make specific restrictions.

[0053] However, because the present application is applicable to multi-step decision algorithms such as partially observable Markov decision processes (POMDPs), and such algorithms require multiple branch decision steps to complete the solution from the initial state to the triggering of the termination condition to exit the solution process. In order to obtain a more accurate collision detection unit, the preset duration in the embodiment of the present application is the minimum step update duration.

[0054] Therefore, before determining whether the collision detection units overlap, it is necessary to calculate the minimum step update duration. Specifically, the minimum step update duration is calculated based on the preset decision cycle and the maximum decision update number, and the maximum decision update number is the maximum number of times the decision is changed within the preset decision cycle.

[0055] For example, assuming a POMDP behavior decision model, the maximum decision cycle is set to 6 seconds, the maximum decision update number Dmax is 3, and the minimum step update time △t is 2 seconds. The physical meaning of the maximum decision update number Dmax is the number of changes in longitudinal behavior or lateral behavior during the entire decision cycle. Among them, longitudinal behavior includes acceleration and deceleration, and lateral behavior includes left turn, right turn, straight driving, etc.

[0056] Assuming that the minimum step update time is △t, and t2=t1+△t, the trajectories to be evaluated corresponding to t1 are St1min and St1max, and the trajectories to be evaluated corresponding to t2 are St2min and St2max, then the rectangle with St1min, St1max, St2min and St2max as vertices is the collision detection unit of the trajectory to be evaluated. For example, Figure 4As shown, the minimum step update time is 2 seconds, the collision detection unit of the trajectory to be evaluated within 0-2 seconds is the blue rectangle corresponding to 0-2 seconds, and the collision detection unit of the predicted trajectory within 0-2 seconds is the red rectangle corresponding to 0-2 seconds.

[0057] In a possible implementation, after obtaining the number of decision updates, the driving style can be judged based on the number of decision updates, where the number of decision updates is the number of times the decision is changed within a preset decision cycle; and the driving decision is adjusted based on the driving style.

[0058] It should be noted that the maximum number of decision updates corresponds to the maximum decision cycle, and the number of decision updates corresponds to any preset decision cycle, that is, when the preset decision cycle is the maximum decision cycle, the number of decision updates is the maximum number of decision updates.

[0059] It is understandable that when the number of decision updates is too large, it means that the driving behavior has been changed frequently and multiple times within the preset decision cycle, such as continuous acceleration and deceleration, which indicates an aggressive driving style that easily affects the comfort of the driver and passengers. When the number of decision updates is too small, it means that there are few behavioral changes within the preset decision cycle. For example, in extreme cases, the number of decision updates is 1, and in the future decision cycle, only one of the longitudinal behaviors such as acceleration, deceleration or constant speed is performed, or only one of the lateral behaviors such as left turn and right turn is taken. Then, after adding the principle of driving safety first, the driving style is conservative and inefficient.

[0060] For example, Figure 4 The speed of the trajectory to be evaluated is uniform, that is, the number of decision updates is 1. Figure 4 It can be seen that there is no risk of collision between the ego vehicle and other vehicles, and too few decision updates result in the distance between the ego vehicle and other vehicles getting farther and farther. Usually users expect the vehicle to reach the destination as quickly as possible while ensuring safety, so too few decision updates will also affect the user experience.

[0061] The embodiment of the present application also provides a schematic diagram of a trajectory to be evaluated and a predicted trajectory in another ST coordinate system.

[0062] See also Figure 5 , is a schematic diagram of another trajectory to be evaluated and predicted trajectory in the ST coordinate system provided in an embodiment of the present application. Figure 5 As shown in Figure 2, the collision detection unit of the trajectory to be evaluated does not overlap with the collision detection unit of the predicted trajectory, so there is no collision risk for the ego vehicle, and the ego vehicle speed increases first and then decreases, which is consistent with Figure 4 In comparison, the distance traveled in the same amount of time is farther, so the driving efficiency is higher.

[0063] In a possible implementation, the driving style is determined to be aggressive or conservative by comparing the relationship between the number of decision updates and the preset number, so as to adjust the driving decision according to the obtained driving style. It can be understood that when the driving style is aggressive, the number of decision updates is appropriately reduced; when the driving style is conservative, the number of decision updates is appropriately increased. Of course, the premise of increasing the number of decision updates is to ensure driving safety.

[0064] Although the driving style is conservative when the number of decision updates is small, conservative does not mean that collisions will not occur.

[0065] For example, see Figure 6 , is a schematic diagram of another trajectory to be evaluated and predicted trajectory in the ST coordinate system provided in an embodiment of the present application. Figure 6 As shown in the figure, the driving style of this car is conservative, but due to the high speed, the collision detection unit of the trajectory to be evaluated and the collision detection unit of the predicted trajectory overlap within 2-4 seconds. In other words, if the car drives according to the current driving decision, it will collide with other vehicles within 2-4 seconds. This obviously violates the principle of driving safety, so it is necessary to adjust the driving decision in advance to avoid collisions as much as possible.

[0066] Specifically, if the number of decision updates is greater than or equal to the first preset number, the driving style is determined to be aggressive; if the number of decision updates is less than or equal to the second preset number, the driving style is determined to be conservative; wherein the first preset number is greater than the second preset number. Those skilled in the art may set the first preset number and the second preset number to any number according to actual needs, and the embodiments of the present application do not impose specific restrictions on this.

[0067] In one possible implementation, it is determined whether the distance between the predicted trajectory and the trajectory to be evaluated at the same time is less than or equal to a preset distance threshold; if the distance between the predicted trajectory and the trajectory to be evaluated at the same time is less than or equal to the preset distance threshold, it is further determined whether the collision detection unit of the trajectory to be evaluated corresponding to the same time period in the ST coordinate system coincides with the collision detection unit of the predicted trajectory; if the distance between the predicted trajectory and the trajectory to be evaluated at the same time is greater than the preset distance threshold, it is determined that there is no collision risk for the vehicle. Those skilled in the art can set the preset distance threshold to any number according to actual needs, and the embodiments of the present application do not impose specific restrictions on this.

[0068] For example, taking a side collision as an example, see Figure 7 , is a schematic diagram of another trajectory to be evaluated and predicted trajectory in the ST coordinate system provided in an embodiment of the present application. Figure 7As shown in the figure, the distance between the predicted trajectory corresponding to 0-2 seconds and the trajectory to be evaluated is greater than the preset distance threshold, so the predicted trajectory of other vehicles is a gray rectangle. At this time, it can be directly determined that there is no collision risk with the vehicle, thereby avoiding some unnecessary calculation load. And if the vehicle drives according to the current driving decision, it will collide with other vehicles within 2-4 seconds. This obviously violates the principle of driving safety, so it is necessary to adjust the driving decision in advance after detecting the predicted trajectory of other vehicles to avoid collision as much as possible.

[0069] In summary, the judgment of whether there is a collision risk between the vehicle and other vehicles within a certain time interval △t can be represented by the formula, specifically: in, Used to characterize the collision risk within △t time, if the distance between the predicted trajectory and the trajectory to be evaluated is If the distance is less than or equal to the preset distance threshold, and the collision detection unit of the trajectory to be evaluated intersects with the collision detection unit of the predicted trajectory, a collision will occur. In other cases, no collision will occur. Characterizes the distance between the predicted trajectory and the trajectory to be evaluated Less than or equal to the preset distance threshold , A collision detection unit that represents the trajectory to be evaluated Collision detection unit with predicted trajectory There is an intersection.

[0070] In summary, the embodiments of the present application utilize the characteristics of multi-step decision algorithms such as POMDP to construct a more flexible collision detection unit according to the decision step size, thereby making it easier to plan a safe and efficient trajectory.

[0071] Corresponding to the above embodiments, the present application also provides a collision risk assessment device.

[0072] See also Figure 8 , is a schematic diagram of the structure of a collision risk assessment device provided in an embodiment of the present application. Figure 8 As shown, the collision risk assessment device includes a trajectory acquisition module 801, a coordinate conversion module 802 and a collision risk determination module 803. These components communicate through one or more buses. Those skilled in the art can understand that the structure of the electronic device shown in the figure does not constitute a limitation on the embodiments of the present application. It can be a bus structure or a star structure, and can also include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently.

[0073] The trajectory acquisition module 801 is used to obtain the trajectory to be evaluated of the vehicle and the predicted trajectories of other vehicles within a preset range; A coordinate conversion module 802 is used to convert the trajectory to be evaluated and the predicted trajectory into the same ST coordinate system, where S is the distance traveled by the vehicle in the current lane of the ego vehicle, and T is the time; The collision risk determination module 803 is used to determine whether the vehicle has a collision risk based on the trajectory to be evaluated and the predicted trajectory in the ST coordinate system.

[0074] Corresponding to the above embodiments, the present application also provides an electronic device.

[0075] See also Fig. 9 , is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. Fig. 9 As shown, the electronic device 900 may include: a processor 901, a memory 902 and a communication unit 903. These components communicate via one or more buses. Those skilled in the art will appreciate that the structure of the electronic device shown in the figure does not limit the embodiments of the present application. It may be a bus structure or a star structure, and may include more or fewer components than shown in the figure, or combine certain components, or arrange components differently.

[0076] The communication unit 903 is used to establish a communication channel so that the electronic device can communicate with other devices, receive user data sent by other devices or send user data to other devices.

[0077] The processor 901 is the control center of the electronic device. It uses various interfaces and lines to connect various parts of the entire electronic device. It runs or executes software programs, instructions, and / or modules stored in the memory 902, and calls data stored in the memory to perform various functions of the electronic device and / or process data. The processor can be composed of an integrated circuit (IC), for example, it can be composed of a single packaged IC, or it can be composed of multiple packaged ICs with the same or different functions. For example, the processor 901 can include only a central processing unit (CPU). In the embodiment of the present application, the CPU can be a single computing core or multiple computing cores.

[0078] The memory 902 is used to store the execution instructions of the processor 901. The memory 902 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0079] When the execution instructions in the memory 902 are executed by the processor 901, the electronic device 900 can execute Figure 3 Some or all of the steps in the illustrated embodiments.

[0080] In a specific implementation, the embodiment of the present application further provides a computer storage medium, wherein the computer storage medium may store a program, and when the program is executed, the program may include some or all of the steps in each embodiment of the simulation scene generation method provided in the embodiment of the present application. The storage medium may be a disk, an optical disk, a read-only memory (ROM) or a random access memory (RAM), etc.

[0081] In the embodiments of the present application, "at least one" refers to one or more, and "plurality" refers to two or more. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can represent the existence of A alone, the existence of A and B at the same time, and the existence of B alone. Among them, A and B can be singular or plural. The character " / " generally indicates that the previous and subsequent associated objects are in an "or" relationship. "At least one of the following" and similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one of a, b and c can be represented by: a, b, c, ab, ac, bc, or abc, where a, b, c can be single or multiple.

[0082] Those of ordinary skill in the art will appreciate that the various units and algorithm steps described in the embodiments disclosed herein can be implemented in a combination of electronic hardware, computer software, and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0083] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0084] In several embodiments provided in the present application, if any function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or the part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk, etc., various media that can store program codes.

[0085] In this specification, the same or similar parts between the various embodiments can be referred to each other. In particular, for the device embodiment and the terminal embodiment, since they are basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the description in the method embodiment.

Claims

1. A collision risk assessment method, characterized in that: include: Obtain the trajectory of the vehicle to be evaluated and the predicted trajectories of other vehicles within the preset range; Convert the trajectory to be evaluated and the predicted trajectory to the same ST coordinate system, where S is the distance traveled by the vehicle in the current lane of the vehicle, and T is the time; Determine whether the ego-vehicle has a collision risk based on the to-be-evaluated trajectory and the predicted trajectory in the ST coordinate system.

2. The method according to claim 1, characterized in that The determining whether the vehicle has a collision risk according to the trajectory to be evaluated and the predicted trajectory in the ST coordinate system includes: Determine whether the collision detection unit of the trajectory to be evaluated and the collision detection unit of the predicted trajectory corresponding to the same time period in the ST coordinate system overlap, and the collision detection unit is a trajectory within a preset time length; If the collision detection unit of the to-be-evaluated trajectory and the collision detection unit of the predicted trajectory corresponding to the same time period in the ST coordinate system overlap, it is determined that the ego-vehicle has a collision risk; If the collision detection unit of the trajectory to be evaluated and the collision detection unit of the predicted trajectory corresponding to the same time period in the ST coordinate system do not overlap, it is determined that there is no collision risk for the ego vehicle.

3. The method according to claim 2, characterized in that The preset time length is the minimum step update time length. Before determining whether the collision detection unit of the trajectory to be evaluated corresponding to the same time period in the ST coordinate system coincides with the collision detection unit of the predicted trajectory, the method further includes: The minimum step update duration is calculated based on the preset decision cycle and the maximum number of decision updates, where the maximum number of decision updates is the maximum number of times a decision is changed within the preset decision cycle.

4. The method according to claim 3, characterized in that The method further comprises: Determine the driving style according to the number of decision updates, where the number of decision updates is the number of times the decision is changed within the preset decision cycle; Based on the described driving style, driving decisions are adjusted.

5. The method according to claim 4, characterized in that The determining the driving style according to the decision update number includes: If the decision update number is greater than or equal to a first preset number, determining that the driving style is an aggressive type; If the decision update number is less than or equal to a second preset number, determining that the driving style is conservative; Wherein, the first preset number of times is greater than the second preset number of times.

6. The method according to claim 2, characterized in that The determining whether the collision detection unit of the trajectory to be evaluated corresponding to the same time period in the ST coordinate system coincides with the collision detection unit of the predicted trajectory includes: If the distance between the predicted trajectory and the trajectory to be evaluated at the same time is less than or equal to a preset distance threshold, it is determined whether the collision detection unit of the trajectory to be evaluated corresponding to the same time period in the ST coordinate system coincides with the collision detection unit of the predicted trajectory.

7. The method according to claim 6, characterized in that The method further comprises: Determine whether the distance between the predicted trajectory and the trajectory to be evaluated at the same time is less than or equal to a preset distance threshold; If the distance between the predicted trajectory and the trajectory to be evaluated at the same time is greater than a preset distance threshold, it is determined that there is no collision risk for the vehicle.

8. A collision risk assessment device, characterized in that: include: The trajectory acquisition module is used to obtain the trajectory of the vehicle to be evaluated and the predicted trajectories of other vehicles within a preset range; A coordinate conversion module, used for converting the trajectory to be evaluated and the predicted trajectory into the same ST coordinate system, wherein S is the distance traveled by the vehicle in the current lane of the ego vehicle, and T is the time; A collision risk determination module is used to determine whether the vehicle has a collision risk based on the trajectory to be evaluated and the predicted trajectory in the ST coordinate system.

9. An electronic device, characterized in that: include: processor; Memory; And a computer program, wherein the computer program is stored in the memory, and the computer program includes instructions, and when the instructions are executed by the processor, the electronic device executes the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored program, wherein when the program is executed, the device where the computer-readable storage medium is located is controlled to execute the method according to any one of claims 1 to 7.

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