Vehicle prompt information processing method and related device and medium

Abstract

The embodiment of the application discloses a vehicle prompt information processing method based on road abnormal state recognition, and related devices and media, which comprises the following steps: acquiring road surface information in the driving process; determining the road condition of the non-motor vehicle lane adjacent to the motor vehicle lane where the vehicle is located according to the road surface information; determining the road condition of the other motor vehicle lane in the same direction as the motor vehicle lane according to the road surface information; if the non-motor vehicle lane appears a preset first abnormal situation, and the other motor vehicle lane appears a preset second abnormal situation, outputting first prompt information; if the non-motor vehicle lane appears a preset first abnormal situation, and the other motor vehicle lane does not appear a preset second abnormal situation, outputting second prompt information. The embodiment of the application can monitor, accurately identify and adjust the driving strategy in real time for the safety hidden danger of the adjacent non-motor vehicle lane driving scene, and improve the real-time performance, accuracy and intelligence of the vehicle information processing based on the road abnormal situation.

Description

Technical Field

[0001] This application is applied to the field of general data processing technology in the Internet industry, and in particular relates to a method, device and medium for processing vehicle prompt information based on road abnormality identification. Background Technology

[0002] Intelligent driving technology can assist vehicles in driving at safe speeds and maintaining safe following distances in motor vehicle lanes. However, in driving scenarios where non-motorized vehicles frequently enter the motor vehicle lane adjacent to the vehicle's lane, there is often a safety hazard. Current intelligent driving technology cannot accurately identify this safety hazard, and therefore the vehicle cannot adjust its driving strategy in a timely manner to avoid potential driving risks.

[0003] Therefore, how to accurately identify safety hazards in non-motorized vehicle lane driving scenarios and implement effective driving strategies during vehicle operation is a technical problem that those skilled in the art are studying. Summary of the Invention

[0004] This application discloses a method and apparatus for processing vehicle-based road anomaly status alerts, aiming to enable the vehicle's intelligent driving domain controller to monitor, accurately identify, and alert drivers to adjust driving strategies in real time to avoid potential driving risks in adjacent non-motorized vehicle lane driving scenarios, thereby improving the real-time performance, accuracy, and intelligence of vehicle-based information processing based on road anomalies.

[0005] In a first aspect, embodiments of this application provide a method for processing vehicle-based road anomaly state recognition prompt information, applied to the intelligent driving domain controller of a vehicle's domain controller system. The method includes:

[0006] The vehicle acquires road surface information during its journey, wherein the road surface information is used to represent the position information and / or motion state of objects in each lane of the road segment in which the vehicle is located.

[0007] The road conditions of the non-motorized lane adjacent to the motorized lane where the vehicle is located are determined based on the road surface information;

[0008] The road conditions of other motor vehicle lanes traveling in the same direction as the motor vehicle lane are determined based on the road surface information.

[0009] If a preset first abnormal situation occurs in the non-motorized vehicle lane and a preset second abnormal situation occurs in the other motorized vehicle lane, a first prompt message is output. The first abnormal situation is used to indicate that there is a safety hazard of non-motorized vehicles occupying the motorized vehicle lane where the vehicle is located in the non-motorized vehicle lane. The second abnormal situation is used to indicate that the other motorized vehicle lane does not meet the conditions for allowing the vehicle to change lanes. The first prompt message is used to indicate the first abnormal situation in the non-motorized vehicle lane and to prompt the vehicle to slow down.

[0010] If a preset first abnormal situation occurs in the non-motorized vehicle lane, and no preset second abnormal situation occurs in the other motorized vehicle lanes, a second prompt message is output, wherein the second prompt message is used to indicate the first abnormal situation in the non-motorized vehicle lane and to prompt lane changing.

[0011] In the above method, if it is determined that the adjacent non-motorized vehicle lane is abnormal, i.e. there is a safety hazard of non-motorized vehicles entering the motorized vehicle lane, and if the vehicle determines that the other motorized vehicle lane in the same direction is also abnormal, then the first prompt message is output to indicate the abnormality and to slow down; if it is determined that the other motorized vehicle lane in the same direction is not abnormal and the conditions for changing lanes are met, then the second prompt message is output to indicate the abnormality and to change lanes.

[0012] In other words, in the above method, the vehicle monitors the road conditions of adjacent non-motorized vehicle lanes in real time through the intelligent driving domain controller. After accurately identifying a safety hazard of non-motorized vehicles entering the motorized vehicle lane, it can output corresponding prompts based on the road conditions of the motorized vehicle lane in the same direction. This is used to alert the driver to the abnormal situation and suggest that the driver adjust their driving strategy accordingly. Therefore, the above method can improve the real-time performance, accuracy, and intelligence of the vehicle's information processing based on abnormal road conditions.

[0013] In conjunction with the first aspect, in one possible implementation, the method further includes:

[0014] The system receives driving parameters from the server when other vehicles pass through the lane where the vehicle is located within a preset time period.

[0015] Based on the driving parameters of the other vehicles, determine the driving behavior of the other vehicles within the preset time period;

[0016] The first and second prompt messages are also used to prompt the driving behavior of other vehicles within the preset time period.

[0017] In the above method, the vehicle interacts with other vehicles through the server, combining the driving behavior of other vehicles when passing through the same motor vehicle lane within a preset time period with the road conditions of the adjacent non-motorized vehicle lane and the same-direction motor vehicle lane to determine the corresponding assisted driving strategy. In other words, based on the determined road conditions and referring to the driving behavior of other vehicles within a preset time period, the vehicle can more accurately identify safety hazards of non-motorized vehicles entering the motor vehicle lane and output relevant prompts, further improving the vehicle's driving safety.

[0018] Optionally, the driving parameter can be one or more of the following: location information, vehicle speed, distance to other vehicles, and lighting information; the driving behavior can be deceleration, emergency braking, or lane change.

[0019] In conjunction with the first aspect, or any of the above-described possible implementations of the first aspect, in another possible implementation, the road surface information includes image information; the step of determining the road conditions of the non-motorized lane adjacent to the motorized lane where the vehicle is located based on the road surface information includes:

[0020] If the image information is analyzed, and at least one of the following conditions is met, the non-motorized vehicle lane is determined to be the first abnormal situation:

[0021] The image information contains preset construction signs or road closure signs;

[0022] The number of non-motorized vehicles in the image information exceeds a first threshold.

[0023] The distance between non-motorized vehicles in the image information is lower than the second threshold.

[0024] In the above method, the vehicle sets corresponding preset conditions for multiple factors affecting non-motorized vehicles entering the motorized vehicle lane, such as lane closure and lane congestion. Then, it determines whether the non-motorized vehicle lane is abnormal by comparing key information in the image with the preset conditions. Therefore, the above method can accurately identify safety hazards of non-motorized vehicles entering the motorized vehicle lane.

[0025] Optionally, the image information can be captured by the vehicle's onboard camera or by the vehicle's dashcam.

[0026] In conjunction with the first aspect, or any of the above-described possible implementations of the first aspect, in another possible implementation, determining the road conditions of other lanes traveling in the same direction as the lane based on the road surface information includes:

[0027] If the image information is analyzed, and at least one of the following conditions is met, then the other vehicle lane is determined to be a second abnormal situation:

[0028] The image information contains preset construction signs or road closure signs;

[0029] The image information contains a preset lane change prohibition sign;

[0030] The number of motor vehicles in the image information exceeds a third threshold.

[0031] The distance between motor vehicles in the image information is lower than the fourth threshold.

[0032] In the above method, the vehicle sets corresponding preset conditions for multiple factors affecting its lane change to the same-direction traffic lane, such as lane closure, lane changing prohibition, and lane congestion. Then, by comparing key information in the image with the preset conditions, it determines whether the same-direction traffic lane meets the conditions for lane changing. Therefore, the above method can enhance the effectiveness of the assisted driving strategy.

[0033] In conjunction with the first aspect, or any of the above possible implementations of the first aspect, in yet another possible implementation, the road surface information includes map information; the step of determining the road conditions of the non-motorized lane adjacent to the motorized lane where the vehicle is located based on the road surface information includes:

[0034] If the map information is analyzed and one or more of the following are found on the non-motorized lane within a preset range centered on the vehicle: a construction sign, a road closure sign, and a congestion sign, then the non-motorized lane is determined to be the first abnormal situation.

[0035] In the above method, the vehicle sets corresponding preset conditions for multiple factors affecting non-motorized vehicles entering the motorized vehicle lane, such as lane closure and lane congestion. Then, it determines whether the non-motorized vehicle lane is abnormal by comparing key information in the image with the preset conditions. Therefore, the above method can accurately identify safety hazards of non-motorized vehicles entering the motorized vehicle lane.

[0036] In conjunction with the first aspect, or any of the above possible implementations of the first aspect, in yet another possible implementation, determining the road conditions of other lanes traveling in the same direction as the lane based on the road surface information includes:

[0037] If the map information is analyzed and one or more of the following are found on other motor vehicle lanes within a preset range centered on the vehicle: a construction sign, a road closure sign, a congestion sign, and a no-lane-change sign, then the other motor vehicle lanes are determined to be the second abnormal situation.

[0038] In the above method, the vehicle sets corresponding preset conditions for multiple factors affecting lane changes to the same-direction traffic lane, such as lane closure, lane changing prohibition, and lane congestion. Then, by comparing key information in the map with the preset conditions, it determines whether the same-direction traffic lane is suitable for lane changing. Therefore, this method enhances the effectiveness of the assisted driving strategy.

[0039] In conjunction with the first aspect, or any of the possible implementations of the first aspect described above, in yet another possible implementation, before collecting road surface information during the driving process, the method further includes:

[0040] The distance information between the vehicle and surrounding vehicles is obtained through sensors, and the surrounding vehicles include vehicles within the coverage area of ​​the sensor device;

[0041] A driving strategy for the vehicle is generated based on the vehicle distance information;

[0042] If no preset first abnormal situation occurs in the non-motorized lane, a third prompt message is output, wherein the third prompt message is used to prompt driving according to the driving strategy.

[0043] In the above method, the vehicle acquires distance information to surrounding vehicles via sensors during operation, and then determines a corresponding assisted driving strategy based on this distance information. For example, if the distance is lower than a preset threshold, the vehicle will output a warning message to slow down. If the vehicle determines that there is no abnormality in the non-motorized vehicle lane, i.e., the probability of a non-motorized vehicle entering the motorized vehicle lane is very low, then the assisted driving strategy is maintained. Therefore, the above method can ensure the driving safety of the vehicle under normal conditions.

[0044] Optionally, the sensor can be an infrared detector, lidar, millimeter-wave radar, or ultrasonic radar.

[0045] In conjunction with the first aspect, or any of the above possible implementations of the first aspect, in yet another possible implementation, before outputting the second prompt information, the method further includes:

[0046] Select at least two target roads from the video information of the other roads. The two target roads are both roads where the first abnormal situation occurs in the target non-motorized vehicle lane and the preset second abnormal situation does not occur in the target motorized vehicle lane. The target motorized vehicle lane and the target non-motorized vehicle lane are separated by one motorized vehicle lane.

[0047] Calculate the duration of the first abnormal situation occurring in the target non-motorized vehicle lane and the second abnormal situation not occurring in the target motorized vehicle lane in the video information of the target road, and divide the video information of the target road during the duration into N sub-video information on an average basis, where N is an integer greater than 1;

[0048] Calculate the vehicle traffic efficiency on the target motor vehicle lane in each of the N sub-video information;

[0049] Determine the driving behavior of multiple first vehicles in the target motor vehicle lane from the sub-video information with the highest vehicle traffic efficiency;

[0050] Determine the driving behavior of multiple second vehicles in the target motor vehicle lane from the sub-video information with the lowest vehicle traffic efficiency;

[0051] The proportion of vehicles whose driving behavior includes changing lanes is determined to be greater than a fifth threshold among the plurality of first vehicles, and the proportion of vehicles whose driving behavior includes changing lanes is less than the fifth threshold among the plurality of second vehicles.

[0052] In the above method, the vehicle can, based on the road conditions of the road where the vehicle is located, refer to the driving behavior of vehicles on other roads with the same road conditions as the road where the vehicle is located, more accurately identify the safety hazards of non-motorized vehicles entering the motorized vehicle lane on the road where the vehicle is located, and output lane change prompt information, thereby further improving the driving safety of the vehicle.

[0053] Secondly, embodiments of this application provide a vehicle intelligent driving domain control device, the device comprising:

[0054] The acquisition unit is used to collect road surface information during the driving process, wherein the road surface information is used to represent the position information and / or motion state of objects in each lane of the road segment where the vehicle is located;

[0055] The first determining unit is used to determine the road conditions of the non-motorized lane adjacent to the motorized lane where the vehicle is located based on the road surface information.

[0056] The second determining unit is used to determine the road conditions of other motor vehicle lanes traveling in the same direction as the motor vehicle lane based on the road surface information;

[0057] The first output unit is configured to output a first prompt message if a preset first abnormal situation occurs in the non-motorized vehicle lane and a preset second abnormal situation occurs in the other motorized vehicle lanes. The first abnormal situation is used to indicate that there is a safety hazard of non-motorized vehicles occupying the motorized vehicle lane where the vehicle is located in the non-motorized vehicle lane. The second abnormal situation is used to indicate that the other motorized vehicle lanes do not meet the conditions for allowing the vehicle to change lanes. The first prompt message is used to indicate the first abnormal situation in the non-motorized vehicle lane and to prompt the vehicle to slow down.

[0058] The second output unit is used to output a second prompt message if a preset first abnormal situation occurs in the non-motorized vehicle lane and no preset second abnormal situation occurs in the other motorized vehicle lanes. The second prompt message is used to prompt the first abnormal situation in the non-motorized vehicle lane and to prompt lane changing.

[0059] In conjunction with the second aspect, in one possible implementation, the device further includes:

[0060] A receiving unit is used to receive driving parameters sent by a server when other vehicles pass through the motor vehicle lane where the vehicle is located within a preset time period, wherein the server is used to collect driving parameters of all vehicles connected to the server.

[0061] The third determining unit is used to determine the driving behavior of the other vehicles within the preset time period based on the driving parameters of the other vehicles.

[0062] The first and second prompt messages are also used to prompt the driving behavior of other vehicles within the preset time period.

[0063] In conjunction with the second aspect, or any of the possible implementations of the second aspect described above, in another possible implementation, the road surface information includes image information; in determining the road conditions of the non-motorized lane adjacent to the motorized lane where the vehicle is located based on the road surface information, the first determining unit is specifically used for:

[0064] If the image information is analyzed, and at least one of the following conditions is met, the non-motorized vehicle lane is determined to be the first abnormal situation:

[0065] The image information contains preset construction signs or road closure signs;

[0066] The number of non-motorized vehicles in the image information exceeds a first threshold.

[0067] The distance between non-motorized vehicles in the image information is lower than the second threshold.

[0068] In conjunction with the second aspect, or any of the possible implementations of the second aspect described above, in yet another possible implementation, regarding the determination of the road conditions of other lanes traveling in the same direction as the lane based on the road surface information, the second determining unit is specifically used for:

[0069] If the image information is analyzed, and at least one of the following conditions is met, then the other vehicle lane is determined to be a second abnormal situation:

[0070] The image information contains preset construction signs or road closure signs;

[0071] The image information contains a preset lane change prohibition sign;

[0072] The number of motor vehicles in the image information exceeds a third threshold.

[0073] The distance between motor vehicles in the image information is lower than the fourth threshold.

[0074] In conjunction with the second aspect, or any of the above possible implementations of the second aspect, in yet another possible implementation, the road surface information includes map information; regarding the determination of the road conditions of the non-motorized lane adjacent to the motorized lane where the vehicle is located based on the road surface information, the first determining unit is specifically used for:

[0075] If the map information is analyzed and one or more of the following are found on the non-motorized lane within a preset range centered on the vehicle: a construction sign, a road closure sign, and a congestion sign, then the non-motorized lane is determined to be the first abnormal situation.

[0076] In conjunction with the second aspect, or any of the possible implementations of the second aspect described above, in yet another possible implementation, regarding the determination of the road conditions of other lanes traveling in the same direction as the lane based on the road surface information, the second determining unit is specifically used for:

[0077] If the map information is analyzed and one or more of the following are found on other motor vehicle lanes within a preset range centered on the vehicle: a construction sign, a road closure sign, a congestion sign, and a no-lane-change sign, then the other motor vehicle lanes are determined to be the second abnormal situation.

[0078] In conjunction with the second aspect, or any of the possible implementations of the second aspect described above, in yet another possible implementation, before collecting road surface information during the driving process, the device further includes:

[0079] A receiving unit is used to acquire vehicle distance information between the vehicle and surrounding vehicles through sensors, wherein the surrounding vehicles include vehicles within the coverage area of ​​the sensor device;

[0080] An analysis unit is used to generate a driving strategy for the vehicle based on the vehicle distance information;

[0081] The third output unit is used to output a third prompt message if the non-motorized lane does not experience a preset first abnormal situation, wherein the third prompt message is used to prompt the driver to drive according to the driving strategy.

[0082] Optionally, the sensor can be an infrared detector, lidar, millimeter-wave radar, or ultrasonic radar.

[0083] In conjunction with the second aspect, or any of the possible implementations of the second aspect described above, in another possible implementation, before outputting the second prompt information, the device further includes:

[0084] The selection unit is used to select video information of at least two target roads from the video information of the other roads. The two target roads are both roads where the first abnormal situation occurs in the target non-motorized vehicle lane and the preset second abnormal situation does not occur in the target motorized vehicle lane. The target motorized vehicle lane and the target non-motorized vehicle lane are separated by one motorized vehicle lane.

[0085] A segmentation unit is used to calculate the duration of the first abnormal situation occurring in the target non-motorized vehicle lane and the target motorized vehicle lane not experiencing a preset second abnormal situation in the video information of the target road, and to divide the video information of the target road during the duration into N sub-video information on an average basis, where N is an integer greater than 1;

[0086] The calculation unit is used to calculate the vehicle traffic efficiency on the target motor vehicle lane in the N sub-video information respectively;

[0087] The fourth determining unit is used to determine the driving behavior of multiple first vehicles in the target motor vehicle lane in the sub-video information with the highest vehicle traffic efficiency;

[0088] The fifth determining unit is used to determine the driving behavior of multiple second vehicles in the target motor vehicle lane in the sub-video information with the lowest vehicle traffic efficiency;

[0089] The sixth determining unit determines that the proportion of vehicles whose driving behavior includes changing lanes among the plurality of first vehicles is greater than a fifth threshold, and the proportion of vehicles whose driving behavior includes changing lanes among the plurality of second vehicles is less than the fifth threshold.

[0090] Thirdly, embodiments of this application provide a vehicle intelligent driving domain controller, which includes a processor, a memory, and a communication interface. The communication interface is used to perform receiving and / or sending operations under the control of the processor. The memory is used to store a computer program, and the processor is used to call the computer program to implement the method described in the first aspect or any possible implementation of the first aspect.

[0091] Fourthly, embodiments of this application provide a vehicle including an intelligent driving domain controller for implementing the methods described in the first aspect or any possible implementation of the first aspect.

[0092] Fifthly, embodiments of this application provide a computer-readable storage medium storing a computer program that, when executed on a processor, implements the method described in the first aspect or any possible implementation thereof. The beneficial effects of the technical methods provided in the second to fifth aspects of this application can be referred to the beneficial effects of the technical solution in the first aspect, and will not be repeated here. Attached Figure Description

[0093] The accompanying drawings used in the description of the embodiments of this application will be briefly introduced below.

[0094] Figure 1A This is a schematic diagram of a scenario for a vehicle-based road anomaly state recognition prompt information processing method provided in an embodiment of this application;

[0095] Figure 1B This is a schematic diagram of the structure of a vehicle domain controller system provided in an embodiment of this application;

[0096] Figure 2 This is a flowchart illustrating a method for processing vehicle alert information based on road anomaly identification, as provided in an embodiment of this application.

[0097] Figure 3 This is a schematic diagram of a scenario where a vehicle collects road surface information, provided in an embodiment of this application.

[0098] Figure 4 This is a schematic diagram of a scenario where a vehicle outputs a first prompt message, as provided in an embodiment of this application.

[0099] Figure 5 This is a schematic diagram of a scenario where a vehicle outputs a second prompt message, as provided in an embodiment of this application.

[0100] Figure 6 This is a schematic diagram of a scenario for a vehicle to obtain distance information, provided in an embodiment of this application.

[0101] Figure 7This is a schematic diagram of the structure of a vehicle intelligent driving domain control device 70 provided in an embodiment of this application;

[0102] Figure 8 This is a schematic diagram of the structure of a vehicle intelligent driving domain controller 80 provided in an embodiment of this application. Detailed Implementation

[0103] The embodiments of this application will now be described in detail with reference to the accompanying drawings.

[0104] Please see Figure 1A , Figure 1A This is a schematic diagram illustrating a scenario for vehicle-based road anomaly identification and alert processing according to an embodiment of this application. The scenario includes a target vehicle 101, motor vehicle lanes 102-103, and a non-motor vehicle lane 104. The number of vehicles is not strictly limited in this application. Figure 1A The embodiments shown are merely examples.

[0105] The target vehicle 101 is traveling in the motor vehicle lane 102. The motor vehicle lane 103 is the adjacent lane in the same direction to the left of the motor vehicle lane 102. The non-motor vehicle lane 104 is the adjacent non-motor vehicle lane to the right of the motor vehicle lane 102.

[0106] The target vehicle 101 can analyze road conditions through the vehicle domain controller system and output prompts to assist the driver in driving the vehicle. It should be noted that the type of the target vehicle is not strictly limited in this application embodiment. Optionally, the target vehicle 101 can be a car, motorcycle, agricultural transport vehicle, tractor, or trailer; when the target vehicle 101 is a car, it can be a sedan, SUV, truck, bus, or van.

[0107] For better understanding, please refer to Figure 1B , Figure 1B This is a schematic diagram of a vehicle domain controller system provided in an embodiment of this application. The vehicle domain control system 105 can be a control system composed of a powertrain domain controller 106, a chassis domain controller 107, a body domain controller 108, a smart cockpit domain controller 109, and a smart driving domain controller 110. The domain controllers can interact with each other. Each domain controller is a control component integrating multiple electronic control units, capable of receiving information sent by functional devices in the target vehicle and controlling those devices to perform related operations.

[0108] The intelligent driving domain controller 110 is used to receive road information collected by the acquisition device of the target vehicle 101 during its driving process, analyze road conditions, and control the output device of the target vehicle 101 to output prompts related to road conditions. Optionally, the road information can be video information or map information, the acquisition device can be an in-vehicle camera, dashcam, or navigation device in the target vehicle 101, and the output device can be a voice device such as a car audio system or a display device such as a center console screen.

[0109] Specifically, during driving, the intelligent driving domain controller 110 in the target vehicle 101 first acquires road surface information about the motor vehicle lane 103 and the non-motor vehicle lane 104 collected by the acquisition device, and then determines the road conditions of the motor vehicle lane 103 and the non-motor vehicle lane 104 respectively. Optionally, the road conditions of the motor vehicle lane 103 can be the normal conditions preset by the intelligent driving domain controller 110 (such as normal lane traffic) or the abnormal conditions preset by the intelligent driving domain controller 110 (such as lane closure, lane congestion, or lane changing prohibited); the road conditions of the non-motor vehicle lane 104 can be the normal conditions preset by the intelligent driving domain controller 110 (such as normal lane traffic) or the abnormal conditions preset by the intelligent driving domain controller 110 (such as lane closure or lane congestion).

[0110] If the road conditions of the non-motorized vehicle lane 104 are determined to be abnormal, i.e., there is a safety hazard of non-motorized vehicles entering the motorized vehicle lane, the intelligent driving domain controller 110 will output a first prompt message to indicate the abnormality and slow down if it determines that the road conditions of the motorized vehicle lane 103 are also abnormal; if it determines that the motorized vehicle lane 103 is not abnormal and has the conditions for changing lanes, the control output device will output a second prompt message to indicate the abnormality and change lanes.

[0111] Figure 1A In the scenario shown, the target vehicle can monitor the road conditions of adjacent non-motorized vehicle lanes in real time through the intelligent driving domain controller. In response to the safety hazards of non-motorized vehicles entering the motorized vehicle lane where it is located, the vehicle outputs corresponding prompt information based on the road conditions of the adjacent motorized vehicle lanes in the same direction. This information is used to alert the driver to abnormal situations and suggest that the driver take appropriate driving actions to avoid potential driving risks.

[0112] Please see Figure 2 , Figure 2 This is a flowchart illustrating a method for processing vehicle-based road anomaly state identification prompts according to an embodiment of this application. This method can be based on... Figure 1A The method, as shown in the example, includes, but is not limited to, the following steps:

[0113] Step S201: The intelligent driving domain controller acquires road information during the driving process.

[0114] Specifically, the intelligent driving domain controller can be Figure 1B The intelligent driving domain controller 110 in the corresponding embodiment can also be other controllers, used to assist the target vehicle in executing assisted driving strategies according to road conditions. The road information includes the road information of the non-motorized vehicle lane adjacent to the motorized vehicle lane where the target vehicle is located, as well as the road information of other motorized vehicle lanes in the same direction as the motorized vehicle lane where the target vehicle is located.

[0115] The road surface information can be either image information or map information. When the road surface information is image information, it can be collected by the vehicle's onboard camera or dashcam. When the road surface information is map information, it can be collected by the vehicle's navigation device.

[0116] For ease of understanding, the following text explains the different ways in which the intelligent driving domain controller obtains road information.

[0117] Scenario 1: The road surface information is image information, which is collected by multiple on-board cameras of the target vehicle.

[0118] Please see Figure 3 , Figure 3 This is a schematic diagram of a scenario where a vehicle collects road surface information, as provided in an embodiment of this application. Figure 3 The target vehicle 301 in the text can be Figure 1A The target vehicle 101 in the corresponding embodiment can also be other vehicles. The target vehicle 301 is equipped with a front-view camera 302, a rear-view camera 303, and side-view cameras 304-309. The front-view camera 302 and the rear-view camera 303 are used to collect image information of the motor vehicle lane 310 where the target vehicle 301 is located. The side-view cameras 304-306 are used to collect image information of the non-motor vehicle lane 312 adjacent to the motor vehicle lane 310 where the target vehicle 301 is located. The side-view cameras 307-309 are used to collect image information of the same-direction motor vehicle lane 311 adjacent to the motor vehicle lane 310 where the target vehicle 301 is located.

[0119] It should be noted that, Figure 3 The field of view and acquisition range of each camera are merely examples, and the embodiments of this application do not impose strict limitations on them. For example, the field of view A and acquisition range (area shown in figure ABC) of the side-view camera 304, and the field of view D and acquisition range (area shown in figure DEF) of the side-view camera 306 can be set according to actual application scenarios and requirements.

[0120] The multiple vehicle-mounted cameras transmit the collected road information to the intelligent driving domain controller in the target vehicle 301. Scenario 2: The road information is map information, collected by the target vehicle's navigation device. The target vehicle's navigation device can obtain the target vehicle's location information and collect map information based on this location information. This map information can use different markers to distinguish the real-time traffic conditions of each lane within a preset range centered on the target vehicle.

[0121] Optionally, the location information can be provided by the Global Positioning System (GPS), the BeiDou Navigation Satellite System, or other positioning systems.

[0122] The navigation device sends the collected road information to the intelligent driving domain controller in the target vehicle.

[0123] Step S202: The intelligent driving domain controller determines the road conditions of the non-motorized lane adjacent to the motorized lane where the target vehicle is located based on the road information.

[0124] The intelligent driving domain controller sets corresponding preset conditions for multiple factors affecting the entry of non-motorized vehicles from the non-motorized lane adjacent to the motorized lane where the target vehicle is located, such as lane closure and lane congestion. Then, it determines whether the non-motorized lane is abnormal by analyzing whether the road information contains information that is the same as the preset conditions.

[0125] When the road information is image information, if the image shows that the non-motorized vehicle lane has corresponding signs such as construction signs or road closure signs, the non-motorized vehicle lane is closed; if the image shows that there are many non-motorized vehicles in the non-motorized vehicle lane and / or the distance between non-motorized vehicles is small, the non-motorized vehicle lane is congested. Therefore, the intelligent driving domain controller can set corresponding preset conditions, compare the image information with the preset conditions, and then determine whether the road condition of the non-motorized vehicle lane is abnormal. For ease of understanding, please refer to Table 1, which is a table showing the correspondence between preset conditions and non-motorized vehicle lane conditions provided in the embodiments of this application:

[0126]

[0127] Optionally, the first threshold and the second threshold can be the default thresholds set for the target vehicle, or thresholds set according to the actual application scenario and requirements.

[0128] Optionally, the construction sign can be a construction material required for road construction (such as piled sand, cement, or asphalt), a construction tool required for road construction (such as a bulldozer, road screed, or road milling machine), or a traffic warning sign that directly indicates that lane changing is prohibited. The closure sign can be road closure tools required for road closure (such as fences or warning ropes), or a traffic warning sign that directly indicates that the road is closed.

[0129] Optionally, the non-motorized vehicle may be a bicycle, tricycle, rickshaw, animal-drawn vehicle, electric vehicle, or vehicle for the disabled.

[0130] It should be noted that the embodiments of this application do not limit the number of signs in the preset conditions. The number shown in Table 1 is only an example. It is easy to understand that the more signs in the preset conditions, the more accurately the target vehicle can judge the road conditions of the non-motorized vehicle lane, and thus more accurately identify the safety hazards of non-motorized vehicles entering the motorized vehicle lane.

[0131] When the road information is map information, if the map shows that the non-motorized vehicle lane has corresponding signs such as construction signs or road closure signs, the non-motorized vehicle lane is in a closed state; if the map shows that the non-motorized vehicle lane has corresponding signs such as congestion signs, the non-motorized vehicle lane is in a congested state. Therefore, the intelligent driving domain controller can set corresponding preset conditions, compare the map information with the preset conditions, and then determine the road condition of the non-motorized vehicle lane. For easier understanding, please refer to Table 2, which is another correspondence table between preset conditions and non-motorized vehicle lane conditions provided in the embodiments of this application:

[0132]

[0133] The map information uses different colors to distinguish the status of non-motorized vehicle lanes. For example, if the motorized vehicle lane is gray, it indicates that the lane is closed; if it is yellow, it indicates that the lane is closed; if it is red, it indicates that the lane is congested; and if it is green, it indicates that the lane is open to traffic. In other words, the markers in this map information can be color-coded, text-based, or icon-based.

[0134] Step S203: The intelligent driving domain controller determines the road conditions of other motor vehicle lanes in the same direction as the target vehicle's lane based on the road information.

[0135] The intelligent driving domain controller sets corresponding preset conditions for multiple factors that affect the target vehicle's lane change to other lanes in the same direction as the target vehicle's lane, such as lane closure, lane change prohibition, and lane congestion. Then, it analyzes whether the road information contains information that is the same as the preset conditions to determine whether the lane is abnormal.

[0136] When the road information is image information, if the image shows that other motor vehicle lanes have corresponding signs such as construction signs or road closure signs, the non-motor vehicle lane is closed; if the image shows that there are many motor vehicles in other motor vehicle lanes and / or the distance between motor vehicles is small, the other motor vehicle lane is congested; if the image shows that other motor vehicle lanes have corresponding signs such as no lane changing signs, the other motor vehicle lane is prohibited from changing lanes. Therefore, the intelligent driving domain controller can set corresponding preset conditions, compare the image information with the preset conditions, and then determine whether the road conditions of other motor vehicle lanes are abnormal. Please refer to Table 3, which is a table showing the correspondence between preset conditions and motor vehicle road conditions provided in the embodiments of this application:

[0137]

[0138] Optionally, the third and fourth thresholds can be the default thresholds set for the target vehicle, or thresholds set according to the actual application scenario and requirements.

[0139] Optionally, the stationary lane change sign can be a solid line sign on the other lane or a traffic warning sign that directly indicates that lane change is prohibited.

[0140] When the road information is map information, if the map shows that other motor vehicle lanes have corresponding signs such as construction signs or road closure signs, then those other motor vehicle lanes are closed; if the map shows that other motor vehicle lanes have corresponding signs such as congestion signs, then those other motor vehicle lanes are congested; if the map shows that other motor vehicle lanes have corresponding signs such as no lane changing signs, then those other motor vehicle lanes are no lane changing. Therefore, the intelligent driving domain controller can set corresponding preset conditions, compare the map information with the preset conditions, and then determine the road conditions of the non-motorized vehicle lane. For easier understanding, please refer to Table 4, which is another table showing the correspondence between preset conditions and motor vehicle road conditions provided in the embodiments of this application:

[0141]

[0142] The map information can distinguish the status of the non-motorized vehicle lane by different colors. That is to say, the signs in the map information can be color signs, text signs, or icon signs.

[0143] It should be noted that this intelligent driving domain controller can select the type of road information to acquire based on the actual scenario and needs, thereby accurately determining the road conditions between the non-motorized vehicle lane and other motorized vehicle lanes. For example, when the target vehicle is located in a remote area where detailed map information is unavailable, the intelligent driving domain controller can determine the lane's road conditions based on image information; for example, when the target vehicle is driving at night and the image information is not clear, the intelligent driving domain controller can determine the lane's road conditions based on map information; and for example, when the target vehicle is located in an area prone to traffic accidents, the intelligent driving domain controller can combine image information and map information to determine the lane's road conditions.

[0144] Step S204: If a preset first abnormal situation occurs in the non-motorized vehicle lane and a preset second abnormal situation occurs in other motorized vehicle lanes, the intelligent driving domain controller will output the first prompt information.

[0145] Specifically, the first alert is used to indicate the first abnormal situation in the non-motorized vehicle lane and to remind drivers to slow down.

[0146] For better understanding, please refer to Figure 4 , Figure 4 This is a schematic diagram illustrating a scenario where a vehicle outputs a first prompt message according to an embodiment of this application. At time T1, the target vehicle 401 is traveling in the motor vehicle lane 402. The intelligent driving domain controller in the target vehicle 401 determines that the road condition of the non-motor vehicle lane 403 is a first abnormal situation based on the road closure sign 409 in the image information of the non-motor vehicle lane 403. Furthermore, by analyzing the image information of the motor vehicle lane 404, the number of other vehicles 405-408 exceeds a third threshold, thus determining that the road condition of the motor vehicle lane 404 is a second abnormal situation. In other words, the target vehicle 401 recognizes that there is a safety hazard of non-motor vehicles entering the motor vehicle lane 402 in the non-motor vehicle lane 403 and that the motor vehicle lane 404 does not meet the conditions for lane changing. Therefore, the intelligent driving domain controller controls the output device of the target vehicle 401 to output a first prompt message to indicate the first abnormal situation in the non-motor vehicle lane 403 and to prompt the driver to slow down. After receiving the first prompt message, the driver of the target vehicle 401 can choose to reduce the vehicle speed. In other words, the speed of the target vehicle 401 at time T2 is less than the speed of the target vehicle 401 at time T1.

[0147] Optionally, the output device can be a voice device such as a car audio system, or a display device such as a center console screen; the first prompt information can be output via voice broadcast or video playback.

[0148] For example, the first prompt message could be a voice message saying, "The non-motorized vehicle lane on the right is closed. Please adjust your speed and drive safely."

[0149] Step S205: If a preset first abnormal situation occurs in the non-motorized vehicle lane, and no preset second abnormal situation occurs in other motorized vehicle lanes, the intelligent driving domain controller will output a second prompt message.

[0150] Specifically, the second notification message is used to indicate the first abnormal situation in the non-motorized vehicle lane and to prompt lane changing.

[0151] For better understanding, please refer to Figure 5 , Figure 5 This is a schematic diagram illustrating a scenario where a vehicle outputs a second prompt message according to an embodiment of this application. At time T1, the target vehicle 501 is traveling in the motor vehicle lane 502. The intelligent driving domain controller in the target vehicle 501 determines that the non-motor vehicle lane 503 is congested (i.e., the road condition of the non-motor vehicle lane 503 is the first abnormal situation) based on the map information showing that the non-motor vehicle lane 503 is a red lane, and determines that the motor vehicle lane 504 is in a normal traffic state (i.e., the road condition of the motor vehicle lane 504 is normal) based on the map information showing that the motor vehicle lane 504 is a green lane. In other words, the intelligent driving domain controller identifies a safety hazard of non-motor vehicles entering the motor vehicle lane 502 in the non-motor vehicle lane 503, and that the motor vehicle lane 504 has the conditions for lane changing. Therefore, the intelligent driving domain controller controls the output device of the target vehicle 501 to output a second prompt message to indicate the first abnormal situation in the non-motor vehicle lane 503 and to prompt the driver to change lanes. After receiving the second prompt message, the driver of the target vehicle 501 can choose to change lanes to the motor vehicle lane 504. In other words, at time T2, the target vehicle 501 changed lanes from lane 502 to lane 504, and at time T3, the target vehicle 501 had changed lanes to lane 504.

[0152] Optionally, the output device can be a voice device such as a car audio system, or a display device such as a center console screen; the second prompt information can be output via voice broadcast or video playback.

[0153] For example, the second prompt could be a voice message saying, "The right-hand non-motorized vehicle lane is congested. Drivers are advised to change lanes to the left."

[0154] Through the embodiments of this application, when the target vehicle determines that there is a safety hazard of non-motorized vehicles entering the motorized vehicle lane through the intelligent driving domain controller, it outputs corresponding prompt information according to the road conditions of the motorized vehicle in the same direction. This is used to alert the driver to the abnormal situation and suggest that the driver adjust the corresponding driving strategy. This can avoid potential driving risks and improve the real-time performance, accuracy and intelligence of the vehicle's information processing based on abnormal road conditions.

[0155] In one optional embodiment, the intelligent driving domain controller can acquire video information of other roads through a first server, analyze the road conditions of each lane in the video information of these other roads, and select video information of at least two target roads. These two target roads are those where the first abnormal situation occurs in the target non-motorized vehicle lane, but the preset second abnormal situation does not occur in the target motorized vehicle lane. It should be noted that the target motorized vehicle lane is separated from the target non-motorized vehicle lane by one motorized vehicle lane. That is, both target roads exhibit the same road conditions as the road where the target vehicle is located. It should be noted that the video information can reflect the actual traffic conditions of each lane in the other roads and the road surface details of each lane. Optionally, the first server can be a physical device such as a server or host, or a virtual device such as a virtual machine or container. For example, the first server can be in the cloud, such as a single service or a server cluster composed of multiple servers in the cloud, or it can be a local device, such as a single service or a server cluster composed of multiple servers locally. The first server can be connected to the target vehicle, roadside equipment and surveillance cameras on other roads via wireless communication, such as wireless LAN, Bluetooth, mobile communication networks and other intangible media, and can be used to assist the target vehicle in obtaining video information of other roads captured by roadside equipment or surveillance cameras.

[0156] Then, for each target road, the intelligent driving domain controller calculates the duration of the first abnormal situation in the target non-motorized lane and the duration of the second abnormal situation in the target motorized lane in the video information of the target road. According to the duration, the video information of the target road is divided into N sub-video information on an average basis, and the vehicle traffic efficiency on the target motorized lane in the N sub-video information is calculated respectively, where N is an integer greater than 1.

[0157] It should be noted that the intelligent driving domain controller can select a fixed marker on the target motor vehicle lane as a reference and calculate the number of vehicles passing the fixed marker within the time of each sub-video. Since the time of each sub-video is the same, the target vehicle can use the calculated number of vehicles as the vehicle traffic efficiency on the target motor vehicle lane in each sub-video information.

[0158] Furthermore, the intelligent driving domain controller determines the driving behavior of multiple first vehicles in the target motor vehicle lane in the sub-video information with the highest vehicle traffic efficiency, and determines the driving behavior of multiple second vehicles in the target motor vehicle lane in the sub-video information with the lowest vehicle traffic efficiency.

[0159] If, in each of the two target roads, the proportion of vehicles in the target motor vehicle lane that are changing lanes is greater than a fifth threshold, and the proportion of vehicles in the target second lane that are changing lanes is less than the fifth threshold, then the target vehicle outputs second indication information through its output device. This second indication information is used to indicate the first abnormal situation in the non-motorized vehicle lane, to indicate lane-changing driving behavior of vehicles in other roads, and to prompt lane-changing. In other words, the intelligent driving domain controller determines the effectiveness of executing the lane-changing strategy by analyzing the impact of lane-changing behavior of vehicles in the target motor vehicle lane on the traffic efficiency of the target motor vehicle.

[0160] Optionally, the output device can be a voice device such as a car audio system, or a display device such as a center console screen; the second prompt information can be output via voice broadcast or video playback.

[0161] Optionally, the fifth threshold can be a threshold set by default for the target vehicle, or a threshold set according to the actual application scenario and requirements.

[0162] For example, the second prompt could be a voice message saying, "The right-hand non-motorized vehicle lane is congested. Most vehicles on other roads choose to change lanes when faced with the same situation. Drivers are advised to change lanes to the left."

[0163] In this embodiment, when the target vehicle determines that there is a safety hazard of non-motorized vehicles entering the motorized vehicle lane through the intelligent driving domain controller, if there is no abnormality in other motorized vehicle lanes in the same direction and the conditions for changing lanes are met, the vehicle can further refer to the driving behavior of vehicles on other roads with the same road conditions as the target vehicle. This can more accurately identify the safety hazard of non-motorized vehicles entering the motorized vehicle lane and output a second prompt message indicating lane changing, thereby further improving the intelligence of the vehicle in processing information based on abnormal road conditions.

[0164] Furthermore, if the non-motorized lane does not exhibit the preset first abnormal situation, and other motorized lanes do not exhibit the preset second abnormal situation, the target vehicle will output a third prompt message.

[0165] Specifically, during driving, this intelligent driving domain controller can obtain distance information between the target vehicle and surrounding vehicles through the vehicle's sensors. For a clearer understanding, please refer to [link to relevant documentation]. Figure 6 , Figure 6This is a schematic diagram illustrating a scenario where a vehicle acquires distance information, as provided in an embodiment of this application. The intelligent driving domain controller in the target vehicle 601 can acquire distance information between itself and surrounding vehicles 602-604 within the sensor's coverage area (the area shown in Figure 605) via sensors. When surrounding vehicles 602 and 603 enter the target vehicle's preset dangerous distance range (the area shown in Figure 606), i.e., the distance between the target vehicle 601 and surrounding vehicles 602 and 603 is less than or equal to a third threshold, the intelligent driving domain controller will output a third prompt message through the control output device to remind the driver to slow down.

[0166] Optionally, the surrounding vehicles 602-604 can be motor vehicles or non-motor vehicles. The sensor can be an infrared detector, lidar, millimeter-wave radar, or ultrasonic radar.

[0167] Optionally, the third threshold can be a threshold set by default for the target vehicle, or a threshold set according to the actual application scenario and requirements.

[0168] Optionally, the third prompt message can be output via voice broadcast or video playback.

[0169] For example, the third prompt could be a voice message such as "Please keep a safe distance from surrounding vehicles and it is recommended to slow down."

[0170] Through the embodiments of this application, the target vehicle can identify potential driving risks based on the distance information of surrounding vehicles by using the intelligent driving domain controller, and output prompt information to alert the driver of abnormal situations and suggest the driver to perform corresponding driving operations, which can improve the intelligence of the vehicle in processing information based on abnormal road conditions.

[0171] In one optional embodiment, the intelligent driving domain controller can also interact with other vehicles through a second server to obtain driving parameters sent by the second server regarding other vehicles passing through the target vehicle's lane within a preset time period, and determine the driving behavior of the other vehicles based on these parameters. The target vehicle can then output the first information, the second information, or the third information, based on the road conditions of adjacent non-motorized vehicle lanes and the same-direction motorized vehicle lanes, and with reference to the driving behavior of the other vehicles. Specifically, the first information, the second information, and the third information are also used to indicate the driving behavior of the other vehicles within the preset time period.

[0172] Optionally, the second server can be a physical device such as a server or host, or a virtual device such as a virtual machine or container. For example, the second server can be in the cloud, such as a single service or a server cluster composed of multiple servers in the cloud, or it can be a local device, such as a single service or a server cluster composed of multiple servers locally. The second server can be connected to the vehicle wirelessly, such as through wireless local area networks, Bluetooth, mobile communication networks, or other intangible media, to facilitate information exchange between vehicles.

[0173] Optionally, the driving parameter can be one or more of the following: location information, vehicle speed, distance to other vehicles, and lighting information; the driving behavior can be deceleration, emergency braking, or lane change.

[0174] Optionally, the preset time period can be the default time period set for the target vehicle, or it can be a time period set according to the actual application scenario and requirements.

[0175] For example, the intelligent driving domain controller determines that a preset first abnormal situation has occurred in the non-motorized vehicle lane, while no preset second abnormal situation has occurred in other motorized vehicle lanes. Then, based on the speed information of the other vehicles within a preset time period, it determines that the other vehicles have performed an emergency braking operation. Consequently, it outputs a second prompt message through the control output device. This second prompt message is used to indicate the first abnormal situation in the non-motorized vehicle lane, the driving behavior of the other vehicles, and to suggest changing lanes. This second prompt message could be a voice prompt message such as, "The right-hand non-motorized vehicle lane is congested, and another vehicle in your lane performed an emergency braking operation five minutes ago. Drivers are advised to change lanes to the left."

[0176] In this embodiment, the target vehicle, through the intelligent driving domain controller, can more accurately identify safety hazards of non-motorized vehicles entering motorized lanes and output prompt information by referring to the driving behavior of other vehicles within a preset time period based on the road conditions of non-motorized lanes and other motorized lanes, thereby further improving the accuracy of the vehicle's information processing based on abnormal road conditions.

[0177] The methods of the embodiments of this application have been described in detail above. In order to facilitate better implementation of the above solutions of the embodiments of this application, the apparatus of the embodiments of this application is provided below.

[0178] It is understood that the apparatus provided in the embodiments of this application, such as a vehicle intelligent driving domain control device, includes hardware structures, software modules, or combinations of hardware structures and software structures to perform the functions described in the above method embodiments in order to achieve the functions.

[0179] Those skilled in the art will readily recognize that, based on the units and steps described in conjunction with the embodiments disclosed herein, the embodiments of this application can be implemented in hardware or a combination of hardware and computer software. Whether a function is executed in hardware or by computer software driving hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art can implement the foregoing method embodiments using different device implementations in different usage scenarios, and such different device implementations should not be considered beyond the scope of the embodiments of this application.

[0180] This application embodiment can divide the device into functional modules. For example, each function can be divided into its own functional modules, or two or more functions can be integrated into one functional module. The integrated module can be implemented in hardware or software. It should be noted that the module division in this application embodiment is illustrative and only represents one logical functional division; other division methods may be used in actual implementation. For example, taking the case of dividing the device into functional modules through integration as an example, this application illustrates several possible processing devices.

[0181] Please see Figure 7 , Figure 7 This is a schematic diagram of the structure of a vehicle intelligent driving domain control device provided in an embodiment of this application. The vehicle intelligent driving domain control device 70 can be... Figure 1A The target vehicle 101 shown, or the devices in the target vehicle 101; the vehicle intelligent driving domain control device 70 may include an acquisition unit 701, a first determination unit 702, a second determination unit 703, a first output unit 704, and a second output unit 705, each unit being connected via a bus, wherein each unit is described in detail below:

[0182] The acquisition unit 701 is used to collect road surface information during driving, wherein the road surface information is used to represent the position information and / or motion state of objects in each lane of the road segment where the vehicle is located;

[0183] The first determining unit 702 is used to determine the road conditions of the non-motorized lane adjacent to the motorized lane where the vehicle is located based on the road surface information.

[0184] The second determining unit 703 is used to determine the road conditions of other motor vehicle lanes traveling in the same direction as the motor vehicle lane based on the road surface information;

[0185] The first output unit 704 is used to output a first prompt message if a preset first abnormal situation occurs in the non-motorized vehicle lane and a preset second abnormal situation occurs in the other motorized vehicle lanes. The first abnormal situation is used to indicate that there is a safety hazard of non-motorized vehicles occupying the motorized vehicle lane where the vehicle is located in the non-motorized vehicle lane. The second abnormal situation is used to indicate that the other motorized vehicle lanes do not meet the conditions for allowing the vehicle to change lanes. The first prompt message is used to indicate the first abnormal situation in the non-motorized vehicle lane and to prompt the vehicle to slow down.

[0186] The second output unit 705 is used to output a second prompt message if a preset first abnormal situation occurs in the non-motorized vehicle lane and no preset second abnormal situation occurs in the other motorized vehicle lanes. The second prompt message is used to prompt the first abnormal situation in the non-motorized vehicle lane and to prompt lane changing.

[0187] In one possible implementation, the vehicle intelligent driving domain control device 70 further includes:

[0188] The receiving unit is used to receive the driving parameters of other vehicles passing through the motor vehicle lane where the vehicle is located within a preset time period, sent by the server. The server is used to collect the driving parameters of all vehicles connected to the server.

[0189] The third determining unit is used to determine the driving behavior of the other vehicles within the preset time period based on the driving parameters of the other vehicles.

[0190] The first and second prompt messages are also used to prompt the driving behavior of other vehicles within the preset time period.

[0191] In another possible implementation, the road surface information includes image information; in determining the road conditions of the non-motorized lane adjacent to the motorized lane where the vehicle is located based on the road surface information, the first determining unit 702 is specifically used for:

[0192] If the image information is analyzed, and at least one of the following conditions is met, the non-motorized vehicle lane is determined to be the first abnormal situation:

[0193] The image information contains preset construction signs or road closure signs;

[0194] The number of non-motorized vehicles in the image information exceeds a first threshold.

[0195] The distance between non-motorized vehicles in the image information is lower than the second threshold.

[0196] In another possible implementation, regarding the determination of the road conditions of other lanes traveling in the same direction as the lane based on the road surface information, the second determining unit 703 is specifically used for:

[0197] If the image information is analyzed, and at least one of the following conditions is met, then the other vehicle lane is determined to be a second abnormal situation:

[0198] The image information contains preset construction signs or road closure signs;

[0199] The image information contains a preset lane change prohibition sign;

[0200] The number of motor vehicles in the image information exceeds a third threshold.

[0201] The distance between motor vehicles in the image information is lower than the fourth threshold.

[0202] In another possible implementation, the road surface information includes map information; and in determining the road conditions of the non-motorized lane adjacent to the motorized lane where the vehicle is located based on the road surface information, the first determining unit 702 is specifically used for:

[0203] If the map information is analyzed and one or more of the following are found on the non-motorized lane within a preset range centered on the vehicle: a construction sign, a road closure sign, and a congestion sign, then the non-motorized lane is determined to be the first abnormal situation.

[0204] In another possible implementation, regarding the determination of the road conditions of other lanes traveling in the same direction as the lane based on the road surface information, the second determining unit 703 is specifically used for:

[0205] If the map information is analyzed and one or more of the following are found on other motor vehicle lanes within a preset range centered on the vehicle: a construction sign, a road closure sign, a congestion sign, and a no-lane-change sign, then the other motor vehicle lanes are determined to be the second abnormal situation.

[0206] In yet another possible implementation, the vehicle intelligent driving domain control device 70 further includes:

[0207] A receiving unit is used to acquire vehicle distance information between the vehicle and surrounding vehicles through sensors, wherein the surrounding vehicles include vehicles within the coverage area of ​​the sensor device;

[0208] An analysis unit is used to generate a driving strategy for the vehicle based on the vehicle distance information;

[0209] The third output unit is used to output a third prompt message if the non-motorized lane does not experience a preset first abnormal situation, wherein the third prompt message is used to prompt the driver to drive according to the driving strategy.

[0210] In another possible implementation, before outputting the second prompt information, the vehicle intelligent driving domain control device 70 further includes:

[0211] The selection unit is used to select video information of at least two target roads from the video information of the other roads. The two target roads are both roads where the first abnormal situation occurs in the target non-motorized vehicle lane and the preset second abnormal situation does not occur in the target motorized vehicle lane. The target motorized vehicle lane and the target non-motorized vehicle lane are separated by one motorized vehicle lane.

[0212] A segmentation unit is used to calculate the duration of the first abnormal situation occurring in the target non-motorized vehicle lane and the target motorized vehicle lane not experiencing a preset second abnormal situation in the video information of the target road, and to divide the video information of the target road during the duration into N sub-video information on an average basis, where N is an integer greater than 1;

[0213] The calculation unit is used to calculate the vehicle traffic efficiency on the target motor vehicle lane in the N sub-video information respectively;

[0214] The fourth determining unit is used to determine the driving behavior of multiple first vehicles in the target motor vehicle lane in the sub-video information with the highest vehicle traffic efficiency;

[0215] The fifth determining unit is used to determine the driving behavior of multiple second vehicles in the target motor vehicle lane in the sub-video information with the lowest vehicle traffic efficiency;

[0216] The sixth determining unit determines that the proportion of vehicles whose driving behavior includes changing lanes among the plurality of first vehicles is greater than a fifth threshold, and the proportion of vehicles whose driving behavior includes changing lanes among the plurality of second vehicles is less than the fifth threshold.

[0217] It should be noted that, in the embodiments of this application, the specific implementation and technical effects of each unit can also be referred to accordingly. Figure 1A , Figure 1B ,as well as Figures 2-6 The corresponding description of the embodiments.

[0218] Please see Figure 8 , Figure 8This application provides a vehicle intelligent driving domain controller 80, which includes a processor 801, a memory 802, and a communication interface 803. The processor 801, memory 802, and communication interface 803 are interconnected via a bus.

[0219] Processor 801 can be one or more central processing units (CPUs). If processor 801 is a CPU, the CPU can be a single-core CPU or a multi-core CPU.

[0220] The memory 802 includes, but is not limited to, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), or compact disc read-only memory (CD-ROM), which is used for related computer programs and data.

[0221] The communication interface 803 is used to receive and send data. Optionally, the communication interface 803 acquires road surface information and sends the road surface information to the processor 801; optionally, the communication interface 803 receives prompt information sent by the processor 801 and outputs prompt information.

[0222] Processor 801 is used to read the computer program code stored in memory 802 and perform the following operations:

[0223] The vehicle acquires road surface information during its journey, wherein the road surface information is used to represent the position information and / or motion state of objects in each lane of the road segment in which the vehicle is located.

[0224] The road conditions of the non-motorized lane adjacent to the motorized lane where the vehicle is located are determined based on the road surface information;

[0225] The road conditions of other motor vehicle lanes traveling in the same direction as the motor vehicle lane are determined based on the road surface information.

[0226] If a preset first abnormal situation occurs in the non-motorized vehicle lane and a preset second abnormal situation occurs in the other motorized vehicle lane, a first prompt message is output. The first abnormal situation is used to indicate that there is a safety hazard of non-motorized vehicles occupying the motorized vehicle lane where the vehicle is located in the non-motorized vehicle lane. The second abnormal situation is used to indicate that the other motorized vehicle lane does not meet the conditions for allowing the vehicle to change lanes. The first prompt message is used to indicate the first abnormal situation in the non-motorized vehicle lane and to prompt the vehicle to slow down.

[0227] If a preset first abnormal situation occurs in the non-motorized vehicle lane, and no preset second abnormal situation occurs in the other motorized vehicle lanes, a second prompt message is output, wherein the second prompt message is used to indicate the first abnormal situation in the non-motorized vehicle lane and to prompt lane changing.

[0228] In one possible implementation, the processor 801 is further configured to receive driving parameters sent by the server when other vehicles pass through the motor vehicle lane where the vehicle is located within a preset time period, wherein the server is configured to collect driving parameters of all vehicles connected to the server.

[0229] Based on the driving parameters of the other vehicles, determine the driving behavior of the other vehicles within the preset time period;

[0230] The first and second prompt messages are also used to prompt the driving behavior of other vehicles within the preset time period.

[0231] In another possible implementation, the road surface information includes image information; and in determining the road conditions of the non-motorized lane adjacent to the motorized lane where the vehicle is located based on the road surface information, the processor 801 is specifically used for:

[0232] If the image information is analyzed, and at least one of the following conditions is met, the non-motorized vehicle lane is determined to be the first abnormal situation:

[0233] The image information contains preset construction signs or road closure signs;

[0234] The number of non-motorized vehicles in the image information exceeds a first threshold.

[0235] The distance between non-motorized vehicles in the image information is lower than the second threshold.

[0236] In yet another possible implementation, in determining the road conditions of other lanes traveling in the same direction as the lane based on the road surface information, the processor 801 is specifically configured to:

[0237] If the image information is analyzed, and at least one of the following conditions is met, then the other vehicle lane is determined to be a second abnormal situation:

[0238] The image information contains preset construction signs or road closure signs;

[0239] The image information contains a preset lane change prohibition sign;

[0240] The number of motor vehicles in the image information exceeds a third threshold.

[0241] The distance between motor vehicles in the image information is lower than the fourth threshold.

[0242] In another possible implementation, the road surface information includes map information; and in determining the road conditions of the non-motorized lane adjacent to the motorized lane where the vehicle is located based on the road surface information, the processor 801 is specifically used for:

[0243] If the map information is analyzed and one or more of the following are found on the non-motorized lane within a preset range centered on the vehicle: a construction sign, a road closure sign, and a congestion sign, then the non-motorized lane is determined to be the first abnormal situation.

[0244] In yet another possible implementation, before acquiring road surface information during the driving process, the processor 801 is further configured to:

[0245] The distance information between the vehicle and surrounding vehicles is obtained through sensors, and the surrounding vehicles include vehicles within the coverage area of ​​the sensor device;

[0246] A driving strategy for the vehicle is generated based on the vehicle distance information;

[0247] If no preset first abnormal situation occurs in the non-motorized lane, a third prompt message is output, wherein the third prompt message is used to prompt driving according to the driving strategy.

[0248] In another possible implementation, before outputting the second prompt message, the processor 801 is further configured to:

[0249] Select at least two target roads from the video information of the other roads. The two target roads are both roads where the first abnormal situation occurs in the target non-motorized vehicle lane and the preset second abnormal situation does not occur in the target motorized vehicle lane. The target motorized vehicle lane and the target non-motorized vehicle lane are separated by one motorized vehicle lane.

[0250] Calculate the duration of the first abnormal situation occurring in the target non-motorized vehicle lane and the second abnormal situation not occurring in the target motorized vehicle lane in the video information of the target road, and divide the video information of the target road during the duration into N sub-video information on an average basis, where N is an integer greater than 1;

[0251] Calculate the vehicle traffic efficiency on the target motor vehicle lane in each of the N sub-video information;

[0252] Determine the driving behavior of multiple first vehicles in the target motor vehicle lane from the sub-video information with the highest vehicle traffic efficiency;

[0253] Determine the driving behavior of multiple second vehicles in the target motor vehicle lane from the sub-video information with the lowest vehicle traffic efficiency;

[0254] The proportion of vehicles whose driving behavior includes changing lanes is determined to be greater than a fifth threshold among the plurality of first vehicles, and the proportion of vehicles whose driving behavior includes changing lanes is less than the fifth threshold among the plurality of second vehicles.

[0255] It should be noted that the implementation of each operation can also be referred to accordingly. Figure 1A , Figure 1B ,as well as Figures 2-6 The corresponding description of the embodiments.

[0256] This application also provides a computer-readable storage medium storing a computer program that, when run on a network device. Figure 2 The method flow shown is thus implemented.

[0257] In the embodiments of this application, "multiple" refers to two or more objects, and "and / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent three situations: A existing alone, A and B existing simultaneously, and B existing alone. A and B can be singular or plural. Furthermore, unless otherwise stated, the "first" in the first abnormal situation, first prompt information, first threshold, first output unit, and first determination unit mentioned in the embodiments of this application is only used for name identification and is not used to limit the order, timing, priority, or importance of multiple objects. This rule also applies to "second," "third," and "fourth," etc.

[0258] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for processing vehicle alert information based on road anomaly identification, characterized in that, The method includes: The vehicle acquires road surface information during its journey, wherein the road surface information is used to represent the position information and motion state of objects in each lane of the road segment in which the vehicle is located; The road conditions of the non-motorized lane adjacent to the motorized lane where the vehicle is located are determined based on the road surface information; The road conditions of other motor vehicle lanes traveling in the same direction as the motor vehicle lane are determined based on the road surface information. If the road condition of the non-motorized vehicle lane is detected to be a preset first abnormal situation, and the road condition of the other motorized vehicle lane is detected to be a preset second abnormal situation, then a first prompt message is output. The first abnormal situation is used to indicate that there is a safety hazard of non-motorized vehicles occupying the motorized vehicle lane where the vehicle is located in the non-motorized vehicle lane, and the second abnormal situation is used to indicate that the other motorized vehicle lane does not meet the conditions for allowing the vehicle to change lanes. The first prompt message is used to indicate the first abnormal situation of the non-motorized vehicle lane and to prompt the vehicle to slow down. If the road condition of the non-motorized vehicle lane is detected as the first abnormal situation occurs in the non-motorized vehicle lane, and the road condition of the other motorized vehicle lane is detected as the second abnormal situation does not occur in the other motorized vehicle lane, then a second prompt message is output, wherein the second prompt message is used to prompt the first abnormal situation of the non-motorized vehicle lane and to prompt lane changing. Before outputting the second prompt information, the method further includes: selecting video information of at least two target roads from video information of other roads, wherein the two target roads are roads where the first abnormal situation occurs in the target non-motorized vehicle lane and the preset second abnormal situation does not occur in the target motorized vehicle lane, wherein the target motorized vehicle lane and the target non-motorized vehicle lane are separated by one motorized vehicle lane; Calculate the duration of the first abnormal situation occurring in the target non-motorized vehicle lane and the second abnormal situation not occurring in the target motorized vehicle lane in the video information of the target road, and divide the video information of the target road during the duration into N sub-video information on an average basis, where N is an integer greater than 1; Calculate the vehicle traffic efficiency in the target motor vehicle lane in each of the N sub-video information; determine the driving behavior of multiple first vehicles in the target motor vehicle lane in the sub-video information with the highest vehicle traffic efficiency; determine the driving behavior of multiple second vehicles in the target motor vehicle lane in the sub-video information with the lowest vehicle traffic efficiency; determine that the proportion of driving behavior including lane changing among the multiple first vehicles is greater than a fifth threshold, and the proportion of driving behavior including lane changing among the multiple second vehicles is less than the fifth threshold; If no preset first abnormal situation occurs in the non-motorized lane and no preset second abnormal situation occurs in other motorized lanes, a third prompt message is output to remind the driver to slow down. If one or more preset construction signs, road closure signs, congestion signs, and lane change prohibition signs are present in other motorized lanes, then the other motorized lanes are determined to be in the second abnormal situation.

2. The method according to claim 1, characterized in that, The method further includes: The system receives driving parameters from the server when other vehicles pass through the lane where the vehicle is located within a preset time period. Based on the driving parameters of the other vehicles, determine the driving behavior of the other vehicles within the preset time period; The first and second prompt messages are also used to prompt the driving behavior of other vehicles within the preset time period.

3. The method according to claim 1 or 2, characterized in that, The road surface information includes image information; determining the road conditions of the non-motorized lane adjacent to the motorized lane where the vehicle is located based on the road surface information includes: If the image information is analyzed, and at least one of the following conditions is met, the non-motorized vehicle lane is determined to be the first abnormal situation: The image information contains preset construction signs or road closure signs; The number of non-motorized vehicles in the image information exceeds a first threshold. The distance between non-motorized vehicles in the image information is lower than the second threshold.

4. The method according to claim 1 or 2, characterized in that, The road surface information includes image information; determining the road conditions of other motor vehicle lanes traveling in the same direction as the motor vehicle lane based on the road surface information includes: If the image information is analyzed, and at least one of the following conditions is met, then the other vehicle lane is determined to be a second abnormal situation: The image information contains preset construction signs or road closure signs; The image information contains a preset lane change prohibition sign; The number of motor vehicles in the image information exceeds a third threshold. The distance between motor vehicles in the image information is lower than the fourth threshold.

5. The method according to claim 1 or 2, characterized in that, The road surface information includes map information; determining the road conditions of the non-motorized lane adjacent to the motorized lane where the vehicle is located based on the road surface information includes: If the map information is analyzed and one or more of the following are found on the non-motorized lane within a preset range centered on the vehicle: a construction sign, a road closure sign, and a congestion sign, then the non-motorized lane is determined to be the first abnormal situation.

6. The method according to claim 5, characterized in that, Determining the road conditions of other lanes traveling in the same direction as the lane based on the road surface information includes: If the map information is analyzed and one or more of the following are found on other motor vehicle lanes within a preset range centered on the vehicle: a construction sign, a road closure sign, a congestion sign, and a no-lane-change sign, then the other motor vehicle lanes are determined to be the second abnormal situation.

7. A vehicle intelligent driving domain control device, characterized in that, The device includes: The acquisition unit is used to collect road surface information during the driving process, wherein the road surface information is used to represent the position information and / or motion state of objects in each lane of the road segment where the vehicle is located; The first determining unit is used to determine the road conditions of the non-motorized lane adjacent to the motorized lane where the vehicle is located based on the road surface information. The second determining unit is used to determine the road conditions of other motor vehicle lanes traveling in the same direction as the motor vehicle lane based on the road surface information; The first output unit is configured to output a first prompt message if a preset first abnormal situation occurs in the non-motorized vehicle lane and a preset second abnormal situation occurs in the other motorized vehicle lanes. The first abnormal situation is used to indicate that there is a safety hazard of non-motorized vehicles occupying the motorized vehicle lane where the vehicle is located in the non-motorized vehicle lane. The second abnormal situation is used to indicate that the other motorized vehicle lanes do not meet the conditions for allowing the vehicle to change lanes. The first prompt message is used to indicate the first abnormal situation in the non-motorized vehicle lane and to prompt the vehicle to slow down. The second output unit is used to output a second prompt message if a preset first abnormal situation occurs in the non-motorized vehicle lane and no preset second abnormal situation occurs in the other motorized vehicle lanes. The second prompt message is used to prompt the first abnormal situation in the non-motorized vehicle lane and to prompt lane changing. The device further includes: The selection unit is used to select at least two target roads from the video information of other roads before outputting the second prompt information. The two target roads are both roads where the first abnormal situation occurs in the target non-motorized vehicle lane and the preset second abnormal situation does not occur in the target motorized vehicle lane. The target motorized vehicle lane and the target non-motorized vehicle lane are separated by one motorized vehicle lane. A segmentation unit is used to calculate the duration of the first abnormal situation occurring in the target non-motorized vehicle lane and the target motorized vehicle lane not experiencing a preset second abnormal situation in the video information of the target road, and to divide the video information of the target road during the duration into N sub-video information on an average basis, where N is an integer greater than 1; The calculation unit is used to calculate the vehicle traffic efficiency on the target motor vehicle lane in the N sub-video information respectively; The fourth determining unit is used to determine the driving behavior of multiple first vehicles in the target motor vehicle lane in the sub-video information with the highest vehicle traffic efficiency; The fifth determining unit is used to determine the driving behavior of multiple second vehicles in the target motor vehicle lane in the sub-video information with the lowest vehicle traffic efficiency; The sixth determining unit is used to determine that the proportion of vehicles whose driving behavior includes changing lanes is greater than a fifth threshold among a plurality of first vehicles, and the proportion of vehicles whose driving behavior includes changing lanes is less than the fifth threshold among a plurality of second vehicles. in, The vehicle intelligent driving domain control device is also used to output a third prompt message to remind the driver to slow down if the non-motorized lane does not experience a preset first abnormal situation and other motorized lanes do not experience a preset second abnormal situation.

8. A vehicle intelligent driving domain controller, characterized in that, Includes processor, memory, and communication interface. The communication interface is used to perform receiving and / or sending operations under the control of the processor, the memory is used to store computer programs, and the processor is used to call the computer programs to implement the method according to any one of claims 1-6.

9. A vehicle, characterized in that, The vehicle includes an intelligent driving domain controller, wherein the controller is the control device of claim 7 or the controller of claim 8.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when run on a processor, implements the method described in any one of claims 1-6.

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