Vehicle hazard event analysis method and device, computer equipment and storage medium

Abstract

The invention relates to a vehicle hazard event analysis method and device, computer equipment and a storage medium. The method belongs to the technical field of intelligent driving and comprises the steps of determining a first obstacle detection condition under the condition that a target vehicle is detected to have a target hazard event; and when the first obstacle detection condition is that no obstacle is detected, determining a camera detection result according to the camera detection information. And determining a vehicle hazard event analysis report of the target vehicle according to a camera detection result and the millimeter wave detection information and the laser radar detection information of the target vehicle. According to the invention, a user can quickly analyze the hazard event based on the vehicle hazard event analysis report and quickly confirm the cause of the hazard event.

Description

Technical Field

[0001] The present application relates to the field of intelligent driving technology, and in particular to a vehicle hazard event analysis method, device, computer equipment and storage medium. Background Art

[0002] With the development of intelligent network technology, the functions of high-level intelligent driving systems are increasing and the complexity of the systems is increasing, which inevitably brings about intelligent driving safety issues.

[0003] When a hazardous event occurs to a vehicle (such as a collision), how to conduct intelligent driving safety analysis of the hazardous event is one of the important issues that urgently need to be solved in the field of intelligent driving. Summary of the invention

[0004] Based on this, it is necessary to provide a vehicle hazard event analysis method, device, computer equipment and storage medium that can effectively improve the engine braking effect in response to the above technical problems.

[0005] In a first aspect, the present application provides a vehicle hazard event analysis method. The method comprises:

[0006] In the case where a target hazard event is detected for the target vehicle, determining a first obstacle detection condition;

[0007] When the first obstacle detection condition is that no obstacle is detected, determining a camera detection result according to the camera detection information;

[0008] Based on the camera detection results, as well as the millimeter wave detection information and lidar detection information of the target vehicle, a vehicle hazard event analysis report of the target vehicle is determined.

[0009] In one embodiment, the camera detection information includes image information;

[0010] Accordingly, according to the camera detection information, the camera detection result is determined, including:

[0011] Determine the second obstacle detection status fed back by the camera;

[0012] When the second obstacle detection condition is that no obstacle is detected, the camera detection result is determined according to the image information.

[0013] In one embodiment, determining the camera detection result according to the image information includes:

[0014] According to the image information, determine the ambient light information, as well as the background color information and motion trajectory information of the obstacle;

[0015] The camera detection result is determined based on the ambient light information, as well as the background color information and motion trajectory information of the obstacle.

[0016] In one embodiment, a vehicle hazard event analysis report of a target vehicle is determined based on the camera detection result, as well as the millimeter wave detection information and the lidar detection information of the target vehicle, including:

[0017] Determine the third obstacle detection status of the millimeter wave radar of the target vehicle according to the millimeter wave detection information of the target vehicle;

[0018] Determine the fourth obstacle detection status of the target vehicle's laser radar according to the target vehicle's laser radar detection information;

[0019] According to the camera detection results, the third obstacle detection situation of the millimeter-wave radar and the fourth obstacle detection situation of the lidar, the vehicle hazard event analysis report of the target vehicle is determined.

[0020] In one embodiment, the method further comprises:

[0021] When a first hazardous event is detected to occur on the target vehicle, obtaining an event type of the first hazardous event;

[0022] When the event type is a high-risk event, the first hazard event is used as a target hazard event; wherein a high-risk event refers to an event that is higher than a risk threshold.

[0023] In one embodiment, obtaining the event type of the first hazard event includes:

[0024] Obtain the driving strategy of the target vehicle; wherein the driving strategy includes single-lane cruising, safe obstacle avoidance, safe parking and automatic lane change;

[0025] An event type of a first hazardous event is determined according to the driving strategy.

[0026] In a second aspect, the present application also provides a vehicle hazard event analysis device. The device comprises:

[0027] A first determination module is used to determine a first obstacle detection situation when a target hazard event is detected for a target vehicle;

[0028] A second determination module is used to determine a camera detection result according to the camera detection information when the first obstacle detection condition is that no obstacle is detected;

[0029] The third determination module is used to determine a vehicle hazard event analysis report of the target vehicle based on the camera detection results, as well as the millimeter wave detection information and lidar detection information of the target vehicle.

[0030] In a third aspect, the present application further provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor implements the following steps when executing the computer program.

[0031] In the case where a target hazard event is detected for the target vehicle, determining a first obstacle detection condition;

[0032] When the first obstacle detection condition is that no obstacle is detected, determining a camera detection result according to the camera detection information;

[0033] Based on the camera detection results, as well as the millimeter wave detection information and lidar detection information of the target vehicle, a vehicle hazard event analysis report of the target vehicle is determined.

[0034] In a fourth aspect, the present application further provides a computer-readable storage medium. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the following steps are implemented:

[0035] In the case where a target hazard event is detected for the target vehicle, determining a first obstacle detection condition;

[0036] When the first obstacle detection condition is that no obstacle is detected, determining a camera detection result according to the camera detection information;

[0037] Based on the camera detection results, as well as the millimeter wave detection information and lidar detection information of the target vehicle, a vehicle hazard event analysis report of the target vehicle is determined.

[0038] In a fifth aspect, the present application further provides a computer program product. The computer program product includes a computer program, and when the computer program is executed by a processor, the following steps are implemented:

[0039] In the case where a target hazard event is detected for the target vehicle, determining a first obstacle detection condition;

[0040] When the first obstacle detection condition is that no obstacle is detected, determining a camera detection result according to the camera detection information;

[0041] Based on the camera detection results, as well as the millimeter wave detection information and lidar detection information of the target vehicle, a vehicle hazard event analysis report of the target vehicle is determined.

[0042] The above-mentioned vehicle hazard event analysis method, device, computer equipment and storage medium determine the first obstacle detection situation when a target hazard event is detected in the target vehicle. When the first obstacle detection situation is that no obstacle is detected, the camera detection result is determined based on the camera detection information. According to the camera detection result, as well as the millimeter wave detection information and the laser radar detection information of the target vehicle, a vehicle hazard event analysis report of the target vehicle is determined. In the case where the target vehicle detects a target hazard event, the present application can determine the camera detection result based on the camera detection information when the first obstacle detection situation is that no obstacle is detected. According to the camera detection result, as well as the millimeter wave detection information and the laser radar detection information of the target vehicle, the vehicle hazard event analysis report of the target vehicle is determined quickly and efficiently, which not only facilitates users to quickly analyze hazard events based on the vehicle hazard event analysis report, but also quickly confirms the cause of the hazard event. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] FIG1 is an application environment diagram of the vehicle hazard event analysis method provided by this embodiment;

[0044] FIG2 is a schematic diagram of a flow chart of a first vehicle hazard event analysis method provided in this embodiment;

[0045] Figure 3 A schematic diagram of a flow chart for determining a target valve clearance of an engine provided in this embodiment;

[0046] Figure 4 A schematic diagram of a flow chart for adjusting the engine valve clearance provided in this embodiment;

[0047] Figure 5 A schematic flow chart of a second vehicle hazard event analysis method provided in this embodiment;

[0048] Figure 6 A structural block diagram of a vehicle hazard event analysis device provided in this embodiment;

[0049] FIG. 7 is a diagram showing the internal structure of the computer device provided in this embodiment. DETAILED DESCRIPTION

[0050] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0051] The vehicle state analysis method provided in the embodiment of the present application can be executed by a vehicle-mounted terminal, or can be executed by a server. That is, the method can be applied to the application environment shown in Figure 1. Taking the application to the server as an example for illustration, the server 104 determines the first obstacle detection situation when it detects that the target vehicle 102 has a target hazard event. When the first obstacle detection situation is that no obstacle is detected, the camera detection result is determined according to the camera detection information. The server 104 determines the vehicle hazard event analysis report of the target vehicle based on the camera detection result, as well as the millimeter wave detection information and lidar detection information of the target vehicle.

[0052] The server 104 may be implemented as an independent server or a server cluster composed of multiple servers. The target vehicle 102 may be a fuel vehicle or a new energy vehicle. The target vehicle in this application is mainly a vehicle with an automatic driving function.

[0053] In one embodiment, as shown in FIG2 , a vehicle hazard event analysis method is provided, and the method is applied to the server in FIG1 as an example for explanation, as shown in FIG2 , including the following steps:

[0054] S201, when a target hazard event is detected for a target vehicle, determining a first obstacle detection situation.

[0055] The target vehicle refers to a vehicle with an automatic driving function in which a target hazard event occurs. A target hazard event refers to a hazard event (e.g., a collision event) that occurs under a preset driving plan. The first obstacle detection condition refers to the detection condition of the target vehicle for an obstacle. The target vehicle determines the first obstacle detection condition based on the environmental information detected by various detection devices.

[0056] As an optional implementation of the embodiment of the present application, the hazard events are classified in advance, and when the target hazard event is detected in the target vehicle, the first obstacle detection situation is determined. Exemplarily, the hazard events are divided into passive hazard events and active hazard events, wherein the passive hazard event refers to the event corresponding to the target vehicle being endangered (for example, being hit). The active hazard event refers to the hazard event initiated by the target vehicle and the main responsibility lies with the target vehicle.

[0057] As an optional implementation of the embodiment of the present application, when a target hazard event is detected in a target vehicle, a log acquisition request is sent to the target vehicle, so that the target vehicle sends a corresponding log to the server based on the log acquisition situation. The corresponding log records the first obstacle detection situation.

[0058] S202, when the first obstacle detection situation is that no obstacle is detected, determining a camera detection result according to camera detection information.

[0059] As an optional implementation of the embodiment of the present application, when the first obstacle detection situation is that no obstacle is detected, the camera detection information is input into the intelligent analysis tool based on the camera detection information, and the intelligent analysis tool outputs the camera detection result.

[0060] As another optional implementation of the embodiment of the present application, in this embodiment, the camera detection information includes image information, on this basis, when the first obstacle detection situation is that no obstacle is detected, the second obstacle detection situation fed back by the camera is determined. When the second obstacle detection situation is that no obstacle is detected, the camera detection result is determined according to the image information. Specifically, the second obstacle detection situation fed back by the camera to the target vehicle is obtained from the target vehicle. The second obstacle detection situation refers to the detection situation of the camera for the obstacle, for example, an obstacle is detected or not detected. The camera detection result refers to the detection result of the camera determined based on the image information.

[0061] Optionally, when the first obstacle detection situation is that an obstacle is detected, a braking system triggering situation of the target vehicle is determined, and based on the braking system triggering situation, a vehicle hazard event analysis report of the target vehicle is determined.

[0062] S203, determining a vehicle hazard event analysis report of the target vehicle based on the camera detection result, as well as the millimeter wave detection information and the lidar detection information of the target vehicle.

[0063] Among them, millimeter wave detection information refers to the detection results of millimeter wave for obstacles. Lidar detection information refers to the detection results of Lidar for obstacles. Vehicle hazard event analysis report refers to the event analysis report of the target hazard event of the target vehicle.

[0064] As an optional implementation of the embodiment of the present application, based on the camera detection results, as well as the millimeter wave detection information and lidar detection information of the target vehicle, an event analysis content is generated, and the event analysis content is added to the initial event analysis report to obtain a vehicle hazard event analysis report of the target vehicle. The initial event analysis report refers to an event analysis report without adding event analysis content.

[0065] As another optional implementation of the embodiment of the present application, the camera detection results, as well as the millimeter wave detection information and the laser radar detection information of the target vehicle are input into the intelligent analysis tool, and the intelligent analysis tool outputs the vehicle hazard event analysis report of the target vehicle. The intelligent analysis report can be, but is not limited to, a neural network model.

[0066] The above-mentioned vehicle hazard event analysis method determines the first obstacle detection situation when a target hazard event is detected in the target vehicle. When the first obstacle detection situation is that no obstacle is detected, the camera detection result is determined based on the camera detection information. According to the camera detection result, as well as the millimeter wave detection information and the lidar detection information of the target vehicle, a vehicle hazard event analysis report of the target vehicle is determined. In the case where the target vehicle detects a target hazard event, the present application can determine the camera detection result based on the camera detection information when the first obstacle detection situation is that no obstacle is detected. According to the camera detection result, as well as the millimeter wave detection information and the lidar detection information of the target vehicle, the vehicle hazard event analysis report of the target vehicle is determined quickly and efficiently, which not only facilitates users to quickly analyze hazard events based on the vehicle hazard event analysis report, but also quickly confirms the cause of the hazard event.

[0067] In one embodiment, in order to more accurately determine the camera detection result, such as Figure 3 As shown, an optional implementation method of determining the camera detection result according to the image information includes:

[0068] S301, determining ambient light information, and background color information and motion trajectory information of the obstacle according to the image information.

[0069] Among them, image information refers to image information captured by the camera, specifically image information containing obstacles. Ambient light information refers to the lighting information of the target vehicle's surrounding environment. Background color information refers to information related to the background color of the obstacle, which is mainly used to determine whether the obstacle is not recognized because the background color is the same or close to the obstacle color. Operation trajectory information refers to the trajectory information of the obstacle, such as whether it is stationary or moving. If it is moving, the corresponding operation trajectory information needs to be analyzed and determined.

[0070] As an optional implementation of the embodiment of the present application, the image information is input into an image analysis tool, and the image analysis tool determines the ambient light information, the background color information and the motion trajectory information of the obstacle. The image analysis tool can be a neural network model, for example, a neural network model with strong image recognition capabilities.

[0071] It should be noted that the image information may be a continuous multi-frame image, and based on the continuous multi-frame image, it is convenient to determine the movement trajectory information of the obstacle.

[0072] S302, determining the camera detection result according to the ambient light information, and the background color information and motion trajectory information of the obstacle.

[0073] As an optional implementation of the embodiment of the present application, the ambient light information, the background color information and the motion trajectory information of the obstacle are input into the analysis tool, and the analysis tool outputs the camera detection result. The analysis tool can be a neural network model, which performs intelligent analysis based on the ambient light information, the background color information and the motion trajectory information of the obstacle, and then outputs the camera detection result. The purpose of the intelligent analysis is to analyze the reason why the camera did not recognize the obstacle.

[0074] Another optional implementation of the embodiment of the present application is to use the ambient light information, as well as the background color information and motion trajectory information of the obstacle as the camera detection result.

[0075] Optionally, based on the present embodiment, an optional implementation method of determining a vehicle hazard event analysis report of a target vehicle according to the camera detection result, and the millimeter wave detection information and the laser radar detection information of the target vehicle includes:

[0076] According to the millimeter wave detection information of the target vehicle, the third obstacle detection situation of the millimeter wave radar of the target vehicle is determined. According to the laser radar detection information of the target vehicle, the fourth obstacle detection situation of the laser radar of the target vehicle is determined. According to the camera detection results, the third obstacle detection situation of the millimeter wave radar and the fourth obstacle detection situation of the laser radar, the vehicle hazard event analysis report of the target vehicle is determined. Among them, the third obstacle detection situation refers to the detection situation of the millimeter wave radar for the obstacle, whether the obstacle is recognized or not. The third obstacle detection situation refers to the detection situation of the laser radar for the obstacle, whether the obstacle is recognized or not.

[0077] In this embodiment, the ambient light information, the background color information and the motion track information of the obstacle are determined based on the image information. According to the ambient light information, the background color information and the motion track information of the obstacle, the camera detection result can be determined more accurately.

[0078] In one embodiment, if Figure 4 As shown, an optional implementation of a vehicle hazard event analysis method includes:

[0079] S401: When a first hazardous event is detected for a target vehicle, an event type of the first hazardous event is obtained.

[0080] The first hazardous event refers to a hazardous event occurring to the target vehicle, such as a collision event.

[0081] Optionally, in this embodiment, when the first hazardous event is detected in the target vehicle, the driving strategy of the target vehicle is obtained; the driving strategy includes single-lane cruising, safe obstacle avoidance, safe parking and automatic lane change. According to the driving strategy, the event type of the first hazardous event is determined.

[0082] It should be noted that, in the present application, when the driving strategy is safe obstacle avoidance or automatic lane change, the event type of the first hazardous event is a high-risk event.

[0083] S402: When the event type is a high-risk event, the first hazard event is used as a target hazard event.

[0084] Among them, high-risk events refer to events that are above the risk threshold.

[0085] In this embodiment, when the target vehicle is detected to have a first hazard event, the event type of the first hazard event is obtained. When the event type is a high-risk event, the first hazard event is used as the target hazard event, thereby improving the accuracy of determining the target hazard event.

[0086] In one embodiment, if Figure 5 As shown, an optional implementation of a vehicle hazard event analysis method includes:

[0087] S501, when a first hazardous event is detected for a target vehicle, a driving strategy of the target vehicle is obtained, wherein the driving strategy includes single-lane cruising, safe obstacle avoidance, safe parking and automatic lane change.

[0088] S502: Determine the event type of the first hazardous event according to the driving strategy.

[0089] S503: When the event type is a high-risk event, the first hazard event is used as a target hazard event, wherein a high-risk event refers to an event that is higher than a risk threshold.

[0090] S504: When a target hazard event is detected for the target vehicle, a first obstacle detection situation is determined.

[0091] S505: When the first obstacle detection condition is that no obstacle is detected, determine a second obstacle detection condition fed back by the camera.

[0092] S506, when the second obstacle detection situation is that no obstacle is detected, determine the ambient light information, and the background color information and motion trajectory information of the obstacle according to the image information fed back by the camera.

[0093] S507, determining the camera detection result according to the ambient light information, and the background color information and motion trajectory information of the obstacle.

[0094] S508: Determine a third obstacle detection condition of the millimeter-wave radar of the target vehicle according to the millimeter-wave detection information of the target vehicle.

[0095] S509: Determine a fourth obstacle detection condition of the laser radar of the target vehicle according to the laser radar detection information of the target vehicle.

[0096] S510, determining a vehicle hazard event analysis report of the target vehicle based on the camera detection result, the third obstacle detection result of the millimeter wave radar, and the fourth obstacle detection result of the laser radar.

[0097] In this embodiment, when a target hazard event is detected in a target vehicle, the first obstacle detection status is determined. When the first obstacle detection status is that no obstacle is detected, the camera detection result is determined based on the camera detection information. Based on the camera detection result, as well as the millimeter wave detection information and the lidar detection information of the target vehicle, a vehicle hazard event analysis report of the target vehicle is determined. In the case where the target vehicle detects a target hazard event, the present application can determine the camera detection result based on the camera detection information when the first obstacle detection status is that no obstacle is detected. Based on the camera detection result, as well as the millimeter wave detection information and the lidar detection information of the target vehicle, the vehicle hazard event analysis report of the target vehicle is determined quickly and efficiently, which not only facilitates users to quickly analyze hazard events based on the vehicle hazard event analysis report, but also quickly confirms the cause of the hazard event.

[0098] Based on the same inventive concept, the embodiment of the present application also provides a vehicle hazard event analysis device for implementing the vehicle hazard event analysis method involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in the embodiment of a vehicle hazard event analysis device provided below can refer to the limitations of the vehicle hazard event analysis method above, and will not be repeated here.

[0099] In one embodiment, if Figure 6 As shown, a vehicle hazard event analysis device 1 is provided, comprising:

[0100] A first determination module 10 is used to determine a first obstacle detection condition when a target hazard event is detected for a target vehicle;

[0101] A second determination module 20 is used to determine a camera detection result according to the camera detection information when the first obstacle detection condition is that no obstacle is detected;

[0102] The third determination module 30 is used to determine a vehicle hazard event analysis report of the target vehicle according to the camera detection result, and the millimeter wave detection information and the laser radar detection information of the target vehicle.

[0103] Based on the device in this embodiment, when a target hazard event is detected in a target vehicle, the first obstacle detection situation is determined. When the first obstacle detection situation is that no obstacle is detected, the camera detection result is determined based on the camera detection information. According to the camera detection result, as well as the millimeter wave detection information and the lidar detection information of the target vehicle, a vehicle hazard event analysis report of the target vehicle is determined. In the case where the target vehicle detects a target hazard event, the present application can determine the camera detection result based on the camera detection information when the first obstacle detection situation is that no obstacle is detected. According to the camera detection result, as well as the millimeter wave detection information and the lidar detection information of the target vehicle, the vehicle hazard event analysis report of the target vehicle is determined quickly and efficiently, which not only facilitates users to quickly analyze hazard events based on the vehicle hazard event analysis report, but also quickly confirms the cause of the hazard event.

[0104] In one embodiment, the camera detection information includes image information;

[0105] Accordingly, Figure 6 The second determining module 20 is further specifically used for:

[0106] Determine the second obstacle detection status fed back by the camera;

[0107] When the second obstacle detection condition is that no obstacle is detected, the camera detection result is determined according to the image information.

[0108] In one embodiment, the Figure 6 The second determining module 20 is further specifically used for:

[0109] According to the image information, determine the ambient light information, as well as the background color information and motion trajectory information of the obstacle;

[0110] The camera detection result is determined based on the ambient light information, as well as the background color information and motion trajectory information of the obstacle.

[0111] In one embodiment, the Figure 6 The third determining module 30 is further specifically used for:

[0112] Determine the third obstacle detection status of the millimeter wave radar of the target vehicle according to the millimeter wave detection information of the target vehicle;

[0113] Determine the fourth obstacle detection status of the target vehicle's laser radar according to the target vehicle's laser radar detection information;

[0114] According to the camera detection results, the third obstacle detection situation of the millimeter-wave radar and the fourth obstacle detection situation of the lidar, the vehicle hazard event analysis report of the target vehicle is determined.

[0115] In one embodiment, the vehicle hazard event analysis device 1 further includes:

[0116] An acquisition module, configured to acquire an event type of the first hazardous event when a first hazardous event is detected to occur on the target vehicle;

[0117] The fourth determination module is used to, when the event type is a high-risk event, use the first hazard event as a target hazard event; wherein the high-risk event refers to an event that is higher than a risk threshold.

[0118] In one embodiment, the acquisition module is further specifically used for:

[0119] Obtain the driving strategy of the target vehicle; wherein the driving strategy includes single-lane cruising, safe obstacle avoidance, safe parking and automatic lane change;

[0120] An event type of a first hazardous event is determined according to the driving strategy.

[0121] Each module in the above-mentioned vehicle hazard event analysis device can be implemented in whole or in part by software, hardware, or a combination thereof. Each of the above-mentioned modules can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute the operations corresponding to each of the above modules.

[0122] In one embodiment, a computer device is provided, and its internal structure diagram can be shown in FIG7. The computer device includes a processor, a memory, an input / output interface, a communication interface, a display unit, and an input device. The processor, the memory, and the input / output interface are connected through a system bus, and the communication interface, the display unit, and the input device are connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be implemented through WIFI, a mobile cellular network, NFC (near field communication) or other technologies. When the computer program is executed by the processor, a vehicle hazard event analysis method is implemented. The display unit of the computer device is used to form a visually visible picture, which can be a display screen, a projection device, or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad set on the computer device shell, or an external keyboard, touchpad or mouse.

[0123] Those skilled in the art will understand that the structure shown in FIG. 7 is merely a block diagram of a partial structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different arrangement of components.

[0124] In one embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the following steps are implemented:

[0125] In the case where a target hazard event is detected for the target vehicle, determining a first obstacle detection condition;

[0126] When the first obstacle detection condition is that no obstacle is detected, determining a camera detection result according to the camera detection information;

[0127] Based on the camera detection results, as well as the millimeter wave detection information and lidar detection information of the target vehicle, a vehicle hazard event analysis report of the target vehicle is determined.

[0128] In one embodiment, when the processor executes the computer program, the following steps are further implemented: the camera detection information includes image information;

[0129] Accordingly, according to the camera detection information, the camera detection result is determined, including:

[0130] Determine the second obstacle detection status fed back by the camera;

[0131] When the second obstacle detection condition is that no obstacle is detected, the camera detection result is determined according to the image information.

[0132] In one embodiment, when the processor executes the computer program, the following steps are further implemented: determining the camera detection result according to the image information, including:

[0133] According to the image information, determine the ambient light information, as well as the background color information and motion trajectory information of the obstacle;

[0134] The camera detection result is determined based on the ambient light information, as well as the background color information and motion trajectory information of the obstacle.

[0135] In one embodiment, when the processor executes the computer program, the following steps are further implemented: determining a vehicle hazard event analysis report of the target vehicle according to the camera detection result, and the millimeter wave detection information and the laser radar detection information of the target vehicle, including:

[0136] Determine the third obstacle detection status of the millimeter wave radar of the target vehicle according to the millimeter wave detection information of the target vehicle;

[0137] Determine the fourth obstacle detection status of the target vehicle's laser radar according to the target vehicle's laser radar detection information;

[0138] According to the camera detection results, the third obstacle detection situation of the millimeter-wave radar and the fourth obstacle detection situation of the lidar, the vehicle hazard event analysis report of the target vehicle is determined.

[0139] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0140] When a first hazardous event is detected to occur on the target vehicle, obtaining an event type of the first hazardous event;

[0141] When the event type is a high-risk event, the first hazard event is used as a target hazard event; wherein a high-risk event refers to an event that is higher than a risk threshold.

[0142] In one embodiment, when the processor executes the computer program, the following steps are further implemented: obtaining the event type of the first hazard event, including:

[0143] Obtain the driving strategy of the target vehicle; wherein the driving strategy includes single-lane cruising, safe obstacle avoidance, safe parking and automatic lane change;

[0144] An event type of a first hazardous event is determined according to the driving strategy.

[0145] In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

[0146] In the case where a target hazard event is detected for the target vehicle, determining a first obstacle detection condition;

[0147] When the first obstacle detection condition is that no obstacle is detected, determining a camera detection result according to the camera detection information;

[0148] Based on the camera detection results, as well as the millimeter wave detection information and lidar detection information of the target vehicle, a vehicle hazard event analysis report of the target vehicle is determined.

[0149] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented: the camera detection information includes image information;

[0150] Accordingly, according to the camera detection information, the camera detection result is determined, including:

[0151] Determine the second obstacle detection status fed back by the camera;

[0152] When the second obstacle detection condition is that no obstacle is detected, the camera detection result is determined according to the image information.

[0153] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented: determining the camera detection result according to the image information, including:

[0154] According to the image information, determine the ambient light information, as well as the background color information and motion trajectory information of the obstacle;

[0155] The camera detection result is determined based on the ambient light information, as well as the background color information and motion trajectory information of the obstacle.

[0156] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented: determining a vehicle hazard event analysis report of the target vehicle according to the camera detection result, and the millimeter wave detection information and the laser radar detection information of the target vehicle, including:

[0157] Determine the third obstacle detection status of the millimeter wave radar of the target vehicle according to the millimeter wave detection information of the target vehicle;

[0158] Determine the fourth obstacle detection status of the target vehicle's laser radar according to the target vehicle's laser radar detection information;

[0159] According to the camera detection results, the third obstacle detection situation of the millimeter-wave radar and the fourth obstacle detection situation of the lidar, the vehicle hazard event analysis report of the target vehicle is determined.

[0160] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0161] When a first hazardous event is detected to occur on the target vehicle, obtaining an event type of the first hazardous event;

[0162] When the event type is a high-risk event, the first hazard event is used as a target hazard event; wherein a high-risk event refers to an event that is higher than a risk threshold.

[0163] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented: obtaining the event type of the first hazard event, including:

[0164] Obtain the driving strategy of the target vehicle; wherein the driving strategy includes single-lane cruising, safe obstacle avoidance, safe parking and automatic lane change;

[0165] An event type of a first hazardous event is determined according to the driving strategy.

[0166] In one embodiment, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements the following steps:

[0167] In the case where a target hazard event is detected for the target vehicle, determining a first obstacle detection condition;

[0168] When the first obstacle detection condition is that no obstacle is detected, determining a camera detection result according to the camera detection information;

[0169] Based on the camera detection results, as well as the millimeter wave detection information and lidar detection information of the target vehicle, a vehicle hazard event analysis report of the target vehicle is determined.

[0170] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented: the camera detection information includes image information;

[0171] Accordingly, according to the camera detection information, the camera detection result is determined, including:

[0172] Determine the second obstacle detection status fed back by the camera;

[0173] When the second obstacle detection condition is that no obstacle is detected, the camera detection result is determined according to the image information.

[0174] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented: determining the camera detection result according to the image information, including:

[0175] According to the image information, determine the ambient light information, as well as the background color information and motion trajectory information of the obstacle;

[0176] The camera detection result is determined based on the ambient light information, as well as the background color information and motion trajectory information of the obstacle.

[0177] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented: determining a vehicle hazard event analysis report of the target vehicle according to the camera detection result, and the millimeter wave detection information and the laser radar detection information of the target vehicle, including:

[0178] Determine the third obstacle detection status of the millimeter wave radar of the target vehicle according to the millimeter wave detection information of the target vehicle;

[0179] Determine the fourth obstacle detection status of the target vehicle's laser radar according to the target vehicle's laser radar detection information;

[0180] According to the camera detection results, the third obstacle detection situation of the millimeter-wave radar and the fourth obstacle detection situation of the lidar, the vehicle hazard event analysis report of the target vehicle is determined.

[0181] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0182] When a first hazardous event is detected to occur on the target vehicle, obtaining an event type of the first hazardous event;

[0183] When the event type is a high-risk event, the first hazard event is used as a target hazard event; wherein a high-risk event refers to an event that is higher than a risk threshold.

[0184] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented: obtaining the event type of the first hazard event, including:

[0185] Obtain the driving strategy of the target vehicle; wherein the driving strategy includes single-lane cruising, safe obstacle avoidance, safe parking and automatic lane change;

[0186] An event type of a first hazardous event is determined according to the driving strategy.

[0187] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0188] The technical features of the above embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0189] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be construed as limiting the scope of the present application. It should be noted that, for a person of ordinary skill in the art, several modifications and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A vehicle hazard event analysis method, characterized in that: The method comprises: In the case where a target hazard event is detected for the target vehicle, determining a first obstacle detection condition; When the first obstacle detection condition is that no obstacle is detected, determining a camera detection result according to the camera detection information; A vehicle hazard event analysis report of the target vehicle is determined based on the camera detection result, as well as the millimeter wave detection information and the lidar detection information of the target vehicle.

2. The method according to claim 1, characterized in that The camera detection information includes image information; Correspondingly, determining the camera detection result according to the camera detection information includes: Determine the second obstacle detection status fed back by the camera; When the second obstacle detection condition is that no obstacle is detected, the camera detection result is determined according to the image information.

3. The method according to claim 2, characterized in that The step of determining the camera detection result according to the image information includes: Determine the ambient light information, and the background color information and motion trajectory information of the obstacle according to the image information; The camera detection result is determined according to the ambient light information, and the background color information and motion trajectory information of the obstacle.

4. The method according to claim 3, characterized in that Determining a vehicle hazard event analysis report of the target vehicle based on the camera detection result, and the millimeter wave detection information and the laser radar detection information of the target vehicle includes: Determining a third obstacle detection condition of the millimeter-wave radar of the target vehicle according to the millimeter-wave detection information of the target vehicle; Determine, according to the laser radar detection information of the target vehicle, a fourth obstacle detection condition of the laser radar of the target vehicle; A vehicle hazard event analysis report of the target vehicle is determined based on the camera detection result, the third obstacle detection status of the millimeter wave radar, and the fourth obstacle detection status of the laser radar.

5. The method according to claim 1, characterized in that The method further comprises: When a first hazardous event is detected to occur to the target vehicle, obtaining an event type of the first hazardous event; In the case where the event type is a high-risk event, the first hazard event is used as the target hazard event; wherein the high-risk event refers to an event that is higher than a risk threshold.

6. The method according to claim 5, characterized in that The obtaining of the event type of the first hazardous event includes: Acquire the driving strategy of the target vehicle; wherein the driving strategy includes single-lane cruising, safe obstacle avoidance, safe parking and automatic lane change; An event type of the first hazardous event is determined according to the driving strategy.

7. A vehicle hazard event analysis device, characterized in that: The device comprises: A first determination module is used to determine a first obstacle detection situation when a target hazard event is detected for a target vehicle; A second determination module, configured to determine a camera detection result according to camera detection information when the first obstacle detection condition is that no obstacle is detected; The third determination module is used to determine a vehicle hazard event analysis report of the target vehicle based on the camera detection result, and the millimeter wave detection information and lidar detection information of the target vehicle.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the vehicle hazard event analysis method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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