WO2023159528A1 - 一种数据生成、使用方法及装置 - Google Patents

一种数据生成、使用方法及装置 Download PDF

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Publication number
WO2023159528A1
WO2023159528A1 PCT/CN2022/078122 CN2022078122W WO2023159528A1 WO 2023159528 A1 WO2023159528 A1 WO 2023159528A1 CN 2022078122 W CN2022078122 W CN 2022078122W WO 2023159528 A1 WO2023159528 A1 WO 2023159528A1
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Prior art keywords
collision
information
target vehicle
predicted
indication information
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PCT/CN2022/078122
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English (en)
French (fr)
Inventor
费雯凯
杨淼
刘建琴
Original Assignee
华为技术有限公司
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
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Application filed by 华为技术有限公司 filed Critical 华为技术有限公司
Priority to CN202280089757.5A priority Critical patent/CN118613408A/zh
Priority to PCT/CN2022/078122 priority patent/WO2023159528A1/zh
Publication of WO2023159528A1 publication Critical patent/WO2023159528A1/zh

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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units
    • B60W30/08—Active safety systems predicting or avoiding probable or impending collision or attempting to minimise its consequences

Definitions

  • the present application relates to the field of Internet of Vehicles, and in particular to a method and device for generating and using data.
  • the predicted collision information of the vehicle is of great significance to the vehicle.
  • the vehicle can adjust its own driving strategy and driving path in advance based on the predicted collision information, so as to avoid the collision as much as possible or reduce the damage caused by the collision, which plays an important role in ensuring the driving safety of the vehicle.
  • the current prediction of vehicle collision information cannot meet the accuracy and timeliness requirements of future intelligent driving and intelligent transportation.
  • the application discloses a method and device for generating and using data, which can accurately predict possible collisions of vehicles, provide collision indication information with reference significance for vehicles, and help improve the response efficiency of vehicles to collisions.
  • the present application provides a data generation method, the method includes: obtaining collision indication information based on road environment information and predicted trajectory information, the predicted trajectory information is used to indicate the predicted trajectory of multiple moving objects, and the above multiple moving objects
  • the object includes a target vehicle, the road environment information is used to indicate the driving environment of the road where the trajectory is located, the collision indication information includes first time information and first probability information, the first time information is used to indicate the time when the target vehicle will be predicted to collide, and the second A probability information is used to indicate the probability of the predicted collision; sending the collision indication information to the target vehicle.
  • the time indicated by the first time information is the predicted time when the target vehicle may collide, not necessarily the time when the target vehicle actually collides.
  • the first time information may indicate a time point (for example, a moment), or may indicate a time period.
  • the first probability information may be represented by a floating point number of (0, 1]. The greater the value of the probability indicated by the first probability information, the greater the possibility of the target vehicle colliding.
  • the network side device may be, for example, a server deployed on the network side (such as an application server or a map server), or a component or a chip in the server.
  • the network side device may be deployed in a cloud environment or an edge environment, which is not specifically limited in this embodiment of the present application.
  • Roadside equipment can be, for example, devices such as Road Side Unit (Road Side Unit, RSU), Multi-Access Edge Computing (Multi-Access Edge Computing, MEC) or sensors, or components or chips inside these devices, or can be composed of A system-level device composed of RSU and MEC, or a system-level device composed of RSU and sensors, or a system-level device composed of RSU, MEC and sensors.
  • the collision indication information can provide the vehicle with the prediction information of possible future collisions, and in the process of generating the collision indication information, not only the trajectory of the vehicle and its surrounding moving objects, but also the trajectory of the road where the trajectory is located are also considered comprehensively.
  • the driving environment improves the accuracy of the predicted possible collision of the target vehicle, which is conducive to improving the safety rate of terminal travel.
  • the driving environment includes at least one of the following: weather, visibility, light intensity, road type, number of lanes, road flatness, road smoothness, road construction, historical traffic behavior statistics, and traffic flow.
  • the weather includes but is not limited to parameters such as precipitation, snowfall, wind direction, wind force level, and lightning index.
  • roads There are many types of roads. For example, based on road administrative levels, they can be divided into national roads, provincial roads, county roads, and township roads. Class roads, class 3 roads, etc., can be divided into motor vehicle lanes based on the identity of road users, or can be divided into other ways, which are not specifically limited here.
  • the smoothness of the road can be expressed by parameters such as the location of potholes, the number of potholes, and the depth of potholes.
  • the smoothness of the road is expressed by parameters such as the thickness of the icing on the road, the area of the icing on the road, and the material of the road.
  • the road construction status can be expressed by parameters such as construction location, construction area, and construction time.
  • Traffic flow conditions include but are not limited to parameters such as average traffic flow and maximum traffic flow.
  • the historical traffic behavior statistics are the statistics of the hot behavior areas (or high-frequency behavior areas) of moving objects.
  • the historical statistics of traffic behavior include but are not limited to areas where pedestrians frequently pass through, areas where vehicles accelerate urgently, areas where vehicles decelerate urgently, areas where high-frequency reverse driving, areas where high-frequency running red lights, etc.
  • road environment factors are taken into consideration when performing collision prediction, which can effectively reduce the impact of environmental risks on collision prediction.
  • icy roads will cause poor braking effect of vehicles driving on the road and affect the vehicle's driving trajectory, making collision predictions inaccurate.
  • the impact of road icing on collision predictions can be corrected, which is beneficial to improve Accuracy of collision prediction.
  • the collision indication information further includes location information, and the location information is used to indicate the location where the collision is predicted to occur.
  • the location information may indicate a geographic location point, or may indicate a geographic area range.
  • the position indicated by the position information is the predicted position where the target vehicle may collide, not necessarily the position where the target vehicle actually collides.
  • the location information provides the target vehicle with the location of possible collisions from the spatial dimension, so that the target vehicle can respond in time.
  • the collision indication information further includes at least one of the following predicted information: identification information of the moving object colliding with the target vehicle, collision level information, collision type information, remaining collision time information, collision identification information, collision
  • the remaining collision time information is used to indicate the time difference between the time when the collision will occur and the current time, and the early warning information is used to indicate the contents to be reminded to the driver or the driving system based on the collision.
  • the identification information of the moving object colliding with the target vehicle is an optional information of the collision indication information. Based on the identification information of the moving object to be collided by the target vehicle, the target vehicle is effectively reminded to pay attention to the motion state of the moving object, so that the target vehicle can make timely response decisions to avoid collisions.
  • the collision level information is an optional information of the collision indication information.
  • the collision level information quantifies the severity of the collision step by step, which can effectively distinguish collisions with different risk levels, and is conducive to prioritization.
  • the collision type information is an optional information of the collision indication information.
  • the collision type information enables the target vehicle to respond to the collision event more quickly and more specifically based on the type of the collision, and improves the efficiency of collision response.
  • the collision type information may classify and describe the collision from the direction of the collision, and may also classify and describe the collision from the cause of the collision. There are many ways of specific classification, which are not limited in this application.
  • the remaining collision time information is an optional information of the collision indication information. Based on the remaining collision time information, it can count down to remind the driver or the driving system that the collision predicted by the driving system is coming, so as to realize the timely warning of the collision.
  • the identification information of the dynamic elements in the map that affect the collision is an optional information of the collision indication information. Based on the identification information of the dynamic elements in the map that affect the collision, the dynamic elements associated with the collision can be quickly found. When it is detected that the dynamic elements associated with the collision change, the collision indication information of the target vehicle can be updated in time, thereby improving the accuracy of the collision indication information. For example, icing on the road is a dynamic factor that may affect the collision prediction of the target vehicle, and the identification of the icing on the road is used as the content of the collision indication information of the target vehicle.
  • Early warning information is an optional information of collision indication information. Based on the early warning information, the driver can be reminded of the predicted collision in time, which is conducive to improving the safety of the vehicle.
  • the identification information of the collision, the identification information of the tile where the collision occurs, and the identification information of the road where the collision occurs are all optional information of the collision indication information.
  • the method further includes: updating the collision indication information or deleting the collision indication information when the trajectories of the multiple moving objects change and/or when the dynamic elements in the map that affect the collision change.
  • collision prediction when it is determined that the trajectory of the moving object changes, collision prediction can be re-performed based on the updated trajectory of the moving object; when the dynamic elements in the map that affect the collision change, based on the identification of the dynamic element and the identification of the collision The mapping relationship between them is re-predicted for collision.
  • the linked update of the collision indication information, or the deletion of the collision indication information can be realized. Deletion of the collision indication information means that it is predicted that the corresponding collision will not occur.
  • the method further includes: performing traffic monitoring, traffic scheduling or controlling the target vehicle according to the collision indication information.
  • a variety of application services can be provided based on the collision indication information, such as traffic monitoring, traffic dispatching and other macro regulation services, and customized proprietary services such as the control of the target vehicle.
  • the method further includes: when it is determined that the target vehicle is about to arrive at the location where the collision will occur, controlling the target vehicle to perform at least one of the following operations:
  • the driver is notified of the collision.
  • the target vehicle when it is determined that the vehicle is about to reach the location where the collision will occur, various coping strategies are provided for the vehicle, for example, changing lanes, adjusting driving speed, updating navigation routes, turning on warning lights, prompting the driver of the collision, etc. , the target vehicle can be controlled by selecting any one or multiple combinations of the above, so that the target vehicle can respond to collisions in a timely and accurate manner, and improve the travel safety of the target vehicle.
  • sending the collision indication information to the target vehicle includes: sending the collision indication information to the target vehicle when at least one of the following conditions is met:
  • the minimum distance between the current position of the target vehicle and the position where the collision is predicted to occur is smaller than a second threshold
  • the road where the location where the collision is predicted to occur belongs to is the road where the target vehicle is located;
  • the tile where the predicted collision will occur belongs to the tile where the target vehicle is located.
  • Carry out the above-mentioned implementation send the collision indication information to the target vehicle, that is, the target vehicle is the user of the collision indication information.
  • the limitation of the probability enables the target vehicle to obtain the collision indication information which is more relevant to it, so that the data transmission traffic can be saved.
  • road environment information is obtained based on dynamic layer data and static layer data in the map
  • predicted trajectory information is obtained based on motion state data of multiple moving objects and driver information.
  • the motion state data of a moving object includes parameters such as position coordinates, speed, acceleration, and heading of the moving object at multiple moments in history.
  • Driver information includes but is not limited to the driver's driving habits, the driver's real-time status, etc.
  • Driving habits can be, for example, frequent merging, speeding, overtaking on curves, rushing to yellow lights, not driving fast, giving way to non-motorized vehicles, Reasonable use of lighting, driving without fatigue, etc., the real-time state of the driver can be excited, calm, angry, tired, asleep, coma, etc., for example.
  • the road environment information can be extracted from the static layer data and dynamic layer data of the map.
  • the static layer data can indicate the road type, the number of lanes, the flatness of the road (for example, the depth of potholes, location information, area , quantity, etc.) and other infrequently changing road conditions;
  • dynamic layer data for example, can indicate weather conditions such as precipitation, snowfall, visibility, light intensity, wind direction, wind force, and lightning index that change more frequently over time, and can also indicate Road surface smoothness (for example, whether there is ice, ice thickness, ice location area, etc.), road construction information (for example, whether there is construction, construction location, construction time, etc.), road water situation, road leaf coverage, etc. Road conditions that change more frequently.
  • the static layer data and dynamic layer data in the map data, as well as the motion state data of the moving object and the driver information provide the possibility for the acquisition of the collision indication information, which can provide the target vehicle with Refer to the prediction information for meaning collisions.
  • the method further includes: storing the collision indication information as map data.
  • the collision indication information may be stored as dynamic layer data of map data, and the dynamic layer where the collision indication information is located may be related to at least one other layer in the map (for example, a static layer, a dynamic map that only carries weather information) Layers, etc.) can be superimposed and displayed, and can also be displayed separately, which is not specifically limited here.
  • the dynamic layer where the collision indication information is located may be related to at least one other layer in the map (for example, a static layer, a dynamic map that only carries weather information) Layers, etc.) can be superimposed and displayed, and can also be displayed separately, which is not specifically limited here.
  • the collision indication information increases the richness of the map data.
  • obtaining collision indication information based on road environment information and predicted trajectory information includes: obtaining a collision prediction result according to the predicted trajectory information, the collision prediction result including second time information and second probability information; inputting the road environment information to the artificial intelligence
  • the AI model outputs risk area information, which includes the location information of the risk area and the risk level of the risk area; corrects the collision prediction result according to the risk area information, and obtains collision indication information.
  • the collision prediction results are corrected based on the risk area information (that is, representing the environmental risk) to obtain the collision indication information, taking into account the environmental risk.
  • the impact on collision prediction improves the accuracy of the predicted collision of the target vehicle.
  • the present application provides a method for using data, which is applied to a target vehicle.
  • the method includes: acquiring collision indication information, where the collision indication information includes first time information and first probability information, and the first time information is used to indicate prediction The time when the target vehicle will collide, the first probability information is used to indicate the probability of the predicted collision; according to the collision indication information, the control of the target vehicle is executed.
  • the method is applied to a target vehicle, and the target vehicle may be, for example, a vehicle driven using collision indication information, a device, component or chip in the vehicle, such as an on-board unit (On Board Unit, OBU), which is not specifically limited here.
  • OBU On Board Unit
  • the time indicated by the first time information is the predicted time when the target vehicle may collide, not necessarily the time when the target vehicle actually collides.
  • the first time information may indicate a time point (for example, a moment), or may indicate a time period.
  • the target vehicle can know the probability of the collision and the time when the collision may occur by obtaining the collision indication information in advance, so that it can adjust itself in time to deal with the collision according to the collision indication information, which not only improves the response efficiency of the target vehicle to the collision, but also Improves the safety of the target vehicle during driving.
  • the collision indication information further includes location information, and the location information is used to indicate the location where the collision is predicted to occur.
  • the location indicated by the location information may be a geographic point or a geographic area.
  • the position indicated by the position information is the predicted position where the target vehicle may collide, not necessarily the position where the target vehicle actually collides.
  • Position information can be expressed as coordinate values obtained based on any coordinate system, for example, the coordinate system can be the world geodetic coordinate system (Word Geodetic System 1984, WGS84), natural coordinate system, road coordinate system, etc.
  • the coordinate system can be the world geodetic coordinate system (Word Geodetic System 1984, WGS84), natural coordinate system, road coordinate system, etc.
  • the collision indication information also includes at least one of the following information:
  • the identification information of the moving object that collided with the target vehicle the collision level information, the collision type information, the remaining collision time information, the identification information of the collision, the identification information of the tile where the collision occurred, the identification information of the road where the collision occurred, and the map that affected the collision Identification information and early warning information of dynamic elements in the system;
  • the collision level information is used to indicate the severity of the collision
  • the collision type information is used to indicate the type of collision
  • the remaining collision time information is used to indicate the time difference between the time when the collision will occur and the current time
  • the early warning information is used to indicate the direction of driving based on the collision. content that is reminded by the driver or the driving system.
  • control of the target vehicle is performed according to the collision indication information, including:
  • the target vehicle is controlled to perform at least one of the following operations:
  • the driver is notified of the collision.
  • the target vehicle when the target vehicle determines that it is about to arrive at the location where the collision will occur, it can control itself to take various measures to deal with the collision, so that the target vehicle can flexibly respond to possible collisions in the future, and the response efficiency of the target vehicle to collisions is improved.
  • performing control on the target vehicle according to the collision indication information includes: when the probability of the predicted collision occurrence is greater than a first preset threshold, and when the time difference between the time when the target vehicle will collide and the current time is smaller than the second preset When the threshold is reached, the control of the target vehicle is executed.
  • performing control on the target vehicle includes at least one of the following operations: changing lanes, adjusting driving speed, updating navigation routes, turning on warning lights, and prompting the driver of the collision.
  • the conditions for triggering the control of the target vehicle are limited from the two dimensions of probability and time.
  • the target vehicle will Controlling improves the efficiency of the target vehicle in coping with collisions.
  • the method further includes: when the time difference between the time when the target vehicle will collide and the current time is less than a third preset threshold and/or the distance between the current position of the target vehicle and the position where the collision occurs is less than a fourth preset When the threshold is reached, the target vehicle is controlled to perform emergency braking or change lanes in the current lane.
  • the third preset threshold is less than or equal to the above-mentioned second preset threshold.
  • the target vehicle cannot avoid the collision with the moving object by slowing down slowly and steadily. Collision, in this case, the target vehicle can achieve rapid deceleration or even stop by emergency braking in the current lane, or the target vehicle can avoid collisions with moving objects by changing lanes, thus ensuring the driving safety of the target vehicle .
  • the method further includes: when it is predicted that multiple moving objects collide with the target vehicle at the same time, according to the severity of the collision between the target vehicle and each moving object, obtaining a coping strategy of the target vehicle.
  • the target vehicle's coping strategy can be: prioritize the collision with the moving object 2, and take measures to avoid the collision with the moving object 2 as much as possible.
  • the target vehicle determines the order of dealing with the collision based on the severity of the collision between itself and the moving object, that is, the target vehicle makes good use of the collision level information, realizes flexible response to the predicted collision, and improves the target vehicle's own safety. safety.
  • the method further includes: presenting collision indication information on a display interface of the target vehicle in at least one of the following ways:
  • the predicted moving object that will collide with the target vehicle is presented on the display interface, which intuitively shows the position and orientation of the moving object relative to the target vehicle itself, and accurately reminds the target vehicle to pay attention to the source of the collision risk, making the target vehicle more targeted proactively take countermeasures.
  • the target vehicle knows through the display interface that the moving object to be collided is located in its left rear, the target vehicle can always pay attention to the running status of the left rear moving object and take timely countermeasures.
  • the time difference between the predicted collision occurrence time and the current time is displayed on the display interface, that is, the predicted remaining collision time information is presented on the display interface, which realizes the countdown reminder of the time when the predicted collision will occur, and increases the collision with the passage of time. A sense of urgency to arrive.
  • the probability of the presented collision is limited on the display interface, and the most likely collision is visually displayed, so as to remind the driver of the collision that is currently focused on.
  • the grades of the presented collisions are limited, and the collisions with a higher degree of danger or more serious are intuitively displayed, so that the user can focus on the collisions with a higher degree of danger.
  • Predicted collision indication information corresponding to collisions that occur on the navigation path is presented on the display interface, wherein the collisions that occur on the navigation path include predictions that the target vehicle will collide and/or that other vehicles will occur on the navigation path of the target vehicle. A collision that occurs in which the target vehicle is not involved. In this way, the target vehicle can be intuitively and effectively reminded of possible future collisions on its navigation path, which improves the safety of the target vehicle during driving.
  • the user can also independently select the collision indication information corresponding to the type or level of collision that he is interested in or currently wants to view, so that it can be displayed on the display interface, which improves the user's interactive experience.
  • the collision indication information corresponding to different levels of collisions is displayed in different colors on the display interface, which intuitively shows the distribution of collisions of different collision levels in the map, and users can also effectively distinguish different levels of collisions based on colors.
  • the collision indication information corresponding to different types of collisions is displayed in different colors on the display interface, which intuitively shows the distribution of collisions of different types in the map, and users can also effectively distinguish different types of collisions based on colors.
  • the collision indication information when the collision indication information is presented on the display interface, all content in the collision indication information may be presented, or part of the content in the collision indication information may be presented. For example, only the predicted moving object colliding with the target vehicle is presented, or the location where the moving object and the predicted target vehicle will collide may also be presented, which is not specifically limited herein.
  • the collision indication information when the collision indication information is presented on the display interface, the collision indication information can be embedded in a map for display, and the map can be a high-precision map, a standard precision map or other types of maps stored locally by the target vehicle , is not specifically limited here.
  • the present application provides a data generation device, which includes: an acquisition unit, configured to obtain collision indication information based on road environment information and predicted trajectory information, where the predicted trajectory information is used to indicate the predicted trajectory of multiple moving objects , the plurality of moving objects includes a target vehicle, the road environment information is used to indicate the driving environment of the road where the trajectory is located, the collision indication information includes first time information and first probability information, and the first time information is used to indicate that the predicted target vehicle will occur The time of the collision, the first probability information is used to indicate the probability of the predicted collision occurrence; the sending unit is used to send the collision indication information to the target vehicle.
  • an acquisition unit configured to obtain collision indication information based on road environment information and predicted trajectory information, where the predicted trajectory information is used to indicate the predicted trajectory of multiple moving objects , the plurality of moving objects includes a target vehicle, the road environment information is used to indicate the driving environment of the road where the trajectory is located, the collision indication information includes first time information and first probability information, and the first time information is used to indicate that the predicted target vehicle will occur The
  • the driving environment includes at least one of the following: weather, visibility, light intensity, road type, number of lanes, road flatness, road smoothness, road construction, historical traffic behavior statistics, and traffic flow.
  • the collision indication information further includes location information, and the location information is used to indicate the location where the collision is predicted to occur.
  • the collision indication information further includes at least one of the following predicted information: identification information of the moving object colliding with the target vehicle, collision level information, collision type information, remaining collision time information, collision identification information, collision
  • the remaining collision time information is used to indicate the time difference between the time when the collision will occur and the current time, and the early warning information is used to indicate the contents to be reminded to the driver or the driving system based on the collision.
  • the device further includes a processing unit configured to update or delete the collision indication information when the trajectories of multiple moving objects change and/or when the dynamic elements in the map that affect the collision change.
  • a processing unit configured to update or delete the collision indication information when the trajectories of multiple moving objects change and/or when the dynamic elements in the map that affect the collision change.
  • the processing unit is further configured to: perform traffic monitoring, traffic scheduling or control of the target vehicle according to the collision indication information.
  • processing unit is further configured to: control the target vehicle to perform at least one of the following operations when it is determined that the target vehicle is about to arrive at the location where the collision will occur:
  • the driver is notified of the collision.
  • the sending unit is specifically configured to send collision indication information to the target vehicle when at least one of the following conditions is met:
  • the minimum distance between the current position of the target vehicle and the position where the collision is predicted to occur is smaller than a second threshold
  • the road where the location where the collision is predicted to occur belongs to is the road where the target vehicle is located;
  • the tile where the predicted collision will occur belongs to the tile where the target vehicle is located.
  • road environment information is obtained based on dynamic layer data and static layer data in the map
  • predicted trajectory information is obtained based on motion state data of multiple moving objects and driver information.
  • the device further includes a storage unit, configured to: store the collision indication information as map data.
  • the acquisition unit is specifically used to: obtain the collision prediction result according to the predicted trajectory information, the collision prediction result includes the second time information and the second probability information; input the road environment information to the artificial intelligence AI model, and output the risk area information, the risk The area information includes the position information of the risk area and the risk level of the risk area; the collision prediction result is corrected according to the risk area information, and the collision indication information is obtained.
  • the present application provides a data usage device, which includes: a receiving unit for acquiring collision indication information, where the collision indication information includes first time information and first probability information, and the first time information is used to indicate the predicted target vehicle The time when the collision will occur, the first probability information is used to indicate the probability of the predicted collision occurrence; the processing unit is used to execute the control on the target vehicle according to the collision indication information.
  • the collision indication information further includes location information, and the location information is used to indicate the location where the collision is predicted to occur.
  • the collision indication information also includes at least one of the following information:
  • the identification information of the moving object that collided with the target vehicle the collision level information, the collision type information, the remaining collision time information, the identification information of the collision, the identification information of the tile where the collision occurred, the identification information of the road where the collision occurred, and the map that affected the collision Identification information and early warning information of dynamic elements in the system;
  • the collision level information is used to indicate the severity of the collision
  • the collision type information is used to indicate the type of collision
  • the remaining collision time information is used to indicate the time difference between the time when the collision will occur and the current time
  • the early warning information is used to indicate the direction of driving based on the collision. content that is reminded by the driver or the driving system.
  • a processing unit specifically for:
  • the target vehicle is controlled to perform at least one of the following operations:
  • the processing unit is specifically configured to: when the probability of the predicted collision occurrence is greater than the first preset threshold, and when the time difference between the time when the target vehicle will collide and the current time is less than the second preset threshold, execute control.
  • the processing unit is further configured to: when the time difference between the time when the target vehicle will collide and the current time is less than a third preset threshold and/or the distance between the current position of the target vehicle and the position where the collision occurs is less than a fourth
  • the threshold is preset, the target vehicle is controlled to perform emergency braking or lane change in the current lane.
  • the processing unit is further configured to: when multiple moving objects are predicted to collide with the target vehicle at the same time, according to the severity of the collision between the target vehicle and each moving object, obtain a coping strategy for the target vehicle.
  • the device further includes a display unit for presenting collision indication information on a display interface of the target vehicle in at least one of the following ways:
  • the present application provides a data generation device, which includes at least one processor and a communication interface, where the communication interface is used to provide information input and/or output for the at least one processor.
  • the device is used to implement the first aspect or the method in any possible embodiment of the first aspect.
  • the present application provides a data usage device, which includes at least one processor and a communication interface, and the communication interface is used to provide information input and/or output for the at least one processor.
  • the device is used to implement the second aspect or the method in any possible embodiment of the second aspect.
  • the present application provides a computer-readable storage medium, including computer instructions.
  • the computer instructions are executed by a processor, the above-mentioned first aspect or any possible implementation of the first aspect can be realized. method.
  • the present application provides a computer-readable storage medium, including computer instructions.
  • the computer instructions are executed by a processor, the above-mentioned second aspect or any possible implementation of the second aspect can be realized. method.
  • the present application provides a computer program product.
  • the computer program product When the computer program product is executed by a processor, the method in the above-mentioned first aspect or any possible embodiment of the first aspect is implemented.
  • the computer program product can be, for example, a software installation package. If the method provided by any possible design of the first aspect above needs to be used, the computer program product can be downloaded and executed on the processor. , so as to implement the first aspect or the method in any possible embodiment of the first aspect.
  • the present application provides a computer program product.
  • the computer program product When the computer program product is executed by a processor, the method in the above-mentioned second aspect or any possible embodiment of the second aspect is implemented.
  • the computer program product may be, for example, a software installation package. If the method provided by any possible design of the second aspect above needs to be used, the computer program product may be downloaded and executed on the processor. , so as to implement the second aspect or the method in any possible embodiment of the second aspect.
  • the present application provides a vehicle, the vehicle includes the data usage device according to the fourth aspect or any possible implementation manner of the fourth aspect above, or includes the device according to the sixth aspect or the sixth aspect above Data usage means of any possible implementation.
  • the present application provides an electronic map, the electronic map includes collision indication information, and the collision indication information includes time information and probability information, wherein the time information is used to indicate the time when the target vehicle will collide, and the probability information is used for Indicates the probability of a predicted collision occurring.
  • the collision indication information further includes location information, and the location information is used to indicate the location where the collision is predicted to occur.
  • the collision indication information further includes at least one of the following predicted information: identification information of the moving object colliding with the target vehicle, collision level information, collision type information, remaining collision time information, collision identification information, collision
  • the remaining collision time information is used to indicate the time difference between the time when the collision will occur and the current time, and the early warning information is used to indicate the contents to be reminded to the driver or the driving system based on the collision.
  • the electronic map is a map product, specifically, it can be a map data product carrying collision indication information, such as a map update data package, or it can be a map application product loaded with collision indication information, such as being installed on a vehicle or a portable terminal Map application programs, or map display products that present collision indication information in graphic and/or text form, such as electronic navigators.
  • the present application provides a computer-readable storage medium for storing the electronic map described in the above-mentioned twelfth aspect and any possible embodiment of the twelfth aspect.
  • the present application provides electronic information, the electronic information carries collision indication information, the collision indication information includes time information and probability information, the time information is used to indicate the time when the target vehicle will collide, and the probability information is used to Indicates the probability of a predicted collision occurring.
  • the electronic information is a collection of electrical, magnetic or electromagnetic signals
  • map information is carried in the form of electrical, magnetic or electromagnetic carriers.
  • a computer-readable storage medium has an information input interface, and the information input interface is capable of receiving information from the fourteenth aspect or any of the possible implementations of the fourteenth aspect. described electronic information, and store the collision indication information carried by the electronic information in the computer-readable storage medium.
  • FIG. 1 is a schematic diagram of a scene provided by an embodiment of the present application.
  • FIG. 2 is a schematic diagram of a system architecture provided by an embodiment of the present application.
  • Fig. 3 is a flow chart of a data generation method provided by an embodiment of the present application.
  • FIG. 4 is a schematic framework diagram of a collision prediction system provided by an embodiment of the present application.
  • Fig. 5 is a schematic representation of the location information of a collision provided by the embodiment of the present application.
  • FIG. 6A is a schematic diagram of a data structure of collision indication information provided by an embodiment of the present application.
  • FIG. 6B is a schematic diagram of a data structure of collision indication information provided by an embodiment of the present application.
  • FIG. 7 is a flow chart of a method for using data provided by an embodiment of the present application.
  • Fig. 8 is a schematic interface diagram of a display device provided by an embodiment of the present application.
  • FIG. 9 is a schematic diagram of a display interface provided by an embodiment of the present application.
  • FIG. 10 is a schematic diagram of the functional structure of a data generation device provided in this embodiment of the present application.
  • FIG. 11 is a schematic diagram of the functional structure of a data usage device provided in this embodiment of the present application.
  • FIG. 12 is a schematic diagram of a functional structure of a data processing device provided in this embodiment of the present application.
  • the number of described objects is not limited by the prefixes, and may be one or more. Taking “the first device” as an example, the number of “device” may be one or more.
  • the objects modified by different prefixes can be the same or different, for example, if the described object is "equipment”, then “first equipment” and “second equipment” can be the same equipment, the same type of equipment or different types of equipment ; For another example, if the described object is "information”, then “first information” and “second information” may be information of the same content or information of different content.
  • the use of prefixes used to distinguish the described objects in the embodiments of the present application does not constitute a restriction on the described objects. For the description of the described objects, please refer to the claims or the description of the context in the embodiments. It should not be because of the use of such prefixes constitute redundant restrictions.
  • a description such as "at least one (or at least one) of a1, a2, ... and an” is used, including any one of a1, a2, ... and an.
  • the case of being alone also includes the case of any combination of any number of a1, a2, ... and an, and each case can exist alone.
  • the description of "at least one of a, b, and c" includes a alone, b alone, c alone, a combination of a and b, a combination of a and c, a combination of b and c, or a combination of abc Condition.
  • a map may include multiple layers (Layers), and a layer may be understood as a map data set, and data in the map data set is organized in a set data structure.
  • Data in layers can describe map features from a variety of sources.
  • map elements can be divided into two types: elements and events: elements are map elements that are relatively fixed, change little, or have a long update cycle, such as road topology, building location, lane line, lane direction or traffic Infrastructure layout, etc.; events are map elements with strong time-varying characteristics, such as traffic accidents, weather changes, road icing, road construction, or traffic congestion.
  • a map description object it may have both time-varying map elements and time-invariant map elements, that is, the description object is not only related to elements in the map, but also related to events in the map.
  • the geographical location of the lane is an element in the map
  • the traffic flow of the lane is an event in the map.
  • elements and events can be recorded in different layers, information about elements is carried by static layers in the map, and information about events is carried by dynamic layers in the map.
  • the map may include at least one static layer, and may further include multiple dynamic layers.
  • the map includes a static layer 1 and two dynamic layers (dynamic layer 1 and dynamic layer 2, respectively), and the geographic location of buildings, roads, trees, traffic lights, and road signs is recorded in static layer 1.
  • the dynamic layer 1 records the real-time speed limit of the lane, the traffic construction situation and the flow of people and vehicles
  • the dynamic layer 2 records the weather conditions, such as sunny, rainy, snowy, windy, temperature or humidity, etc.
  • Data in static layers in a map can be called elements or static features
  • data in dynamic layers in a map can be called events or dynamic features.
  • FIG. 1 is a schematic diagram of an application scenario provided by an embodiment of the present application.
  • vehicle 1 assuming that vehicle 1 intends to reach position D from position A, vehicle 1 obtains the predicted trajectory information of surrounding vehicles by sensing the surrounding environment, and performs collision prediction analysis based on its own predicted trajectory information.
  • vehicle 1 obtains the future trajectory information of vehicle 2 based on the motion state of vehicle 2, and conducts collision prediction analysis based on its own trajectory information to determine that there is a collision risk between vehicle 1 and vehicle 2 in area 2.
  • the embodiment of the present application proposes a data processing method, which can accurately predict the possible collision of the vehicle, and provide the vehicle with reference collision indication information, which is conducive to improving the safety of the vehicle during driving .
  • FIG. 2 exemplarily shows a system architecture diagram of an embodiment of the present application.
  • the system is used to generate collision indication information.
  • the collision indication information includes time information and probability information.
  • the time information is used to indicate the time when the target vehicle will collide, and the probability information is used to indicate the probability of the collision.
  • the system includes at least one of network side equipment, roadside equipment and vehicles.
  • the vehicle can communicate with the network-side device and the road-side device respectively in a wireless manner, and the network-side device and the road-side device can communicate in a wireless or wired manner.
  • the network-side device is a device with a computing function, for example, it may be a server (such as an application server) deployed on the network side, or a component or a chip in the server.
  • the network-side device may be deployed in a cloud environment, that is, a cloud computing server, or the network-side device may also be deployed in an edge environment, that is, an edge computing server.
  • the network side device may be one integrated device, or multiple distributed devices, which is not specifically limited in this embodiment of the present application.
  • Roadside equipment can be, for example, devices such as Road Side Unit (Road Side Unit, RSU), Multi-Access Edge Computing (Multi-Access Edge Computing, MEC) or sensors, or components or chips inside these devices, or can be composed of A system-level device composed of RSU and MEC, or a system-level device composed of RSU and sensors, or a system-level device composed of RSU, MEC and sensors.
  • RSU Road Side Unit
  • MEC Multi-Access Edge Computing
  • the vehicle may be, for example, a vehicle driven using collision indication information, or a device, component, or chip in the vehicle, such as an On Board Unit (OBU), which is not specifically limited in this embodiment of the present application.
  • OBU On Board Unit
  • the collision indication information may be generated by network-side devices or road-side devices.
  • the network-side device first obtains road environment information and predicted trajectory information indicating the predicted trajectory of multiple moving objects, wherein the multiple moving objects include the target vehicle, and according to the predicted trajectory information and road environment information to obtain the above collision indication information; and send the collision indication information to the target vehicle.
  • the network side device may also perform traffic monitoring, traffic dispatching or control of the target vehicle according to the collision indication information. That is to say, the network-side device can serve as a generator and issuer of the collision indication information, and can also serve as a user of the collision indication information.
  • the road environment information is used to indicate the driving environment of the road where the trajectory is located.
  • the driving environment includes but is not limited to weather, visibility, light intensity, road type, number of lanes, road flatness, road smoothness, road construction, and traffic violation history Statistics and traffic flow, etc.
  • the road environment information can be derived from dynamic layer data and static layer data in the map, and the map can be a high-definition map, a standard precision map, or other types of maps, which are not specifically limited in this embodiment of the present application.
  • the collision indication information may also exist in the form of a map layer.
  • collision indication information is stored as dynamic layer data.
  • the vehicle may also generate collision indication information for its own use or to send to other devices for use.
  • a map is stored in the vehicle, and the map may be a high-definition map, a standard-definition map or other types of maps.
  • the vehicle can obtain road environment information from the map, obtain the above-mentioned predicted trajectory information according to the motion state data of multiple moving objects and driver information, and obtain collision indication information according to the road environment information and predicted trajectory information.
  • the network side device can issue the collision indication information to the vehicle through a wireless network, such as a cellular communication network; or, the network side device can issue the collision indication information to other devices, and the other devices forward it to the vehicle , Forwarding can be done through V2X (Vehicle to Everything, Internet of Vehicles).
  • V2X Vehicle to Everything, Internet of Vehicles
  • the server in the cloud sends collision indication information to the target vehicle subscribed to the collision prediction service, which can be published through the cellular communication network including the base station, or forwarded by the roadside device to the target vehicle through V2X communication.
  • the producer of the collision indication information is a roadside device, and the roadside device may publish it through V2X.
  • the collision indication information can be updated with an update frequency of hours or even minutes.
  • the communication between the network side equipment and the vehicle, between the vehicle and the roadside equipment, and between the network side equipment and the roadside equipment can use cellular communication technology, such as 2G cellular communication, such as the Global System for Mobile Communications (global system for mobile communication (GSM), general packet radio service (GPRS); or 3G cellular communication, such as wideband code division multiple access (WCDMA), time division synchronous code division multiple access (time division-synchronous code division multiple access, TS-SCDMA), code division multiple access (code division multiple access, CDMA), or 4G cellular communication, such as long term evolution (long term evolution, LTE). Or 5G cellular communication, or other evolved cellular communication technologies.
  • 2G cellular communication such as the Global System for Mobile Communications (global system for mobile communication (GSM), general packet radio service (GPRS); or 3G cellular communication, such as wideband code division multiple access (WCDMA), time division synchronous code division multiple access (time division-synchronous code division multiple access, TS-SCDMA), code division multiple access (code division multiple access
  • the wireless communication system may also utilize non-cellular communication technologies, such as Wi-Fi and wireless local area network (wireless local area network, WLAN) communication.
  • the communication between the above devices can also use infrared link, bluetooth or ZigBee for direct communication.
  • other wireless protocols may be used for communication between the above devices, such as various vehicle communication systems, for example, the system may include one or more dedicated short range communications (DSRC) devices, these devices It may include public and/or private data communication between vehicles and/or roadside stations, which is not specifically limited in this application.
  • DSRC dedicated short range communications
  • FIG. 2 is only an exemplary architecture diagram, but does not limit the number of network elements included in the system shown in FIG. 2 .
  • FIG. 2 may also include other functional entities.
  • the method provided in the embodiment of the present application can be applied to the communication system shown in FIG. 2 , and of course the method provided in the embodiment of the present application can also be applied to other communication systems, which is not limited in the embodiment of the present application.
  • Figure 3 is a flow chart of a data generation method provided by the embodiment of the present application, which can be applied to network-side equipment or roadside equipment.
  • the following uses network-side equipment as an example to illustrate the solution, but this
  • the embodiment of the application does not limit that the method is only used for the network side device.
  • the method includes but is not limited to the following steps:
  • S101 Acquire predicted trajectory information, where the predicted trajectory information is used to indicate predicted trajectories of multiple moving objects.
  • obtaining predicted trajectory information includes: obtaining motion state data of each of the multiple moving objects, and predicting the trajectory of the corresponding mobile object according to the motion state data of each mobile object, so as to obtain predicted trajectory information.
  • the predicted trajectory of each moving object includes, but is not limited to, the position coordinates, speed, acceleration, heading, etc. of each moving object at each moment.
  • the multiple moving objects also include other moving objects around the target vehicle, for example, they may be inanimate movable objects such as motor vehicles and non-motor vehicles, or pedestrians, pedestrians on bicycles, Animate movable objects such as animals on the road.
  • the motion state data of each mobile object includes state parameters (for example, position coordinates, speed, acceleration, heading, etc.) of the mobile object at multiple historical moments.
  • the predicted trajectory information can also be obtained in combination with the driver information, where the driver information includes but not limited to the driver's driving habits, the driver's real-time status etc.
  • the driving habits can be, for example, frequent merging, speeding, overtaking on curves, rushing to yellow lights, not driving fast, giving way to non-motorized vehicles, using lights reasonably at night, driving without fatigue, etc.
  • the real-time status of the driver can be, for example, Excitement, peace, anger, fatigue, falling asleep, coma, etc.
  • the motion status data of each moving object can be obtained by network-side equipment from a map (for example, a high-precision map), or it can be obtained by the traffic management department based on the identification of the moving object (for example, when the moving object is a vehicle, the moving The identification of the object can be a vehicle identification code) and sent to the network side device after searching, or it can be sent to the network side device after the roadside device or other vehicles monitor the motion state of the moving object.
  • the motion state data of the moving object may be partly or entirely from at least one of the map, the server of the traffic management department, roadside equipment, vehicles, etc., and the embodiment of the present application does not specifically limit the source of the motion state data of the moving object .
  • FIG. 4 is a schematic framework diagram of a collision prediction system provided by an embodiment of the present application.
  • Fig. 4 simply illustrates the acquisition process of predicted trajectory information. It can be seen from Fig. 4 that the motion state data of the target vehicle and the motion state data of other moving objects are obtained respectively, wherein, the motion state data of the target vehicle and the motion state data of other moving objects can refer to the corresponding description above, according to the target Trajectory prediction is performed on the motion state data of the vehicle to obtain the predicted trajectory of the target vehicle; trajectory prediction is performed based on the motion state data of other moving objects to obtain the predicted trajectory of other moving objects.
  • trajectory prediction such as Gaussian mixture model, Bayesian model, Kalman filter model, long-short-term memory (Long Short-Term Memory, LSTM) model, etc.
  • the embodiments of the present application are not specifically limited here.
  • the road environment information is used to indicate the driving environment of the road where the trajectory is located, where the trajectory is the predicted trajectory of the plurality of moving objects.
  • the driving environment includes at least one of the following contents: weather, visibility, light intensity, road type, number of lanes, road flatness, road smoothness, road construction, traffic violation historical statistics, and traffic flow.
  • the weather includes but is not limited to parameters such as precipitation, snowfall, wind direction, wind force level, and lightning index.
  • roads There are many types of roads. For example, based on road administrative levels, they can be divided into national roads, provincial roads, county roads, and township roads. Class roads, class 3 roads, etc., can be divided into motor vehicle lanes based on the identity of road users, or can be divided into other ways, which are not specifically limited here.
  • the number of lanes can reflect the width of the road.
  • the smoothness of the road can be expressed by parameters such as the location of potholes, the number of potholes, and the depth of potholes.
  • the smoothness of the road can be expressed by parameters such as the thickness of the icing on the road, the location of the icing on the road, and the material of the road.
  • the road construction status can be expressed by parameters such as construction location, construction area, and construction time.
  • Traffic flow conditions include but are not limited to parameters such as average traffic flow and maximum traffic flow.
  • the historical traffic behavior statistics are the statistics of the hot behavior areas (or high-frequency behavior areas) of moving objects.
  • the historical statistics of traffic behavior include but are not limited to areas where pedestrians frequently pass through, areas where vehicles accelerate urgently, areas where vehicles decelerate urgently, areas where high-frequency reverse driving, areas where high-frequency running red lights, etc.
  • the main road shown in Figure 1 includes lane 1 and lane 2.
  • vehicle 1 is the target vehicle
  • vehicle 2 is a moving object around vehicle 1
  • the trajectory of vehicle 1 is predicted as path A ⁇ B ⁇ C ⁇ D
  • the road where the trajectory of vehicle 1 is located is road segment AD
  • the road environment information corresponding to vehicle 1 is actually the road environment information at various locations when vehicle 1 is driving on road segment AD based on the trajectory.
  • the road environment information corresponding to the vehicle 2 can also be obtained based on the trajectory of the vehicle 2 .
  • the road environment information corresponding to the vehicle 2 can also be obtained based on the trajectory of the vehicle 2 .
  • the road environment information corresponding to the trajectory of each moving object can be obtained in the above-mentioned manner, and the road corresponding to the trajectory of multiple moving objects can also be determined comprehensively in combination with the trajectories of multiple moving objects
  • the environmental information is not specifically limited here.
  • the road environment information may be obtained by the network side device from dynamic layer data and static layer data in the map.
  • the collision indication information includes first time information and first probability information.
  • the first time information is used to indicate the time when the predicted target vehicle will collide.
  • the first probability information is used to Indicates the probability of a predicted collision occurring.
  • the time indicated by the first time information is the predicted time when the target vehicle may collide, not necessarily the time when the target vehicle actually collides.
  • the time indicated by the first time information may be a time point (for example, a moment), or may be a time period.
  • the first time information When the first time information indicates a time point, the first time information may be expressed as the moment "14:05", for example; when the first time information indicates a time period, the first time information may be expressed as the period "14:05", for example. -14:07", the duration of the period can be expressed in milliseconds ms, seconds s, minutes min or other units of magnitude, which are not specifically limited here.
  • the first probability information may be represented by a floating point number of (0, 1]. The larger the value of the probability indicated by the first probability information, the greater the possibility of the target vehicle colliding.
  • the collision indication information further includes location information, and the location information is used to indicate the location where the collision is predicted to occur.
  • the location information may indicate a geographic location point, or may indicate a geographic area range.
  • the position indicated by the position information is the predicted position where the target vehicle may collide, not necessarily the position where the target vehicle actually collides.
  • Position information can be expressed as coordinate values obtained based on any coordinate system, for example, the coordinate system can be the world geodetic coordinate system (Word Geodetic System 1984, WGS84), natural coordinate system, road coordinate system, etc.
  • the coordinate system can be the world geodetic coordinate system (Word Geodetic System 1984, WGS84), natural coordinate system, road coordinate system, etc.
  • the location information of the collision may be expressed in a lane-level manner.
  • Figure 5 is a schematic representation of the location information of a collision provided by the embodiment of the present application.
  • the road shown in Figure 5 includes lane 1 and lane 2, and it is assumed that the location where the collision will occur is area 1 in lane 1 in Figure 5 , if the area 1 is represented at the lane level, the collision location information can be expressed as the area corresponding to the rectangle abcd, where the width of the area is the width of the lane 1 and the length is the length of the area 1 along the lane line.
  • the location information of the collision may be expressed in a road-level manner, which is not specifically limited here.
  • Both the road-level representation and the lane-level representation can be represented by one or more parameters relative to a reference point (for example, the starting point of a lane or a road), such as distance and coordinates.
  • a reference point for example, the starting point of a lane or a road
  • the location information of the collision can also be expressed in other ways. For example, when the location where the collision occurs is an irregular area, the location information of the collision can also be expressed based on the minimum circumscribed rectangle, or based on multiple corners The geographical coordinates of the points are represented, which are not specifically limited in this embodiment of the present application.
  • the collision indication information further includes at least one of the following predicted information: identification information of the moving object colliding with the target vehicle, collision level information, collision type information, remaining collision time information, collision identification Information, the identification information of the tile where the collision occurs, the identification information of the road where the collision occurs, the identification information and early warning information of the dynamic elements in the map that affect the collision.
  • the collision level information is used to indicate the severity of the collision
  • the collision type information is used to indicate the type of the collision
  • the early warning information is used to indicate the contents to be reminded to the driver or the driving system based on the collision.
  • the collision indication information further includes identification information of a moving object that collides with the target vehicle.
  • identification information of the moving object colliding with the target vehicle is an optional information of the collision indication information.
  • the identification information of the moving object that collides with the target vehicle can effectively remind the target vehicle to pay attention to the movement state of the moving object, so that the target vehicle can make a response decision in time to avoid the occurrence of the collision.
  • the collision indication information further includes collision level information, and the collision level information is used to indicate the severity of the collision.
  • the collision level information is an optional information of the collision indication information. Based on the collision level information, the severity of the collision can be quantified step by step, which is helpful for the target vehicle to quickly distinguish the priority of the collision and improve the response efficiency to the collision.
  • the severity of a collision can be divided into four levels, which are minor, general, major, and extraordinarily serious, wherein the minor level means that one or two people are slightly injured at one time, or the amount of property damage caused by a motor vehicle accident is less than 1,000 yuan , non-motor vehicle accidents are less than 200 yuan; the general level means that 1 to 2 people are seriously injured at one time, or more than 3 people are slightly injured, or the property loss is less than 30,000 yuan; the major level means that 1 to 2 people are killed at a time, or 3 people are seriously injured More than 10 people, or property loss of more than 30,000 yuan but less than 60,000 yuan; extraordinarily large means that more than 3 people were killed, or more than 11 people were seriously injured, or 1 person was killed and more than 8 people were seriously injured at the same time, or 2 people were killed and seriously injured at the same time.
  • the minor level means that one or two people are slightly injured at one time, or the amount of property damage caused by a motor vehicle accident is less
  • the severity of the collision can also be divided in other ways, for example, it can be divided into high risk and low risk based on whether people are injured, where the high risk means that people are injured in this collision, and the low risk means that the No one was injured in the collision.
  • the collision level information may use bitmap, binary value or other methods to indicate the severity of the collision. Taking the binary value method as an example, see Table 1.
  • Table 1 exemplarily provides a mapping table between the value of the collision level information and the severity of the collision. It can be seen from Table 1 that when the value of the collision level information is "00 ", it indicates that the severity of the collision is minor; when the value of the collision level information is "01”, it indicates that the severity of the collision is normal; when the value of the information of the collision level is "10", it indicates that the severity of the collision is major; When the value of the level information is "11”, it means that the collision severity is extremely large.
  • the collision grades corresponding to the severity of the collision are sorted from high to low in order: extra large>major>general>slight. It should be noted that the smaller the value of the collision level information, the smaller the severity of the collision, which also means that the risk of collision is lower.
  • Table 1 is only used as an example to reflect the corresponding relationship between the value of the collision level information and the severity of the collision.
  • the text content and storage method of the corresponding relationship can also be in other forms. Here Not specifically limited.
  • the collision indication information further includes collision type information, and the collision type information is used to indicate the type of the collision. It should be noted that the collision type information is an optional information of the collision indication information.
  • the types of collision events can be classified into front collision, rear collision, left collision and right collision based on the collision orientation.
  • the types of collisions may also be classified into turning collisions, rear-end collisions, lane-changing collisions, etc. based on collision causes.
  • the collision indication information further includes remaining collision time information, and the remaining collision time information is used to indicate the time difference between the time when the collision will occur and the current time. It should be noted that the remaining collision time information is a kind of optional information of the collision indication information.
  • the remaining time-to-collision information may be the remaining travel time of the target vehicle before the earliest time when a future collision of the target vehicle is predicted to occur.
  • the remaining collision time information may also be collision time (Time-to-Collision, TTC), safety time domain (Safety Time Domain, STD), headway (Time Headway, TH), etc., in This is specifically limited. It can be seen that based on the remaining collision time information, the driver or the collision predicted by the driving system can be reminded in real time, and the timely warning of the collision can be realized.
  • the collision indication information further includes identification information of dynamic elements in the map that affect the collision. It should be noted that the identification information of the dynamic element in the map that affects the collision is an optional information of the collision indication information.
  • Dynamic elements in the map that affect collisions include, but are not limited to: icy roads, road construction, heavy fog, snowstorms, rainstorms, road congestion, road collapse, landslides, road maintenance, etc. It can be seen that based on the identification information of the dynamic elements in the map that affect the collision, the dynamic elements associated with the collision can be quickly searched. When it is detected that the dynamic elements associated with the collision change, the collision indication information of the target vehicle can be updated in time, thereby improving the accuracy of the collision indication information.
  • the identification information of the dynamic feature is used to identify the dynamic feature in the map.
  • the identification information of a dynamic element can be a combination of one or more characters, where the characters can be one or more of numbers, letters and other symbols, such as a combination of one or more numbers, or one or more data and A combination of letters.
  • the collision indication information also includes at least one of the identification information of the collision, the identification information of the tile where the collision occurs, the identification information of the road where the collision occurs, and the early warning information, and these information are all elements of the collision indication information.
  • Optional information is also included.
  • a tile can be understood as a rectangular grid image that cuts a map within a certain range into several rows and columns according to a certain size and format, and different map resolutions.
  • the sliced rectangular grid image is called Tile.
  • the identification information of the collision is used for the collision; the identification information of the tile is used for identifying the tile in the map, and the identification information of the road is used for identifying the road in the map.
  • the identification information of the collision, the identification information of the tile or the identification information of the road may be a combination of one or more characters, where the characters may be one or more of numbers, letters and other symbols, such as one or more numbers combination, or one or more combinations of data and letters. It can be seen that by associating the collision with the identification of the map tile, a fast index of the collision can be realized based on the identification of the map tile. By associating collisions with road identities, fast indexing of collisions can be achieved based on road identities. Thus, the collision search time can be saved, and the collision search efficiency can be improved.
  • the early warning information can be, for example, "Please note that there is a risk of collision in area 1 at time 1", or it can be "There is a risk of collision with vehicle A in area 1 at time 1, the probability is 0.8, please adjust the motion state in time", or it can be "There is a 0.6 probability of collision at time 1, please pay attention", or other information with a risk warning function, which is not specifically limited in this embodiment of the present application.
  • Early warning information can be displayed by voice broadcast or text display. It can be seen that through the early warning information, the driver can be reminded of the predicted collision in time to improve the safety of the vehicle.
  • the collision indication information may be stored in a data structure corresponding to the collision identifier.
  • the collision indication information may also be stored as map data, for example, stored as dynamic layer data of a map.
  • the collision indication information is stored as map data
  • the predicted collision may also be called a collision event in the map
  • the identification information of the collision is the identification information of the collision event.
  • FIG. 6A is a schematic diagram of a data structure of collision indication information provided by an embodiment of the present application.
  • the collision indication information corresponding to the collision event 1 is illustrated by taking the collision event 1 as an example.
  • the collision indication information includes time information and probability information, wherein the time information is used to indicate the time when the collision event 1 is predicted to occur, and the probability information is used for Indicates the probability of predicting the occurrence of collision event 1.
  • the collision indication information further includes at least one of the following predicted information: collision level information, collision type information, identification of a moving object that collides with the target vehicle, and dynamic factors affecting the collision event 1 At least one of the identification of , early warning information, the identification of the tile where the collision event 1 is located, the identification of the road where the collision event 1 is located, and the identification of the collision event 1.
  • the predicted collision between the target vehicle and different moving objects can be expressed separately. It can be understood that if it is represented by a collision event in FIG. 6A , it means that one target vehicle corresponds to multiple collision events.
  • the preset distance condition may be that the distance between the two locations is less than or equal to the preset distance threshold, or that the overlapping area between the two locations is greater than or equal to the preset area threshold, or other conditions, which are not specifically limited here.
  • At least one item of time information, probability information, collision level information, collision type information, etc. corresponding to different moving objects may also be different.
  • FIG. 6B is a schematic diagram of a data structure of another kind of collision indication information provided by an embodiment of the present application.
  • the collision indication information includes position information, an identifier of the collision event 1, and time information, probability information, collision level information, collision type information, and early warning information corresponding to each of the multiple moving objects.
  • moving The time information corresponding to the object A is used to indicate the time when the predicted target vehicle collides with the moving object A; the probability corresponding to the moving object A is used to indicate the probability of the predicted target vehicle colliding with the moving object A; the collision level information corresponding to the moving object A It is used to indicate the severity of the collision between the predicted target vehicle and the mobile object A; the collision type information corresponding to the mobile object A is used to indicate the predicted type of the collision between the predicted target vehicle and the mobile object A.
  • the collision indication information further includes an identifier of the tile where the collision event 1 is located, an identifier of the road where the collision event 1 is located, and an identifier of a dynamic element that affects the collision event 1 .
  • the collision level information corresponding to each moving object shown in FIG. 6B can also be defaulted, and the collision level information of collision event 1 is set, and the collision level information of collision event 1 is determined by the target vehicle and each moving object. The severity of the collision is determined.
  • FIG. 6A and FIG. 6B are just an example, and the embodiment of the present application does not limit the data structure diagram of the collision indication information to be only shown in FIG. 6A or FIG. 6B .
  • the predicted trajectory information after obtaining the predicted trajectory information (for details of this process, refer to the above-mentioned S101 related description) and the road environment information, based on the road environment information and the predicted trajectory information can be: according to the road environment information, obtain the risk area information; according to The predicted trajectory information and the risk area information obtain collision indication information, and the collision indication information includes the above-mentioned first time information and first probability information.
  • the collision indication information further includes location information, collision level information, collision type information, and an identification number of a moving object that collides with the target vehicle.
  • obtaining the collision indication information based on the road environment information and the predicted trajectory information may be: obtaining the collision prediction result according to the predicted trajectory information, and the collision prediction result includes the second time information and the second probability information of the collision of the target vehicle; Input the road environment information to the first artificial intelligence (AI) model, and output the risk area information, which includes the location information of the risk area and the risk level of the risk area; correct the collision prediction result according to the risk area information, and obtain the collision indication information.
  • AI artificial intelligence
  • the collision prediction result is corrected based on the risk area information (that is, representing the environmental risk) to obtain the collision indication information, which effectively improves the accuracy of the predicted collision of the target vehicle.
  • the first artificial intelligence AI model can also be called an environmental risk prediction model.
  • the first AI model is obtained through training based on historical collision data and historical road environment data.
  • the historical collision data includes time information, location information,
  • the historical road environment data such as collision type information and collision level information are used to indicate the driving environment of the road where the historical trajectory of the moving object corresponding to the historical collision is located.
  • For the historical road environment data please refer to the description of the corresponding content in S102.
  • the training process of the first AI model may be: first evaluate the risk level of the area where the historical collision is located according to the collision level of the historical collision, so as to establish the relationship between the collision level of the historical collision, the area where the historical collision is located, and the risk level corresponding to the area. mapping relationship. For example, the higher the collision level of the historical collision (indicating the more severe the collision degree), the higher the risk level of the area where the historical collision is located (indicating the lower safety of the area).
  • the first AI model Taking the risk level of the area as the training target, input the historical collision data and historical road environment data into the first AI model, the first AI model outputs the predicted location information of the risk area and the predicted risk level corresponding to the risk area, according to the predicted location information and the area
  • the real location information of the first AI model, the predicted risk level and the real risk level of the area are used to obtain the forecast error of the first AI model, and the model parameters of the first AI model are adjusted based on the forecast error of the first AI model.
  • the forecast error of the first AI model is less than the forecast error
  • the training of the first AI model is completed, and the trained first AI model can accurately predict the risk area and the risk level corresponding to the risk area based on the road environment information.
  • obtaining collision indication information based on road environment information and predicted trajectory information may also be: input road environment information into the first AI model to obtain risk area information, risk area information includes risk area location information and risk The risk level of the area; input the risk area information and predicted trajectory information into the second AI model to obtain collision indication information.
  • the second AI model can integrate the environmental risk and the trajectory of each moving object to realize the collision prediction of the target vehicle.
  • the second AI model is obtained based on the training of historical motion trajectory data, historical collision data and historical road environment data.
  • the historical motion trajectory data Including the historical trajectory of the moving object corresponding to the historical collision, for details about the historical collision data and historical road environment data, please refer to the description of the relevant content of the above-mentioned first AI model, which will not be repeated here.
  • the first AI model or the second AI model can be artificial neural network (Artificial Neural Network, ANN), long short-term memory (Long Short-Term Memory, LSTM) neural network, random forest, support vector machine, or other predictive algorithm.
  • ANN Artificial Neural Network
  • LSTM Long Short-Term Memory
  • S104 Send collision indication information to the target vehicle.
  • sending the collision indication information to the target vehicle may be: after the network side device generates the collision indication information, it sends the collision indication information to the target vehicle.
  • sending the collision indication information to the target vehicle may be: receiving a collision prediction service request from the target vehicle, the collision prediction service request is used to request the network side device to provide the collision prediction service for the target vehicle, and the collision prediction service request includes An identification of the target vehicle; in response to the collision prediction service request, sending collision indication information to the target vehicle. That is to say, the target vehicle pre-subscribes to the network-side device for the collision prediction service, and when the target vehicle is driving, it can send a collision prediction service request carrying its own identity to the network-side device to obtain collision indication information related to the target vehicle.
  • sending the collision indication information to the target vehicle may also be: sending the collision indication information to the target vehicle when at least one of the following conditions is met:
  • the tile where the predicted collision will occur is the tile where the target vehicle is located.
  • the network side device sends the collision indication information to the target vehicle in advance, that is, the time when the network side device sends the collision indication information to the target vehicle is earlier than the predicted time when the target vehicle will collide.
  • the target vehicle can know the collision in advance, so that it can take countermeasures against the collision in time, for example, adjust its own movement strategy, so as to avoid the occurrence of the collision as much as possible.
  • the network side device may also send collision indication information to the moving object predicted to collide with the target vehicle, so as to prompt that the moving object has a risk of colliding with the target vehicle.
  • the network side device may also periodically send collision indication information to the target vehicle. This is because the motion state of the target vehicle, the motion state of the moving object that collides with the target vehicle, and the surrounding road environment information change frequently, so the network side device can obtain updated road environment information and predicted trajectory according to the preset cycle information, and update the collision indication information based on the updated road environment information and the updated predicted trajectory information, and send the updated collision indication information to the target vehicle.
  • updating the collision indication information may also be: updating the collision indication information or deleting the collision indication information when the trajectories of multiple moving objects change and/or when the dynamic elements in the map that affect the collision change.
  • updating the collision indication information specifically includes modifying at least one of the first time information, the first position information, the collision level information, the collision type information, the early warning information, and the identification information of the dynamic elements affecting the collision in the collision indication information.
  • deleting the collision indication information includes at least one of the following situations: the updated collision level information is less than the lower risk threshold (in this case, it can be considered that the risk of collision is low or no risk); the updated first probability information The indicated predicted probability of collision is less than a lower probability threshold (in which case, a collision may be considered to have a low probability of occurrence or not occur).
  • the collision indication information is deleted, meaning that the predicted collision will not occur.
  • S105 Execute traffic monitoring, traffic scheduling or control of the target vehicle according to the collision indication information.
  • performing traffic monitoring according to the collision indication information may be: performing road condition monitoring according to the collision indication information at a location where a collision is predicted to occur.
  • the network-side device can monitor whether there is a collision near the predicted collision location, and when a collision is detected, it can promptly notify the traffic control department personnel to go to the accident scene.
  • the execution of traffic scheduling may be: according to the collision indication information, determine the road area where the collision is located in the map, and remind the vehicles in the road area of the collision, or control the traffic flow in the road area .
  • the network side device prompts the collision to the vehicles in the road area where the collision is located, so that the vehicles in the road area can know in advance that there is a collision risk of the target vehicle around them, so that they can adjust their driving speed in time to keep a safe distance from the target vehicle and prevent Serial rear-end.
  • the network device can also control the traffic flow in the road area where the collision occurs, so as to prevent the traffic flow in the road area from being too large, thereby effectively reducing the congestion caused by the collision in the road area.
  • controlling the target vehicle according to the collision indication information may be: when it is determined that the target vehicle is about to arrive at the location where the collision will occur, controlling the target vehicle to perform at least one of the following operations: changing lanes; adjusting the driving speed; Update navigation routes; turn on warning lights; and alert drivers of collisions.
  • the target vehicle before the network-side device controls the target vehicle, the target vehicle pre-customizes the collision prediction service to the network device, so that the network-side device can control the target vehicle in a timely manner to accurately respond to the collision, so as to avoid collisions as much as possible.
  • implementing the embodiment of the present application can provide vehicles with reference and real-time dynamic collision indication information, and in the process of generating collision indication information, not only the trajectories of the vehicle and its surrounding moving objects are considered, but also comprehensive consideration
  • the driving environment of the road where the trajectory is located is improved, the accuracy of the predicted collision of the target vehicle is improved, and the safety rate of vehicle travel is improved.
  • FIG. 7 is a flow chart of a data usage method provided by an embodiment of the present application, which is applied to a target vehicle.
  • the method includes but is not limited to the following steps:
  • S201 Receive collision indication information, where the collision indication information includes first time information and first probability information, the first time information is used to indicate the time when the target vehicle is predicted to collide, and the first probability information is used to indicate the probability of the predicted collision.
  • the collision indication information includes first time information and first probability information
  • the first time information is used to indicate the time when the target vehicle is predicted to collide
  • the first probability information is used to indicate the probability of the predicted collision.
  • receiving the collision indication information may be: receiving the collision indication information from a network side device or a roadside device.
  • the target vehicle when at least one of the following conditions is met, the target vehicle receives the collision indication information:
  • the tile where the predicted collision will occur is the tile where the target vehicle is located.
  • S202 Perform self-control according to the collision indication information.
  • performing self-control according to the collision indication information may be: when the target vehicle determines that it is about to arrive at the location where the collision occurs, control itself to perform at least one of the following operations: change lanes; adjust driving speed; updating the navigation route; turning on the warning lights; and notifying the driver of the collision.
  • the target vehicle can take timely measures to deal with the collision based on the collision indication information, which is beneficial to improve the efficiency of dealing with the collision.
  • Countermeasure 1 Decelerate ⁇ change lanes ⁇ change lanes in sequence. Specifically, vehicle 1 decelerates first, and when the distance between vehicle 1 and vehicle 2 meets the safe lane-changing distance, vehicle 1 performs lane-changing to switch from lane 2 to lane 1, and drives on lane 1 to avoid the lane 2 section BC, after passing point C, change lanes to lane 2 and drive to position D.
  • Countermeasure 2 Update the navigation route to A ⁇ E ⁇ F ⁇ G ⁇ H ⁇ D. Specifically, according to the collision indication information combined with the received traffic flow control information, vehicle 1 determines that the traffic flow of road section EF, road section FG, and road section GH is small and the road conditions are good, so vehicle 1 updates the navigation route and follows the updated navigation route A. ⁇ E ⁇ F ⁇ G ⁇ H ⁇ D to avoid vehicle 1 and vehicle 2 from colliding.
  • Coping strategy 3 Combination of uniform speed and deceleration. Specifically, the vehicle 1 always keeps driving on the lane 2, pays attention to the distance between itself and the collision prediction object vehicle 2 in real time, and flexibly adjusts its real-time speed through the combination of constant speed and deceleration, so that the distance between itself and the vehicle 2 The distance is greater than the safety distance until the vehicle 1 reaches position D.
  • coping strategies 1-3 are just examples, and the target vehicle can also choose other coping strategies to avoid collisions or minimize personal injuries when collisions occur.
  • the self-control is performed according to the collision indication information, which may be: when the probability of the predicted collision occurrence is greater than the first preset threshold, and the time difference between the time when the target vehicle will collide and the current time is smaller than the second preset threshold.
  • the threshold is set, the control of the target vehicle is executed. In this way, the conditions for triggering the control of the target vehicle are further restricted from the two dimensions of the probability of collision occurrence and the time. It controls itself to improve the efficiency of the target vehicle in dealing with collisions.
  • the third preset threshold is less than or equal to the above-mentioned second preset threshold.
  • the target vehicle cannot avoid the collision with the moving object by slowing down slowly and steadily. Collision, in this case, the target vehicle can quickly decelerate or even stop through emergency braking, or the target vehicle can avoid collisions with moving objects by changing lanes, thus ensuring the driving safety of the target vehicle.
  • the target vehicle when the target vehicle performs emergency braking, it can also sound its horn or turn on double flashing lights at the same time to remind surrounding vehicles to keep a distance between them to avoid collisions.
  • the target vehicle's coping strategy is obtained according to the severity of the collision between the target vehicle and each moving object.
  • vehicle 1 compares the severity of each collision and determines that the severity of its own collision with vehicle 3 is higher than the severity of its own collision with vehicle 2.
  • the coping strategy of vehicle 1 can be to prioritize the collision between itself and vehicle 3, In order to avoid collision with the vehicle 3 as much as possible, the risk can be minimized in this way, which is beneficial to improve the safety of the vehicle 1 itself.
  • the target vehicle makes good use of the collision level information. Based on the collision level information, the priority of the collision can be distinguished, which is conducive to quickly determining the order of dealing with the collision, giving priority to the collision with the greatest severity, and maximizing the impact of the target vehicle. Safety during driving.
  • the target vehicle may also determine a countermeasure in combination with multiple pieces of information in the collision indication information.
  • the target vehicle can also combine the information of the remaining collision time and the collision level information to determine a coping strategy.
  • the target vehicle gives priority to the collision with the most urgent time, that is, the earliest collision predicted. When the remaining collision time is sufficient, the target vehicle can Prioritizes collisions of greatest severity.
  • the target vehicle's coping strategy can also be determined according to the attributes of the moving objects. For example, suppose it is predicted that vehicle 1 will collide with the unmanned express vehicle and the car in front at the same time. As an attribute of a person, the coping strategy of vehicle 1 may be to give priority to avoiding a collision with a car with a person in it.
  • S203 Generate a display interface according to the collision indication information.
  • the target vehicle after the target vehicle receives the collision indication information, it can display the collision indication information on the display device of the target vehicle, and the display device can be a vehicle-machine panel, a vehicle display, or a head up display (HUD) system, etc., are not specifically limited here.
  • the display device can be a vehicle-machine panel, a vehicle display, or a head up display (HUD) system, etc., are not specifically limited here.
  • the collision indication information can be presented on the display interface in at least one of the following ways:
  • the moving object that will collide with the target vehicle is presented on the display interface, and the predicted position and orientation of the moving object to be collided relative to the target vehicle itself are intuitively displayed, and the target vehicle is accurately reminded to pay attention to the source of the orientation of the collision risk. It is beneficial to improve the response efficiency of the target vehicle to the event.
  • the predicted remaining collision time information of the target vehicle is dynamically displayed on the display interface, realizing the countdown reminder of the time when the predicted collision will occur, and increasing the sense of urgency that the collision will arrive as time goes by.
  • different colors may also be used according to the length of the remaining collision time, so as to better remind the driver.
  • the driver can be further reminded that the current moment is getting closer and closer to the time when the predicted collision will occur by increasing the flashing frequency of the indicator light, increasing the volume of the prompt sound, etc. Response decisions need to be made in a timely manner.
  • the collision indication information corresponding to the collision whose predicted probability of collision exceeds the fifth preset threshold is displayed on the display interface, and the most likely collision is intuitively displayed, so that the target vehicle can take corresponding strategies in time to deal with the collision and reduce the collision as much as possible. Injuries to people in the event of a collision.
  • the display interface presents collision indication information corresponding to collisions whose grades of predicted collisions exceed the sixth preset threshold, intuitively displaying collisions with a higher degree of danger or more severe collisions, so that users can focus on collisions with a higher degree of danger.
  • Collision indication information corresponding to collisions that occur on the navigation path is presented on the display interface, wherein the collisions that occur on the navigation path include collisions that are predicted to occur with the target vehicle and/or collisions that will occur with other vehicles on the navigation path of the target vehicle. A collision in which the vehicle was not involved. In this way, the target vehicle can be intuitively and effectively reminded of possible future collisions on its navigation path, which improves the safety of the target vehicle during driving.
  • different colors are used to present the collision indication information corresponding to different grades of collisions, which intuitively shows the distribution of collisions of different collision grades in the map, and users can also effectively distinguish different grades of collisions based on colors.
  • different colors are used to present the collision indication information corresponding to different types of collisions, which intuitively shows the distribution of collisions of different types in the map, and users can also effectively distinguish different types of collisions based on colors.
  • the user can also independently select the collision indication information corresponding to the type or level of collision that he is interested in or currently wants to view, so that it can be displayed on the display interface, which improves the user's interactive experience.
  • the user's selection may be generated based on the user's touch operations such as touching, sliding, and dragging on the display interface, or based on the user's voice command.
  • FIG. 8 is a schematic interface diagram of a display device provided by an embodiment of the present application.
  • the left side is the user operation interface
  • the right side is the display interface.
  • a "collision list” is set, wherein each collision under the collision list is a predicted possible collision of the vehicle. It can be seen that “collision 1" and “collision 2" are displayed under the collision list and “Collision 3", which means that the vehicle has three collisions.
  • the user operation interface is also provided with a voice recognition box. When it is detected that the user has input a voice command, the voice command is automatically recognized, and the content of the voice command is displayed in the display area of the display interface on the right.
  • the user's selection operation is to click on the option box of "position information" of collision 2, the position indicated by the position information will be highlighted in the display area shown in FIG. 8 .
  • the user's selection operation is a drag operation of dragging the "collision 2" button to the display area, the time information, probability information, position information, and collision level information corresponding to collision 2 are displayed in the display area shown in FIG. 8 .
  • the user's selection operation can also be "display the detailed information of all possible collisions of the vehicle", “display the detailed information of the earliest collision in the future", “display the closest collision from the current position will occur location” and other voice commands.
  • FIG. 8 is only an exemplary diagram of a display interface of a display device, and this embodiment of the present application does not limit the interface of the display device to only the form shown in FIG. 8 .
  • the collision indication information when presented on the display interface, it may be displayed in combination with a map, for example, the collision indication information is embedded in the map.
  • the collision indication information when the collision indication information is presented on the display interface, all the information of the collision indication information may be presented, or part of the information in the collision indication information may be presented. For example, mark the location where the collision will occur. For another example, in addition to displaying the location of the collision, the predicted moving object colliding with the target vehicle can also be marked and displayed on the map. For another example, the detailed content of the collision indication information can also be displayed in the form of a bullet box, such as multiple items in time information, probability information, collision level information, collision type information, remaining collision time information, and associated dynamic elements.
  • FIG. 9 is a schematic diagram of a display interface provided by an embodiment of the present application.
  • the elliptical area in the road indicates the location where the vehicle will collide, that is, area B, and there is a bullet box next to it showing the detailed information of the collision, specifically showing "the probability information is 0.8 , the time information is 10:15, the location information is area B, the moving object to be collided is vehicle A, and the collision level information is general" and other information.
  • the moving object to be collided that is, the vehicle A
  • the dynamic element associated with the collision can also be marked on the map, for example, the quadrilateral area in the road indicates the range of the dynamic element associated with the collision, which is icy road.
  • the remaining collision time of the own vehicle may also be displayed in FIG. 9 .
  • a countdown progress bar is set on the upper right, wherein the dark part of the progress bar represents the current remaining collision time. As the dark part of the progress bar gradually shortens, the user can be warned that the moment of collision is about to be reached by means of high-frequency flashing lights or voice prompts.
  • the picture shown in FIG. 9 may also be displayed in the display area of the display interface shown in FIG. 8 .
  • moving objects corresponding to collision levels greater than or equal to a preset level threshold may be preferentially displayed.
  • different colors may also be used to distinguish moving objects corresponding to different levels.
  • the trajectory of the target vehicle and the trajectory of other moving objects can also be displayed on the map, so that the position where the collision will occur can be intuitively displayed as the intersection position of each trajectory .
  • the vehicle can obtain reference collision indication information, and the vehicle can timely control its own vehicle to respond to the collision flexibly based on the collision indication information, which not only improves the vehicle's response efficiency to the collision, but also helps to improve Vehicle safety during driving.
  • a display interface can also be obtained, which visually displays the distribution of collisions in the map.
  • the embodiment of the present application also provides an electronic map or an electronic map data structure, the electronic map or the electronic map data structure includes collision indication information, the collision indication information includes first time information and first probability information, and the first time information is used for Indicates the time when the predicted target vehicle will collide, and the first probability information is used to indicate the probability of the predicted collision.
  • the electronic map or the electronic map data is used in the first device, the first device sends the electronic map data including the collision indication information to the second device, and the second device executes traffic scheduling and vehicle control based on the electronic map and so on.
  • the first device is, for example, a network-side device, such as a cloud device; or a road-side device; the second device is, for example, a vehicle.
  • the collision indication information further includes location information, and the location information is used to indicate the location where the collision is predicted to occur.
  • the collision indication information further includes at least one of the following predicted information:
  • the identification information of the moving object that collided with the target vehicle, the collision level information, the collision type information, the remaining collision time information, the identification information of the collision, the identification information of the tile where the collision occurred, the identification information of the road where the collision occurred, and the map that affected the collision The identification information and early warning information of the dynamic elements in ;
  • the collision level information is used to indicate the severity of the collision
  • the collision type information is used to indicate the type of collision
  • the remaining collision time information is used to indicate the time difference between the time when the collision will occur and the current time
  • the warning information is used to indicate the contents to be reminded to the driver or driving system based on the collision.
  • the collision indication information is stored as dynamic layer data in the electronic map.
  • FIG. 10 is a schematic functional structure diagram of a data generation device provided by an embodiment of the present application.
  • the data generation device 30 includes a processing unit 310 and a sending unit 312 .
  • the data generating device 30 can be realized by hardware, software or a combination of software and hardware.
  • the processing unit 310 is configured to obtain collision indication information based on road environment information and predicted trajectory information, the predicted trajectory information is used to indicate the predicted trajectory of multiple moving objects, the multiple moving objects include the target vehicle, and the road environment information is used to indicate The driving environment of the road where the trajectory is located, the collision indication information includes first time information and first probability information, the first time information is used to indicate the time when the target vehicle will be predicted to collide, and the first probability information is used to indicate the probability of the predicted collision ;
  • the sending unit 312 is configured to send collision indication information to the target vehicle.
  • the data generation device 30 can be used to implement the method described in the embodiment of FIG. 3 .
  • the processing unit 310 may be used to execute S101 , S102 and S103 , and the sending unit 312 may be used to execute S104 .
  • the processing unit 310 may also be used to execute S105.
  • each unit in the above embodiment shown in FIG. 10 may be realized by software, hardware, firmware or a combination thereof.
  • the software or firmware includes but is not limited to computer program instructions or codes, and can be executed by a hardware processor.
  • the hardware includes but not limited to various integrated circuits, such as central processing unit (central processing unit, CPU), digital signal processor (digital signal processor, DSP), field-programmable gate array (field-programmable gate array, FPGA) Or application-specific integrated circuit (ASIC).
  • FIG. 11 is a schematic functional structure diagram of a data usage device provided by an embodiment of the present application.
  • the data usage device 40 includes a receiving unit 410 and a processing unit 412 .
  • the data usage device 40 can be realized by hardware, software or a combination of software and hardware.
  • the receiving unit 410 is configured to receive collision indication information, the collision indication information includes first time information and first probability information, the first time information is used to indicate the time when the predicted target vehicle will collide, and the first probability information is used to indicate Predict the probability of collision occurrence; the processing unit 412 is configured to execute the control of the target vehicle according to the collision indication information.
  • the data usage device 40 further includes a display unit 414, and the display unit 414 is configured to generate a display interface according to the collision indication information.
  • the data usage device 40 can be used to implement the method described in the embodiment of FIG. 7 .
  • the receiving unit 410 may be used to perform S201
  • the processing unit 412 may be used to perform S202
  • the display unit 414 may be used to perform S203.
  • each unit in the above embodiment shown in FIG. 11 may be realized by software, hardware, firmware or a combination thereof.
  • the software or firmware includes but is not limited to computer program instructions or codes, and can be executed by a hardware processor.
  • the hardware includes but not limited to various integrated circuits, such as central processing unit (central processing unit, CPU), digital signal processor (digital signal processor, DSP), field-programmable gate array (field-programmable gate array, FPGA) Or application-specific integrated circuit (ASIC).
  • the present application also provides a data processing device.
  • the data processing device 50 includes: a processor 501 , a communication interface 502 , a memory 503 and a bus 504 .
  • the processor 501 , the memory 503 and the communication interface 502 communicate through a bus 504 . It should be understood that the present application does not limit the number of processors and memories in the data processing device 50 .
  • the data processing device 50 may be a generator of the collision indication information, and the data processing device 50 may be, for example, a network-side device or a road-side device.
  • the network side device may be, for example, a server deployed on the network side (such as an application server), or a component or a chip in the server.
  • Roadside equipment can be, for example, devices such as Road Side Unit (Road Side Unit, RSU), Multi-Access Edge Computing (Multi-Access Edge Computing, MEC) or sensors, or components or chips inside these devices, or can be composed of A system-level device composed of RSU and MEC, or a system-level device composed of RSU and sensors, or a system-level device composed of RSU, MEC and sensors.
  • the data processing device 50 may be a user of the collision indication information, and the data processing device 50 may be, for example, a network-side device, a road-side device or a vehicle.
  • the network side device may be, for example, an application server that uses the collision indication information to provide services, or a component or chip in the application server.
  • the roadside equipment can be, for example, devices such as roadside units (Road Side Unit, RSU), multi-access edge computing (Multi-Access Edge Computing, MEC) or sensors that use collision indication information to provide roadside services, or devices inside these devices.
  • RSU roadside units
  • MEC Multi-Access Edge Computing
  • the component or chip of the chip can also be a system-level device composed of RSU and MEC, or a system-level device composed of RSU and sensors, or a system-level device composed of RSU, MEC and sensors.
  • the vehicle may be, for example, a vehicle driven using collision indication information, a device, component or chip in the vehicle, such as an On Board Unit (OBU), which is not specifically limited in this embodiment of the present application.
  • OBU On Board Unit
  • the bus 504 may be a peripheral component interconnect standard (peripheral component interconnect, PCI) bus or an extended industry standard architecture (extended industry standard architecture, EISA) bus or the like.
  • the bus can be divided into address bus, data bus, control bus and so on. For ease of representation, only one line is used in FIG. 12 , but it does not mean that there is only one bus or one type of bus.
  • the bus 504 may include a path for transferring information between various components of the data processing device 50 (eg, memory 503 , processor 501 , communication interface 502 ).
  • the processor 501 may include any one or more of processors such as a central processing unit (central processing unit, CPU), a microprocessor (micro processor, MP), or a digital signal processor (digital signal processor, DSP).
  • processors such as a central processing unit (central processing unit, CPU), a microprocessor (micro processor, MP), or a digital signal processor (digital signal processor, DSP).
  • the memory 503 is used to provide a storage space, in which data such as operating systems and computer programs can be stored.
  • Memory 503 can be random access memory (random access memory, RAM), erasable programmable read only memory (erasable programmable read only memory, EPROM), read-only memory (read-only memory, ROM), or portable read-only memory One or more combinations of memory (compact disc read memory, CD-ROM), etc.
  • the memory 503 may exist independently, or may be integrated inside the processor 501 .
  • Communication interface 502 may be used to provide information input or output to processor 501 .
  • the communication interface 502 can be used to receive data sent from the outside and/or send data to the outside, and can be a wired link interface such as an Ethernet cable, or a wireless link (such as Wi-Fi, Bluetooth, general wireless transmission, etc.) interface.
  • the communication interface 502 may further include a transmitter (such as a radio frequency transmitter, an antenna, etc.) or a receiver coupled with the interface.
  • the data processing device 50 further includes a display 505 , and the display 505 is connected or coupled to the processor 501 through the bus 504 .
  • the display 505 is used to present the collision indication information on the display interface.
  • the display 505 can be a display screen, and the display screen can be a liquid crystal display (Liquid Crystal Display, LCD), an organic or inorganic light-emitting diode (Organic Light-Emitting Diode, OLED), an active matrix organic light-emitting diode panel (Active Matrix/Organic Light Emitting Diode, AMOLED), etc.
  • the display 505 may also be a vehicle panel, a vehicle display, or a head up display system (Head up Display, HUD).
  • the processor 501 in the data processing device 50 is used to read the computer program stored in the memory 503 to execute the aforementioned method, such as the method described in FIG. 3 or FIG. 7 .
  • the data processing device 50 can be one or more modules in the execution subject of the method shown in FIG. 3 , and the processor 501 can be used to read one or more computer programs stored in the memory. , which does the following:
  • the collision indication information is obtained based on the road environment information and the predicted trajectory information, the predicted trajectory information is used to indicate the predicted trajectory of multiple moving objects, the multiple moving objects include the target vehicle, and the road environment information is used to indicate the driving environment of the road where the trajectory is located,
  • the collision indication information includes first time information and first probability information, the first time information is used to indicate the time when the predicted target vehicle will collide, and the first probability information is used to indicate the probability of the predicted collision;
  • the collision indication information is sent to the target vehicle through the sending unit 312 .
  • the data processing device 50 can be one or more modules in the execution subject of the method shown in FIG. 7 , and the processor 501 can be used to read one or more computer Programs that do the following:
  • the collision indication information is received by the receiving unit 410, the collision indication information includes first time information and first probability information, the first time information is used to indicate the time when the predicted target vehicle will collide, and the first probability information is used to indicate the time when the predicted collision will occur probability;
  • control of the target vehicle is performed.
  • the embodiment of the present application also provides a communication system, which includes a data generating device and a data using device, wherein the data generating device can be, for example, the data generating device 30 shown in FIG. 10 , or the data generating device 30 shown in FIG. 12
  • the data processing device 50 that generates the collision indication information; the data usage device may be, for example, the data usage device 40 shown in FIG. 11 , or the data processing device 50 using the collision indication information described in FIG. 12 .
  • the data generation device may be used to execute the method described in the embodiment of FIG. 3 above, and the data usage device may be used to execute the method described in the embodiment of FIG. 7 above.
  • storage medium includes read-only memory (Read-Only Memory, ROM), random access memory (Random Access Memory, RAM), programmable read-only memory (Programmable Read-only Memory, PROM), erasable programmable read-only memory ( Erasable Programmable Read Only Memory, EPROM), One-time Programmable Read-Only Memory (OTPROM), Electrically-Erasable Programmable Read-Only Memory, EEPROM, Compact Disc Read-Only Memory (CD-ROM) or other optical disk storage, magnetic disk storage, tape storage, or any other computer-readable medium that can be used to carry or store data.
  • Read-Only Memory Read-Only Memory
  • RAM Random Access Memory
  • PROM Programmable Read-only Memory
  • PROM Programmable Read-only Memory
  • EPROM Erasable Programmable Read Only Memory
  • OTPROM One-time Programmable Read-Only Memory
  • EEPROM Electrically-Erasable Programmable Read-Only Memory
  • CD-ROM Compact Disc Read-Only Memory
  • the essence of the technical solution of the present application or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of software products.
  • the computer program product is stored in a storage medium, including several instructions. So that a device (which may be a personal computer, a server, or a network device, a robot, a single-chip microcomputer, a chip, a robot, etc.) executes all or part of the steps of the methods described in the various embodiments of the present application.

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Abstract

本申请公开了一种数据生成、使用方法及装置，该方法包括：基于道路环境信息和预测轨迹信息获得碰撞指示信息，预测轨迹信息用于指示预测的多个移动物体(其包括目标车辆)的轨迹，道路环境信息用于指示轨迹所在的道路的行驶环境，碰撞指示信息包括时间信息和概率信息，时间信息用于指示预测目标车辆将发生碰撞的时间，概率信息用于指示碰撞发生的概率；向目标车辆发送碰撞指示信息。实施本申请，能够实现对车辆可能发生的碰撞的准确预测，为车辆提供了有参考意义的碰撞指示信息，有利于提高车辆行驶过程中的安全性。

Description

一种数据生成、使用方法及装置 技术领域
本申请涉及车联网领域，尤其涉及一种数据生成、使用方法及装置。
背景技术
预测的车辆的碰撞信息对车辆具有重要意义。驾驶过程中，车辆基于预测的碰撞信息可以提前调整自身的驾驶策略以及行驶路径，以尽可能避免碰撞的发生或者减小碰撞造成的伤害，对保证车辆的驾驶安全性具有重要作用。但是当前对车辆的碰撞信息的预测无法满足未来智能驾驶和智能交通对准确性、及时性的要求。
发明内容
本申请公开了一种数据生成、使用方法和装置，能够实现对车辆可能发生的碰撞的准确预测，为车辆提供了有参考意义的碰撞指示信息，有利于提高车辆对碰撞的应对效率。
第一方面，本申请提供了一种数据生成方法，该方法包括：基于道路环境信息和预测轨迹信息获得碰撞指示信息，预测轨迹信息用于指示预测的多个移动物体的轨迹，上述多个移动物体包括目标车辆，道路环境信息用于指示轨迹所在的道路的行驶环境，碰撞指示信息包括第一时间信息和第一概率信息，第一时间信息用于指示预测目标车辆将发生碰撞的时间，第一概率信息用于指示预测碰撞发生的概率；向目标车辆发送碰撞指示信息。
其中，第一时间信息指示的时间是预测到的目标车辆可能发生碰撞的时间，并不一定是目标车辆实际发生碰撞的时间。第一时间信息可以指示一个时间点(例如一个时刻)，也可以指示一个时间段。
第一概率信息可以通过(0，1]的浮点数进行表示，第一概率信息指示的概率的值越大，则目标车辆发生该碰撞的可能性就越大。
该方法可用于网络侧设备或路侧设备。其中，网络侧设备例如可以是部署在网络侧的服务器(例如应用服务器或地图服务器)，或者为该服务器中的组件或者芯片。网络侧设备可以部署在云环境或者边缘环境中，本申请实施例不做具体限定。路侧设备例如可以是路侧单元(Road Side Unit，RSU)、多接入边缘计算(Multi-Access Edge Computing，MEC)或者传感器等装置，或者是这些装置内部的组件或者芯片，也可以是由RSU和MEC组成的系统级设备，或者是由RSU和传感器组成的系统级设备，还可以是由RSU、MEC和传感器组成的系统级设备。
上述方法中，通过碰撞指示信息能够为车辆提供未来可能发生的碰撞的预测信息，且在生成碰撞指示信息的过程中不仅考虑了车辆及其周围移动物体的轨迹，还综合考虑了轨迹所在道路的行驶环境，提高了预测的目标车辆可能发生的碰撞的精准性，有利于提高终端出行的安全率。
可选地，行驶环境包括以下内容中的至少一项：天气、能见度、光照强度、道路类型、车道数量、道路平坦程度、道路光滑程度、道路施工情况、交通行为历史统计情况和交通流 量情况。
其中，天气包括但不限于降水量、降雪量、风向、风力等级、雷电指数等参数。
道路类型的划分有多种，例如，基于道路行政等级可分为国道、省道、县道、乡道等，基于道路使用任务、功能、和交通量可分为高速公路、一级公路、二级公路、三级公路等，基于道路使用者的身份可以划分为机动车道、还可以是其他划分方式，在此不作具体限定。
道路平坦程度可以通过坑洼的位置、坑洼的数量、坑洼的深度等参数表示。
道路光滑程度通过路面结冰的厚度、路面结冰位置区域、路面材料等参数表示。
道路施工情况可以通过施工位置、施工面积、施工时长等参数表示。
交通流量情况包括但不限于平均车流量、最大车流量等参数。
交通行为历史统计情况是对移动物体的热点行为区域(或称为高频行为区域)的统计。交通行为历史统计情况包括但不限于行人高频穿行区域、车辆紧急加速区域、车辆紧急减速区域、高频逆向行驶区域、高频闯红灯区域等。
实施上述实现方式，在进行碰撞预测时考虑道路环境因素，可以有效减少环境风险对碰撞预测的影响。例如，路面结冰会对在该路面行驶的车辆的刹车效果不佳进而影响车辆的行驶轨迹，使得碰撞预测不准确，而基于道路环境信息可以校正路面结冰对碰撞预测的影响，有利于提高碰撞预测的精准性。
可选地，碰撞指示信息还包括位置信息，位置信息用于指示预测碰撞将发生的位置。
其中，位置信息可以指示一个地理位置点，也可以指示一个地理区域范围。
位置信息指示的位置是预测到的目标车辆可能发生的碰撞所在的位置，并不一定是目标车辆实际发生碰撞所在的位置。
实施上述实现方式，位置信息从空间维度为目标车辆提供可能发生的碰撞所在的位置，以使目标车辆能及时应对。
可选地，碰撞指示信息还包括下述预测的信息中的至少一项：与目标车辆碰撞的移动物体的标识信息、碰撞等级信息、碰撞类型信息、剩余碰撞时间信息、碰撞的标识信息、碰撞所在的瓦片的标识信息、碰撞所在的道路的标识信息、影响碰撞的地图中动态要素的标识信息和预警信息；其中，碰撞等级信息用于指示碰撞的严重程度，碰撞类型信息用于指示碰撞的类型，剩余碰撞时间信息用于指示碰撞将发生的时间距离当前时间的时间差，预警信息用于指示基于碰撞向驾驶员或驾驶系统提醒的内容。
与目标车辆碰撞的移动物体的标识信息是碰撞指示信息的一种可选信息。基于目标车辆待碰撞的移动物体的标识信息，有效提醒目标车辆注意该移动物体的运动状态，使得目标车辆可以及时作出应对决策，以避免碰撞的发生。
碰撞等级信息是碰撞指示信息的一种可选信息。碰撞等级信息对碰撞的严重程度进行阶梯量化，能有效区分不同危险程度的碰撞，有利于分清轻重缓急。
碰撞类型信息是碰撞指示信息的一种可选信息。碰撞类型信息使得目标车辆能够基于碰撞的类型更迅速、更有针对性地应对碰撞事件，提高了碰撞的应对效率。例如，碰撞类型信息可以从碰撞方位对碰撞进行分类描述，也可以从碰撞原因对碰撞进行分类描述，具体分类的方式还有多种可能，本申请在此不做限定。
剩余碰撞时间信息是碰撞指示信息的一种可选信息。基于剩余碰撞时间信息能倒计时式提醒驾驶员或驾驶系统预测的碰撞即将到来，实现碰撞的及时预警。
影响碰撞的地图中动态要素的标识信息是碰撞指示信息的一种可选信息。基于影响碰撞的地图中动态要素的标识信息，可以快速查找该碰撞关联的动态要素。当检测该碰撞关联的动态要素发生变化时，可以及时更新目标车辆的碰撞指示信息，提高了碰撞指示信息的准确率。例如，路面结冰是一种动态要素，其可能影响目标车辆的碰撞预测，则将该路面结冰的标识作为目标车辆的碰撞指示信息的内容。
预警信息是碰撞指示信息的一种可选信息。基于预警信息可及时提醒驾驶员预测到的碰撞，有利于提高车辆行驶的安全性。
碰撞的标识信息、碰撞所在的瓦片的标识信息以及碰撞所在的道路的标识信息均是碰撞指示信息的可选信息。将碰撞与地图瓦片的标识关联，可以基于地图瓦片的标识实现碰撞的快速索引。将碰撞与道路的标识关联，可以基于道路的标识实现碰撞的快速索引。由此，有效提高了碰撞的查询搜索效率。
可选地，该方法还包括：在多个移动物体的轨迹发生变化时和/或影响碰撞的地图中动态要素发生变化时，更新碰撞指示信息或者删除碰撞指示信息。
实施上述实现方式，当确定有移动物体的轨迹发生变化时，可以基于移动物体更新后的轨迹重新进行碰撞预测；当影响碰撞的地图中动态要素发生变化时，基于动态要素的标识与碰撞的标识之间的映射关系重新进行碰撞预测。如此，可以实现碰撞指示信息的联动更新，或者，碰撞指示信息的删除。碰撞指示信息的删除，意味着预测到对应的碰撞将不发生。
可选地，该方法还包括：根据碰撞指示信息，执行交通监控、交通调度或对目标车辆的控制。
实施上述实现方式，可以基于碰撞指示信息提供多种应用服务，例如可以是交通监控、交通调度等宏观上的调控服务，也可以是对目标车辆的控制等定制性的专有服务。
可选地，该方法还包括：确定目标车辆即将到达碰撞将发生的位置时，控制目标车辆执行以下操作中的至少一项：
变换车道；
调整行驶速度；
更新导航路线；
开启警示灯；和
向驾驶员提示该碰撞。
实施上述实现方式，在确定车辆即将达到碰撞将发生的位置时，为车辆提供了多种应对策略，例如，变换车道、调整行驶速度、更新导航路线、开启警示灯、向驾驶员提示该碰撞等，可以选取上述任意一种也可以多种组合对目标车辆进行控制，以使目标车辆能及时准确地应对碰撞，提高目标车辆出行的安全性。
可选地，向目标车辆发送碰撞指示信息，包括：在满足下述至少一个条件时，向目标车辆发送碰撞指示信息：
预测碰撞发生的概率大于第一阈值；
目标车辆当前的位置与预测碰撞将发生的位置之间的最小距离小于第二阈值；
预测碰撞将发生的位置所属的道路为目标车辆所在的道路；和
预测碰撞将发生的位置所属的瓦片为目标车辆所在的瓦片。
实施上述实现方式，向目标车辆发送碰撞指示信息，即目标车辆作为碰撞指示信息的使 用者，在此情况下，作为使用者的目标车辆需满足上述条件对车辆所在位置的限定和/或对碰撞的概率的限定，使目标车辆获取与其关联性较大的碰撞指示信息，如此，可以节省数据传输流量。
可选地，道路环境信息是基于地图中的动态图层数据和静态图层数据获得，预测轨迹信息是基于多个移动物体的运动状态数据和驾驶员信息获得。
移动物体的运动状态数据包括移动物体在历史多个时刻的位置坐标、速度、加速度、航向等参数。驾驶员信息包括但不限于驾驶员的驾驶习惯、驾驶员的实时状态等，驾驶习惯例如可以是频繁并线、超速行驶、弯道超车、抢黄灯、不开快车、礼让非机动车、夜间合理运用灯光、不疲劳驾驶等，驾驶员的实时状态例如可以是亢奋、平和、生气、疲劳、睡着、昏迷等。
进一步地，可以从地图的静态图层数据和动态图层数据中提取道路环境信息，静态图层数据例如可以指示道路类型、车道数量、道路平坦程度(例如，坑洼的深度、位置信息、面积、数量等)等不频繁发生变化的道路状态；动态图层数据例如可以指示随时间变化较频繁的降水量、降雪量、能见度、光照强度、风向、风力、雷电指数等天气情况，还可以指示路面光滑程度(例如，是否有结冰、结冰厚度、结冰位置区域等)、路面施工信息(例如，是否有施工、施工位置、施工时长等)、道路积水情况、道路落叶覆盖情况等较频繁发生变化的道路状态。
实施上述实现方式，地图数据中的静态图层数据和动态图层数据，以及移动物体的运动状态数据和驾驶员信息等为碰撞指示信息的获取提供了可能，碰撞指示信息能够为目标车辆提供具有参考意义的碰撞的预测信息。
可选地，该方法还包括：将碰撞指示信息作为地图数据进行存储。
例如，碰撞指示信息可以作为地图数据的动态图层数据进行存储，碰撞指示信息所在的动态图层可以与地图中的其他至少一个图层(例如，静态图层、仅承载了天气信息的动态图层等)叠加显示，也可以单独显示，在此不作具体限定。
实施上述实现方式，碰撞指示信息增加了地图数据的丰富程度。
可选地，基于道路环境信息和预测轨迹信息，获得碰撞指示信息，包括：根据预测轨迹信息获得碰撞预测结果，碰撞预测结果包括第二时间信息和第二概率信息；输入道路环境信息至人工智能AI模型，输出风险区域信息，风险区域信息包括风险区域的位置信息和风险区域的风险等级；根据风险区域信息校正碰撞预测结果，获得碰撞指示信息。
可以理解，由于环境风险对碰撞预测有影响，在根据预测轨迹信息获得碰撞预测结果后，基于风险区域信息(即表征了环境风险)对碰撞预测结果进行修正以获得碰撞指示信息，考量了环境风险对碰撞预测的影响，提高了预测的目标车辆的碰撞的精准性。
第二方面，本申请提供了一种数据使用方法，应用于目标车辆，该方法包括：获取碰撞指示信息，碰撞指示信息包括第一时间信息和第一概率信息，第一时间信息用于指示预测目标车辆将发生碰撞的时间，第一概率信息用于指示预测碰撞发生的概率；根据碰撞指示信息，执行对目标车辆的控制。
该方法应用于目标车辆，目标车辆例如可以是使用碰撞指示信息进行驾驶的车辆、车辆内的装置、部件或芯片，例如车载单元(On Board Unit，OBU)，在此不作具体限定。
其中，第一时间信息指示的时间是预测到的目标车辆可能发生碰撞的时间，并不一定是 目标车辆实际发生碰撞的时间。第一时间信息可以指示一个时间点(例如一个时刻)，也可以指示一个时间段。
上述方法中，目标车辆通过获取碰撞指示信息可以预先知晓碰撞发生的概率以及碰撞可能发生的时间，从而根据碰撞指示信息能够及时调整自身以应对碰撞，不仅提高了目标车辆对碰撞的应对效率，还提高了目标车辆在驾驶过程中的安全性。
可选地，碰撞指示信息还包括位置信息，位置信息用于指示预测碰撞将发生的位置。
位置信息指示的位置可以是一个地理位置位置点，也可以是一个地理范围区域。位置信息指示的位置是预测到的目标车辆可能发生的碰撞所在的位置，并不一定是目标车辆实际发生碰撞所在的位置。
位置信息可以表示为基于任意坐标系获得的坐标值，例如，坐标系可以是世界大地坐标系(Word Geodetic System 1984，WGS84)、自然坐标系、道路坐标系等。
可选地，碰撞指示信息还包括下述信息中的至少一项：
与目标车辆碰撞的移动物体的标识信息、碰撞等级信息、碰撞类型信息、剩余碰撞时间信息、碰撞的标识信息、碰撞所在的瓦片的标识信息、碰撞所在的道路的标识信息、影响碰撞的地图中动态要素的标识信息和预警信息；
其中，碰撞等级信息用于指示碰撞的严重程度，碰撞类型信息用于指示碰撞的类型，剩余碰撞时间信息用于指示碰撞将发生的时间距离当前时间的时间差，预警信息用于指示基于碰撞向驾驶员或驾驶系统提醒的内容。
有关上述各个信息的有益效果具体可参考上述第一方面相应内容的有益效果的说明，为了说明书的简洁，在此不再赘述。
可选地，根据碰撞指示信息，执行对目标车辆的控制，包括：
确定目标车辆即将到达碰撞将发生的位置时，控制目标车辆执行以下操作中的至少一项：
变换车道；
调整行驶速度；
更新导航路线；
开启警示灯；和
向驾驶员提示该碰撞。
实施上述实现方式，目标车辆在确定自身即将到达碰撞将发生的位置时，可以控制自身采取多种措施应对碰撞，从而目标车辆可以灵活应对未来可能发生的碰撞，提高了目标车辆对碰撞的应对效率。
可选地，根据碰撞指示信息，执行对目标车辆的控制，包括：在预测碰撞发生的概率大于第一预设阈值，且在目标车辆将发生碰撞的时间距离当前时间的时间差小于第二预设阈值时，执行对目标车辆的控制。
其中，执行对目标车辆的控制包括以下操作中的至少一项：变换车道、调整行驶速度、更新导航路线、开启警示灯和向驾驶员提示该碰撞。
实施上述实现方式，从概率和时间两个维度上对触发控制目标车辆的条件进行了限制，在碰撞的发生具有较大的可能性且目标车辆的剩余碰撞时间满足条件时，目标车辆才对自身进行控制，提高了目标车辆应对碰撞的效率。
可选地，该方法还包括：在目标车辆将发生碰撞的时间距离当前时间的时间差小于第三 预设阈值和/或目标车辆的当前位置距离碰撞发生的位置之间的距离小于第四预设阈值时，控制目标车辆在当前车道紧急制动或者变道。
可选地，第三预设阈值小于等于上述第二预设阈值。
可以理解，当碰撞将发生的时间距离当前时间的剩余时间较短，或者，目标车辆的当前位置距离碰撞将发生的位置较近时，目标车辆已无法通过缓慢平稳降速避开与移动物体的碰撞，在此情况下，目标车辆可以通过在当前车道紧急制动实现快速降速甚至停车，或者，目标车辆可以通过变道避开与移动物体的碰撞，如此，保证了目标车辆的驾驶安全性。
可选地，该方法还包括：在预测到有多个移动物体同时与目标车辆发生碰撞时，根据目标车辆与每个移动物体碰撞的严重程度，获得目标车辆的应对策略。
例如，预测到目标车辆将同时与两个移动物体(即移动物体1和移动物体2)发生碰撞，其中，目标车辆与移动物体1碰撞的严重程度为“轻微”，目标车辆与移动物体2碰撞的严重程度为“重大”，为了将风险或损失降到最小，目标车辆的应对策略可以是：优先应对与移动物体2的碰撞，尽可能采取措施避免与移动物体2的碰撞的发生。
实施上述实现方式，目标车辆基于自身与移动物体碰撞的严重程度确定应对碰撞的先后顺序，即目标车辆较好地使用了碰撞等级信息，实现了灵活应对预测到的碰撞，提高了目标车辆自身的安全性。
可选地，该方法还包括：通过以下方式中的至少一种在目标车辆的显示界面上呈现碰撞指示信息：
呈现预测的将与目标车辆发生碰撞的移动物体；
呈现预测碰撞发生的时间距离当前时间的时间差；
呈现预测发生碰撞的概率超过第五预设阈值的碰撞对应的碰撞指示信息；
呈现预测发生碰撞的等级超过第六预设阈值的碰撞对应的碰撞指示信息；
呈现预测的在导航路径上发生的碰撞对应的碰撞指示信息；
呈现用户选择的等级或用户选择的类型的碰撞对应的碰撞指示信息；
用不同颜色呈现不同等级的碰撞对应的碰撞指示信息；和
用不同颜色呈现不同类型的碰撞对应的碰撞指示信息。
其中，在显示界面上呈现预测的将与目标车辆碰撞的移动物体，直观显示了该移动物体相对于目标车辆自身的位置方位，准确提醒目标车辆注意碰撞风险的方位来源，使得目标车辆更有针对性地作出应对措施。例如，目标车辆通过显示界面知晓待碰撞的移动物体位于自己的左后方，则目标车辆可以时刻关注左后方的移动物体的运行状态，及时采取应对措施。
在显示界面上呈现预测碰撞发生的时间距离当前时间的时间差，也就是在显示界面呈现了预测的剩余碰撞时间信息，实现了预测碰撞将发生的时间的倒计时式提醒，增加了随着时间流逝碰撞即将到达的紧迫感。
在显示界面上对呈现的碰撞的概率进行限制，直观地显示了最有可能发生的碰撞，以提醒驾驶员当前重点关注的碰撞。
在显示界面上对呈现的碰撞的等级进行限制，直观地显示了危险程度较高或者较为严重的碰撞，以使用户重点关注危险程度较高的碰撞。
在显示界面上呈现预测的在导航路径上发生的碰撞对应的碰撞指示信息，其中，在导航路径上发生的碰撞包括预测目标车辆将发生的碰撞和/或其他车辆在目标车辆的导航路径上 将发生的但目标车辆未参与的碰撞。如此可以直观、有效提醒目标车辆在其导航路径上未来可能发生的碰撞，提高了目标车辆在驾驶过程中的安全性。
在显示界面上用户还可以自主选择感兴趣或者当前想要查看的类型或等级的碰撞对应的碰撞指示信息，使其在显示界面上显示，提高了用户的交互体验感。
在显示界面上用不同颜色呈现不同等级的碰撞所对应的碰撞指示信息，直观地展示了不同碰撞等级的碰撞在地图中的分布，用户基于颜色也可以有效区分不同等级的碰撞。
在显示界面上用不同颜色呈现不同类型的碰撞所对应的碰撞指示信息，直观地展示了不同碰撞类型的碰撞在地图中的分布，用户基于颜色也可以有效区分不同类型的碰撞。
在一些可能的实施例中，在显示界面对碰撞指示信息进行呈现时，可以呈现碰撞指示信息中的全部内容，也可以呈现碰撞指示信息中的部分内容。例如，仅呈现预测的与目标车辆发生碰撞的移动物体，也可以呈现该移动物体和预测的目标车辆将发生碰撞的位置等，在此不作具体限定。
在一些可能的实施例中，在显示界面上呈现碰撞指示信息时，碰撞指示信息可以嵌入地图中进行显示，该地图可以是目标车辆在本地存储的高精地图、标精地图或其他类型的地图，在此不作具体限定。
第三方面，本申请提供了一种数据生成装置，该装置包括：获取单元，用于基于道路环境信息和预测轨迹信息获得碰撞指示信息，预测轨迹信息用于指示预测的多个移动物体的轨迹，上述多个移动物体包括目标车辆，道路环境信息用于指示轨迹所在的道路的行驶环境，碰撞指示信息包括第一时间信息和第一概率信息，第一时间信息用于指示预测目标车辆将发生碰撞的时间，第一概率信息用于指示预测碰撞发生的概率；发送单元，用于向目标车辆发送碰撞指示信息。
可选地，行驶环境包括以下内容中的至少一项：天气、能见度、光照强度、道路类型、车道数量、道路平坦程度、道路光滑程度、道路施工情况、交通行为历史统计情况和交通流量情况。
可选地，碰撞指示信息还包括位置信息，位置信息用于指示预测碰撞将发生的位置。
可选地，碰撞指示信息还包括下述预测的信息中的至少一项：与目标车辆碰撞的移动物体的标识信息、碰撞等级信息、碰撞类型信息、剩余碰撞时间信息、碰撞的标识信息、碰撞所在的瓦片的标识信息、碰撞所在的道路的标识信息、影响碰撞的地图中动态要素的标识信息和预警信息；其中，碰撞等级信息用于指示碰撞的严重程度，碰撞类型信息用于指示碰撞的类型，剩余碰撞时间信息用于指示碰撞将发生的时间距离当前时间的时间差，预警信息用于指示基于碰撞向驾驶员或驾驶系统提醒的内容。
可选地，该装置还包括处理单元，用于：在多个移动物体的轨迹发生变化时和/或影响碰撞的地图中动态要素发生变化时，更新碰撞指示信息或者删除碰撞指示信息。
可选地，处理单元还用于：根据碰撞指示信息，执行交通监控、交通调度或对目标车辆的控制。
可选地，处理单元还用于：确定目标车辆即将到达碰撞将发生的位置时，控制目标车辆执行以下操作中的至少一项：
变换车道；
调整行驶速度；
更新导航路线；
开启警示灯；和
向驾驶员提示该碰撞。
可选地，发送单元具体用于在满足下述至少一个条件时，向目标车辆发送碰撞指示信息：
预测碰撞发生的概率大于第一阈值；
目标车辆当前的位置与预测碰撞将发生的位置之间的最小距离小于第二阈值；
预测碰撞将发生的位置所属的道路为目标车辆所在的道路；和
预测碰撞将发生的位置所属的瓦片为目标车辆所在的瓦片。
可选地，道路环境信息是基于地图中的动态图层数据和静态图层数据获得，预测轨迹信息是基于多个移动物体的运动状态数据和驾驶员信息获得。
可选地，该装置还包括存储单元，用于：将碰撞指示信息作为地图数据进行存储。
可选地，获取单元，具体用于：根据预测轨迹信息获得碰撞预测结果，碰撞预测结果包括第二时间信息和第二概率信息；输入道路环境信息至人工智能AI模型，输出风险区域信息，风险区域信息包括风险区域的位置信息和风险区域的风险等级；根据风险区域信息校正碰撞预测结果，获得碰撞指示信息。
第四方面，本申请提供了一种数据使用装置，该装置包括：接收单元，获取碰撞指示信息，碰撞指示信息包括第一时间信息和第一概率信息，第一时间信息用于指示预测目标车辆将发生碰撞的时间，第一概率信息用于指示预测碰撞发生的概率；处理单元，用于根据碰撞指示信息，执行对目标车辆的控制。
可选地，碰撞指示信息还包括位置信息，位置信息用于指示预测碰撞将发生的位置。
可选地，碰撞指示信息还包括下述信息中的至少一项：
与目标车辆碰撞的移动物体的标识信息、碰撞等级信息、碰撞类型信息、剩余碰撞时间信息、碰撞的标识信息、碰撞所在的瓦片的标识信息、碰撞所在的道路的标识信息、影响碰撞的地图中动态要素的标识信息和预警信息；
其中，碰撞等级信息用于指示碰撞的严重程度，碰撞类型信息用于指示碰撞的类型，剩余碰撞时间信息用于指示碰撞将发生的时间距离当前时间的时间差，预警信息用于指示基于碰撞向驾驶员或驾驶系统提醒的内容。
可选地，处理单元，具体用于：
确定目标车辆即将到达碰撞发生的位置时，控制目标车辆执行以下操作中的至少一项：
变换车道；
调整行驶速度；
更新导航路线；
开启警示灯；和
向驾驶员提示碰撞。
可选地，处理单元，具体用于：在预测碰撞发生的概率大于第一预设阈值，且在目标车辆将发生碰撞的时间距离当前时间的时间差小于第二预设阈值时，执行对目标车辆的控制。
可选地，处理单元，还用于：在目标车辆将发生碰撞的时间距离当前时间的时间差小于第三预设阈值和/或目标车辆的当前位置距离碰撞发生的位置之间的距离小于第四预设阈值时，控制目标车辆在当前车道紧急制动或者变道。
可选地，处理单元，还用于：在预测到有多个移动物体同时与目标车辆发生碰撞时，根据目标车辆与每个移动物体碰撞的严重程度，获得目标车辆的应对策略。
可选地，该装置还包括显示单元，显示单元用于通过以下方式中的至少一种在目标车辆的显示界面上呈现碰撞指示信息：
呈现预测的将与目标车辆发生碰撞的移动物体；
呈现预测碰撞发生的时间距离当前时间的时间差；
呈现预测发生碰撞的概率超过第五预设阈值的碰撞对应的碰撞指示信息；
呈现预测发生碰撞的等级超过第六预设阈值的碰撞对应的碰撞指示信息；
呈现预测的在导航路径上发生的碰撞对应的碰撞指示信息；
呈现用户选择的等级或用户选择的类型的碰撞对应的碰撞指示信息；
用不同颜色呈现不同等级的碰撞对应的碰撞指示信息；和
用不同颜色呈现不同类型的碰撞对应的碰撞指示信息。
第五方面，本申请提供了一种数据生成装置，该装置包含至少一个处理器以及通信接口，所述通信接口用于为所述至少一个处理器提供信息输入和/或输出。该装置用于实现第一方面或者第一方面任一可能的实施例中的所述方法。
第六方面，本申请提供了一种数据使用装置，该装置包含至少一个处理器以及通信接口，所述通信接口用于为所述至少一个处理器提供信息输入和/或输出。该装置用于实现第二方面或者第二方面任一可能的实施例中的所述方法。
第七方面，本申请提供了一种计算机可读存储介质，包括计算机指令，当所述计算机指令在被处理器运行时，实现上述第一方面或者第一方面的任一可能的实现方式中的方法。
第八方面，本申请提供了一种计算机可读存储介质，包括计算机指令，当所述计算机指令在被处理器运行时，实现上述第二方面或者第二方面的任一可能的实现方式中的方法。
第九方面，本申请提供了一种计算机程序产品，当该计算机程序产品被处理器执行时，实现上述第一方面或者第一方面的任一可能的实施例中的所述方法。该计算机程序产品，例如可以为一个软件安装包，在需要使用上述第一方面的任一种可能的设计提供的方法的情况下，可以下载该计算机程序产品并在处理器上执行该计算机程序产品，以实现第一方面或者第一方面的任一可能的实施例中的所述方法。
第十方面，本申请提供了一种计算机程序产品，当该计算机程序产品被处理器执行时，实现上述第二方面或者第二方面的任一可能的实施例中的所述方法。该计算机程序产品，例如可以为一个软件安装包，在需要使用上述第二方面的任一种可能的设计提供的方法的情况下，可以下载该计算机程序产品并在处理器上执行该计算机程序产品，以实现第二方面或者第二方面的任一可能的实施例中的所述方法。
第十一方面，本申请提供了一种车辆，该车辆包括如上述第四方面或第四方面的任一可能的实现方式的数据使用装置，或者，包括如上述第六方面或第六方面的任一可能的实现方式的数据使用装置。
第十二方面，本申请提供了一种电子地图，该电子地图包括碰撞指示信息，碰撞指示信息包括时间信息概率信息，其中，时间信息用于指示预测目标车辆将发生碰撞的时间，概率信息用于指示预测碰撞发生的概率。
可选地，该碰撞指示信息还包括位置信息，位置信息用于指示预测碰撞将发生的位置。
可选地，碰撞指示信息还包括下述预测的信息中的至少一项：与目标车辆碰撞的移动物体的标识信息、碰撞等级信息、碰撞类型信息、剩余碰撞时间信息、碰撞的标识信息、碰撞所在的瓦片的标识信息、碰撞所在的道路的标识信息、影响碰撞的地图中动态要素的标识信息和预警信息；其中，碰撞等级信息用于指示碰撞的严重程度，碰撞类型信息用于指示碰撞的类型，剩余碰撞时间信息用于指示碰撞将发生的时间距离当前时间的时间差，预警信息用于指示基于碰撞向驾驶员或驾驶系统提醒的内容。
所述电子地图为地图产品，具体来说，可以是承载碰撞指示信息的地图数据产品，如地图更新数据包，或者可以为加载碰撞指示信息的地图应用产品，如可安装于车辆或便携终端上的地图应用程序，或者还可以为以图形和/或文字形式等呈现碰撞指示信息的地图展示产品，如电子导航仪。
第十三方面，本申请提供了一种计算机可读存储介质，用于存储上述第十二方面以及第十二方面任一可能的实施例中所述的电子地图。
第十四方面，本申请提供了一种电子信息，该电子信息承载碰撞指示信息，碰撞指示信息包括时间信息和概率信息，时间信息用于指示预测目标车辆将发生碰撞的时间，概率信息用于指示预测碰撞发生的概率。
可选地，该电子信息是电、磁或电磁信号的集合，通过电、磁或电磁这种载体的形式承载地图信息。
第十五方面，提供一种计算机可读存储介质，该计算机可读存储介质具备信息输入接口，该信息输入接口能够接收上述第十四方面或第十四方面的任意一种可能的实现方式所描述的电子信息，并将该电子信息承载的碰撞指示信息存储于该计算机可读存储介质中。
上述第二方面至第十五方面的技术效果与上述第一方面相同，在此不再赘述。
附图说明
图1是本申请实施例提供的一种场景示意图；
图2是本申请实施例提供的一种系统架构的示意图；
图3是本申请实施例提供的一种数据生成方法的流程图；
图4是本申请实施例提供的一种碰撞预测系统的框架示意图；
图5是本申请实施例提供的一种碰撞的位置信息的表达示意图；
图6A是本申请实施例提供的一种碰撞指示信息的数据结构示意图；
图6B是本申请实施例提供的一种碰撞指示信息的数据结构示意图；
图7是本申请实施例提供的一种数据使用方法的流程图；
图8是本申请实施例提供的一种显示装置的界面示意图；
图9是本申请实施例提供的一种显示界面的示意图；
图10是本申请本实施例提供的一种数据生成装置的功能结构示意图；
图11是本申请本实施例提供的一种数据使用装置的功能结构示意图；
图12是本申请本实施例提供的一种数据处理装置的功能结构示意图。
具体实施方式
需要说明的是，本申请中采用诸如“第一”、“第二”的前缀词，仅仅为了区分不同的描述对象，对被描述对象的位置、顺序、优先级、数量或内容等没有任何限定作用。例如，被描述对象为“字段”，则“第一字段”和“第二字段”中“字段”之前的序数词并不限制“字段”之间的位置或顺序，“第一”和“第二”并不限制其修饰的“字段”是否在同一个消息中，也不限制“第一字段”和“第二字段”的先后顺序。再如，被描述对象为“等级”，则“第一等级”和“第二等级”中“等级”之前的序数词并不限制“等级”之间的优先级。再如，被描述对象的数量并不受前缀词的限制，可以是一个或者多个，以“第一设备”为例，其中“设备”的数量可以是一个或者多个。此外，不同前缀词修饰的对象可以相同或不同，例如，被描述对象为“设备”，则“第一设备”和“第二设备”可以是同一个设备、相同类型的设备或者不同类型的设备；再如，被描述对象为“信息”，则“第一信息”和“第二信息”可以是相同内容的信息或者不同内容的信息。总之，本申请实施例中对用于区分描述对象的前缀词的使用不构成对所描述对象的限制，对所描述对象的陈述参见权利要求或实施例中上下文的描述，不应因为使用这种前缀词而构成多余的限制。
需要说明的是，本申请实施例中采用诸如“a1、a2、……和an中的至少一项(或至少一个)”等的描述方式，包括了a1、a2、……和an中任意一个单独存在的情况，也包括了a1、a2、……和an中任意多个的任意组合情况，每种情况可以单独存在。例如，“a、b和c中的至少一项”的描述方式，包括了单独a、单独b、单独c、a和b组合、a和c组合、b和c组合，或abc三者组合的情况。
为了便于理解，下面先对本申请实施例可能涉及的相关术语等进行介绍。
在一种地图结构中，地图可以包括多个图层(Layer)，图层可理解为地图数据集，地图数据集中的数据以设定的数据结构进行组织。图层中的数据能够描述多种来源的地图要素。根据地图要素的时变性，地图要素可分为元素和事件两种类型：元素是比较固定、变化小或者更新周期较长的地图要素，例如道路拓扑、建筑物位置、车道线、车道方向或交通基础设施布局等；事件是具有较强时变特性的地图要素，例如，交通事故、天气变化、道路积冰、道路施工或交通拥堵情况等。对于某个地图描述对象而言，其可能兼具时变性的地图要素和基本不随时间变化的地图要素，即该描述对象既与地图中的元素相关，也与地图中的事件相关。例如，针对某一个车道，该车道的地理位置为地图中的元素，该车道的交通流量为地图中的事件。
在地图中，元素和事件可以被记录于不同的图层，关于元素的信息由地图中的静态图层承载，关于事件的信息由地图中的动态图层承载。地图可以包括至少一个静态图层，进一步地还可以包括多个动态图层。例如，地图包括静态图层1和两个动态图层(分别为动态图层1和动态图层2)，静态图层1中记录了建筑物、道路、树木、交通灯和道路指示牌的地理分布，动态图层1记录了车道的实时限速情况、交通施工情况和人流车流情况，动态图层2记录了天气情况，例如晴天、下雨、下雪、刮风、温度或湿度等。
地图中静态图层中的数据可称作元素或静态要素，地图中动态图层中的数据可称作事件或动态要素。
参见图1，图1是本申请实施例提供的一种应用场景示意图。在图1中，假设车辆1欲从位置A到达位置D，车辆1通过感知周围环境获得周围车辆的预测轨迹信息，并结合自身的预测轨迹信息进行碰撞预测分析。假设车辆1基于车辆2的运动状态获得车辆2未来的轨迹信息，结合自身的轨迹信息进行碰撞预测分析确定车辆1与车辆2在区域2内存在碰撞风 险。但实际上路段BC存在路面结冰、限速、路面坑洼等因素，导致在路段BC上行驶的车辆的行驶速度、刹车效果会受到影响，使得车辆1与车辆2实际发生碰撞的位置为图1中的区域1，其与预测的区域2存在位置偏差。也就是说，车辆1预测的碰撞区域不准确，进一步地，车辆1基于区域2作出的驾驶决策也是不准确的。另外，当车辆1的周围具有较多数量的车辆时，对车辆1的计算力也提出了更高的要求。可以看出，由于当前车辆获得的预测的碰撞信息准确率低，也降低了驾驶决策的准确率。
针对上述问题，本申请实施例提出一种数据处理方法，能够实现对车辆可能发生的碰撞的准确预测，为车辆提供了具有参考意义的碰撞指示信息，有利于提高车辆在驾驶过程中的安全性。
下面将结合附图，对本申请中的技术方案进行描述。
参见图2，图2示例性地给出了本申请实施例的一种系统架构图。该系统用于生成碰撞指示信息，碰撞指示信息包括时间信息和概率信息，时间信息用于指示预测目标车辆将发生碰撞的时间，概率信息用于指示预测该碰撞发生的概率。
如图2所示，该系统包括网络侧设备、路侧设备和车辆中的至少一项。其中，车辆可以分别与网络侧设备、路侧设备以无线的方式进行通信，网络侧设备与路侧设备可以通过无线或者有线的方式进行通信。
其中，网络侧设备是具有计算功能的设备，例如可以是部署在网络侧的服务器(例如应用服务器)，或者为该服务器中的组件或者芯片。网络侧设备可以部署在云环境，即云计算服务器，或者网络侧设备也可以部署在边缘环境中，即边缘计算服务器。网络侧设备可以是集成的一个设备，也可以是分布式的多个设备，本申请实施例不做具体限定。
路侧设备例如可以是路侧单元(Road Side Unit，RSU)、多接入边缘计算(Multi-Access Edge Computing，MEC)或者传感器等装置，或者是这些装置内部的组件或者芯片，也可以是由RSU和MEC组成的系统级设备，或者是由RSU和传感器组成的系统级设备，还可以是由RSU、MEC和传感器组成的系统级设备。
车辆例如可以是使用碰撞指示信息进行驾驶的车辆，也可以是车辆内的装置、部件或芯片等，例如车载单元(On Board Unit，OBU)，本申请实施例不做具体限定。
碰撞指示信息可以由网络侧设备或路侧设备生成。
以网络侧设备生成碰撞指示信息为例，网络侧设备先获取道路环境信息和指示了预测的多个移物体的轨迹的预测轨迹信息，其中，多个移动物体包括目标车辆，并根据预测轨迹信息和道路环境信息，获得上述碰撞指示信息；向目标车辆发送碰撞指示信息。在一些可能的实施例中，网络侧设备还可以根据碰撞指示信息，执行交通监控、交通调度或者对目标车辆的控制。也就是说，网络侧设备既可以作为碰撞指示信息的生成者和发布者，也可以作为碰撞指示信息的使用者。
其中，道路环境信息用于指示轨迹所在的道路的行驶环境，行驶环境包括但不限于天气、能见度、光照强度、道路类型、车道数量、道路平坦程度、道路光滑程度、道路施工情况、交通违规历史统计情况和交通流量情况等。道路环境信息可以来源于地图中动态图层数据和静态图层数据，该地图可以是高精地图、标精地图或者其他类型的地图，本申请实施例在此不作具体限定。
在一些可能的实施例中，碰撞指示信息也可以以地图图层的形式存在。例如，碰撞指示信息以动态图层数据的方式进行存储。
在一些可能的实施例中，车辆也可以生成碰撞指示信息，供自身使用或者发送给其他设备使用。在此情况下，车辆中存储有地图，该地图可以是高精地图、标精地图或者其他类型的地图。车辆可从地图中获取道路环境信息，以及根据多个移动物体的运动状态数据和驾驶员信息获取上述预测轨迹信息，并根据道路环境信息和预测轨迹信息获得碰撞指示信息。
发布碰撞指示信息时，可以由网络侧设备通过无线网络，例如蜂窝通信网络，将碰撞指示信息发布到车辆；或者，可以由网络侧设备将碰撞指示信息发布到其它设备，由其它设备转发给车辆，转发可以通过V2X(Vehicle to Everything，车联网)进行。例如，云端的服务器向订阅了碰撞预测服务的目标车辆发送碰撞指示信息，既可以通过包括基站在内的蜂窝通信网络进行发布，又可以通过V2X通信由路侧设备向该目标车辆转发。或者，碰撞指示信息的生产者为路侧设备，可以由路侧设备通过V2X进行发布。
由于目标车辆的运动状态以及目标车辆周围的移动物体的运动状态是高频变化的，其轨迹也可能变化，而且轨迹所在的道路的行驶环境(例如，天气)等也会随时间动态变化，为了满足实时性的使用需求，可以以小时甚至分钟为更新频率对碰撞指示信息进行更新。
上述各系统中，网络侧设备与车辆之间，车辆与路侧设备之间，网络侧设备与路侧设备之间的通信可使用蜂窝通信技术，例如2G蜂窝通信，例如全球移动通信系统(global system for mobile communication，GSM)、通用分组无线业务(general packet radio service，GPRS)；或者3G蜂窝通信，例如宽带码分多址(wideband code division multiple access，WCDMA)、时分同步码分多址接入(time division-synchronous code division multiple access，TS-SCDMA)、码分多址接入(code division multiple access，CDMA)，或者4G蜂窝通信，例如长期演进(long term evolution，LTE)。或者5G蜂窝通信，或者其他演进的蜂窝通信技术。无线通信系统也可利用非蜂窝通信技术，如Wi-Fi与无线局域网(wireless local area network，WLAN)通信。在一些实施例中，上述设备之间通信还可利用红外链路、蓝牙或ZigBee进行直接通信。在一些实施例中，上述设备之间通信还可以采用其他无线协议，例如各种车辆通信系统，例如，系统中可包括一个或多个专用短程通信(dedicated short range communications，DSRC)设备，这些设备可包括车辆和/或路边台站之间的公共和/或私有数据通信，本申请不做具体限定。
需要说明的是，图2仅为示例性架构图，但不限定图2所示系统包括的网元的数量。虽然图2未示出，但除图2所示的功能实体外，图2还可以包括其他功能实体。另外，本申请实施例提供的方法可以应用于图2所示的通信系统，当然本申请实施例提供的方法也可以适用其他通信系统，本申请实施例对此不予限制。
参见图3，图3是本申请实施例提供的一种数据生成方法的流程图，可应用于网络侧设备或路侧设备，下述以网络侧设备为例进行方案的示例性阐述，但本申请实施例并不限定该方法仅用于网络侧设备。该方法包括但不限于以下步骤：
S101：获取预测轨迹信息，预测轨迹信息用于指示预测的多个移动物体的轨迹。
可选地，获取预测轨迹信息，包括：获取多个移动物体中每个移动物体的运动状态数据，根据每个移动物体的运动状态数据预测对应的移动物体的轨迹，以获得预测轨迹信息。其中，预测的每个移动物体的轨迹包括但不限于每个移动物体在各个时刻的位置坐标、速度、加速 度、航向等。
其中，多个移动物体除了包括目标车辆外，还包括目标车辆周围的其他移动物体，例如，可以是机动车辆、非机动车辆等无生命的可移动物体，也可以是行人、骑车的行人、路面上的动物等有生命的可移动物体。每个移动物体的运动状态数据包括该移动物体在历史多个时刻的状态参数(例如，位置坐标、速度、加速度、航向等)。
在一些可能的实施例中，在移动物体的运动状态数据的基础上，还可以结合驾驶员信息获得预测轨迹信息，其中，驾驶员信息包括但不限于驾驶员的驾驶习惯、驾驶员的实时状态等，其中，驾驶习惯例如可以是频繁并线、超速行驶、弯道超车、抢黄灯、不开快车、礼让非机动车、夜间合理运用灯光、不疲劳驾驶等，驾驶员的实时状态例如可以是亢奋、平和、生气、疲劳、睡着、昏迷等。
例如，每个移动物体的运动状态数据可以是网络侧设备从地图(例如，高精地图)中获取的，也可以是交通管理部门基于移动物体的标识(例如，在移动物体为车辆时，移动物体的标识可以是车辆识别代码)查找后发送给网络侧设备，还可以是路侧设备或其他车辆在监测到移动物体的运动状态后发送给网络侧设备。另外，移动物体的运动状态数据可以部分或全部来自于地图、交通管理部门的服务器、路侧设备、车辆等中的至少一项，本申请实施例对移动物体的运动状态数据的来源不作具体限定。
参见图4，图4是本申请实施例提供的一种碰撞预测系统的框架示意图。图4简单示意了预测轨迹信息的获取过程。由图4可以看出，分别获取目标车辆的运动状态数据和其他移动物体的运动状态数据，其中，有关目标车辆的运动状态数据和其他移动物体的运动状态数据具体可参考上述相应描述，根据目标车辆的运动状态数据进行轨迹预测，获得预测的目标车辆的轨迹；根据其他移动物体的运动状态数据进行轨迹预测，获得预测的其他移动物体的轨迹。轨迹的预测有多种计算方法，例如可以采用高斯混合模型、贝叶斯模型、卡尔曼滤波模型、长短期记忆(Long Short-Term Memory，LSTM)模型等方式中的任意一种进行轨迹预测，本申请实施例在此不作具体限定。
S102：获取道路环境信息。
可选地，道路环境信息用于指示轨迹所在的道路的行驶环境，其中，该轨迹为上述预测的多个移动物体的轨迹。行驶环境包括以下内容中的至少一项：天气、能见度、光照强度、道路类型、车道数量、道路平坦程度、道路光滑程度、道路施工情况、交通违规历史统计情况和交通流量情况。
其中，天气包括但不限于降水量、降雪量、风向、风力等级、雷电指数等参数。
道路类型的划分有多种，例如，基于道路行政等级可分为国道、省道、县道、乡道等，基于道路使用任务、功能、和交通量可分为高速公路、一级公路、二级公路、三级公路等，基于道路使用者的身份可以划分为机动车道、还可以是其他划分方式，在此不作具体限定。
车道数量可以体现道路的宽度。
道路平坦程度可以通过坑洼的位置、坑洼的数量、坑洼的深度等参数表示。
道路光滑程度可以通过路面结冰的厚度、路面结冰位置区域、路面材料等参数表示。
道路施工情况可以通过施工位置、施工面积、施工时长等参数表示。
需要说明的是，上述道路类型、车道数量、道路平坦程度、道路光滑程度、道路施工情况仅是用于指示道路状态的信息的示例，在一些可能的实施例中，还包括道路积水情况、道 路落叶覆盖情况等指示道路状态的信息。
交通流量情况包括但不限于平均车流量、最大车流量等参数。
交通行为历史统计情况是对移动物体的热点行为区域(或称为高频行为区域)的统计。交通行为历史统计情况包括但不限于行人高频穿行区域、车辆紧急加速区域、车辆紧急减速区域、高频逆向行驶区域、高频闯红灯区域等。
例如，图1所示的主干道包括车道1和车道2，在图1中，假设车辆1为目标车辆，车辆2为车辆1周围的一个移动物体，预测车辆1的轨迹为路径A→B→C→D，则车辆1的轨迹所在的道路为路段AD，车辆1对应的道路环境信息实际为车辆1基于轨迹在路段AD上行驶时各个位置处的道路环境信息。相应地，也可以基于车辆2的轨迹获得车辆2对应的道路环境信息。有关道路环境信息的具体内容具体可参考上述有关道路环境信息的说明，在此不再赘述。可以理解，在有多个移动物体的情况下，可以按照上述方式获得每个移动物体的轨迹对应的道路环境信息，也可以结合多个移动物体的轨迹综合确定多个移动物体的轨迹对应的道路环境信息，在此不作具体限定。
一种实施方式中，道路环境信息可以是网络侧设备从地图中的动态图层数据和静态图层数据中获取。
S103：根据道路环境信息和预测轨迹信息获得碰撞指示信息，碰撞指示信息包括第一时间信息和第一概率信息，第一时间信息用于指示预测目标车辆将发生碰撞的时间，第一概率信息用于指示预测碰撞发生的概率。
其中，第一时间信息指示的时间是预测到的目标车辆可能发生碰撞的时间，并不一定是目标车辆实际发生碰撞的时间。
在本申请实施例中，第一时间信息指示的时间可以是一个时间点(例如一个时刻)，也可以是一个时间段。
在第一时间信息指示一个时间点时，第一时间信息例如可以表示为时刻“14:05”；在第一时间信息指示一个时间段时，第一时间信息例如可以表示为时段“14:05-14:07”，时段的时长可以以毫秒ms、秒s、分钟min或者其他量级单位表示，在此不作具体限定。
第一概率信息可以通过(0，1]的浮点数进行表示，第一概率信息指示的概率的值越大，表示目标车辆发生碰撞的可能性就越大。
在本申请实施例中，碰撞指示信息还包括位置信息，位置信息用于指示预测碰撞将发生的位置。位置信息可以指示一个地理位置点，也可以指示一个地理区域范围。
位置信息指示的位置是预测到的目标车辆可能发生的碰撞所在的位置，并不一定是目标车辆实际发生碰撞所在的位置。
位置信息可以表示为基于任意坐标系获得的坐标值，例如，坐标系可以是世界大地坐标系(Word Geodetic System 1984，WGS84)、自然坐标系、道路坐标系等。
一具体实施中，碰撞的位置信息可以以车道级方式表示。例如，图5是本申请实施例提供的一种碰撞的位置信息的表达示意图，图5所示的道路包括车道1和车道2，假设碰撞将发生的位置为图5中车道1中的区域1，若对区域1进行车道级表示，则碰撞的位置信息可表示为矩形abcd对应的区域，其中，该区域的宽度为车道1的宽度以及长度为区域1沿着车道线方向上的长度。另一具体实施中，当碰撞将发生的位置占据了同一道路的多条车道时，碰撞的位置信息可以以道路级方式表示，在此不作具体限定。
道路级表示或者车道级表示，都可以通过一个或多个相对于基准点(例如，车道或道路的起点)的参数，如距离，坐标等表示。在一些可能的实施例中，碰撞的位置信息还可以是其他表示方式，例如，在碰撞发生的位置为不规则区域时，碰撞的位置信息信息还可以基于最小外接矩形表示，或者基于多个角点的地理坐标表示，本申请实施例不作具体限定。
在本申请实施例中，碰撞指示信息还包括下述预测的信息中的至少一项：与目标车辆碰撞的移动物体的标识信息、碰撞等级信息、碰撞类型信息、剩余碰撞时间信息、碰撞的标识信息、碰撞所在的瓦片的标识信息、碰撞所在的道路的标识信息、影响碰撞的地图中动态要素的标识信息和预警信息。其中，碰撞等级信息用于指示碰撞的严重程度，碰撞类型信息用于指示碰撞的类型，预警信息用于指示基于该碰撞向驾驶员或驾驶系统提醒的内容。
一具体实施中，碰撞指示信息还包括与目标车辆碰撞的移动物体的标识信息。需要说明的是，与目标车辆碰撞的移动物体的标识信息是碰撞指示信息的一种可选信息。通过与目标车辆碰撞的移动物体的标识信息可以有效提醒目标车辆注意该移动物体的运动状态，使得目标车辆可以及时作出应对决策，以避免碰撞的发生。
另一具体实施中，碰撞指示信息还包括碰撞等级信息，碰撞等级信息用于指示碰撞的严重程度。需要说明的是，碰撞等级信息是碰撞指示信息的一种可选信息。基于碰撞等级信息，可以对碰撞的严重程度进行阶梯量化，有利于目标车辆快速区分碰撞的轻重缓急，提高对碰撞的应对效率。
示例性地，碰撞的严重程度可以是四级划分，分别为轻微、一般、重大和特大，其中，轻微级别表示一次造成轻伤1至2人，或者财产损失的数额中机动车事故不足1000元，非机动车事故不足200元；一般级别表示一次造成重伤1至2人，或者轻伤3人以上，或者财产损失不足3万元；重大级别表示一次造成死亡1至2人，或者重伤3人以上10人以下，或者财产损失3万元以上不足6万元；特大表示一次造成死亡3人以上，或者重伤11人以上，或者死亡1人，同时重伤8人以上，或者死亡2人，同时重伤5人以上，或者财产损失6万元以上。在一些可能的实施例中，碰撞的严重程度还可以是其他划分方式，例如，基于是否有人员受伤划分为高风险和低风险，其中，高风险表示该次碰撞有人员受伤，低风险表示该次碰撞无人员受伤。
碰撞等级信息可以采用比特映射、二进制取值或其他方式来指示碰撞的严重程度。以二进制取值方式为例，参见表1，表1示例性地提供了一种碰撞等级信息取值与碰撞严重程度之间的映射表，由表1可知，当碰撞等级信息取值为“00”时，表示碰撞严重程度为轻微；当碰撞等级信息取值为“01”时，表示碰撞严重程度为一般；当碰撞等级信息取值为“10”时，表示碰撞严重程度为重大；当碰撞等级信息取值为“11”时，表示碰撞严重程度为特大。由此可以看出，碰撞严重程度对应的碰撞等级按照从高到低的排序依次为：特大>重大>一般>轻微。需要说明的是，碰撞等级信息取值越小，则碰撞严重程度越小，也说明碰撞的风险越低。
表1
碰撞等级信息取值 碰撞严重程度
00 轻微
01 一般
10 重大
11 特大
可以理解，上述表1仅作为一个示例，以体现碰撞等级信息取值与碰撞严重程度之间的对应关系，在实际应用中，该对应关系的文字内容和存储方式还可以是其他形式，在此不作具体限定。
另一具体实施中，碰撞指示信息还包括碰撞类型信息，碰撞类型信息用于指示碰撞的类型。需要说明的是，碰撞类型信息是碰撞指示信息的一种可选信息。
示例性地，碰撞事件的类型基于碰撞方位可分为前方碰撞、后方碰撞、左侧方碰撞和右侧方碰撞。在一些可能的实施例中，碰撞的类型也可以基于碰撞原因分为转弯碰撞、追尾碰撞、变道碰撞等。具体的分类方式还有很多，本申请实施例不作具体限定。可以看出，碰撞类型信息使得目标车辆能够基于碰撞的类型更迅速、更有针对性地应对碰撞事件，提高了碰撞的应对效率。
另一具体实施中，碰撞指示信息还包括剩余碰撞时间信息，剩余碰撞时间信息用于指示碰撞将发生的时间距离当前时间的时间差。需要说明的是，剩余碰撞时间信息是碰撞指示信息的一种可选信息。
示例性地，剩余碰撞时间信息可以是目标车辆距离预测到的该目标车辆未来碰撞发生的最早时间之前的剩余行驶时间。在一些可能的实施例中，剩余碰撞时间信息还可以是碰撞时间(Time-to-Collision，TTC)、安全时间域(Safety Time Domain，STD)、车头时距(Time Headway，TH)等，在此作具体限定。可以看出，基于剩余碰撞时间信息能实时提醒驾驶员或驾驶系统预测的碰撞，实现碰撞的及时预警。
另一具体实施中，碰撞指示信息还包括影响碰撞的地图中动态要素的标识信息。需要说明的是，影响碰撞的地图中动态要素的标识信息是碰撞指示信息的一种可选信息。
其中，动态要素影响碰撞是指动态要素会加重碰撞的严重程度。影响碰撞的地图中的动态要素包括但不限于：路面结冰、道路施工、大雾天气、暴雪天气、暴雨天气、道路拥堵、路面坍塌、山体滑坡、路面检修等。可以看出，基于影响碰撞的地图中动态要素的标识信息，可以快速查找该碰撞关联的动态要素。当检测该碰撞关联的动态要素发生变化时，可以及时更新目标车辆的碰撞指示信息，提高了碰撞指示信息的准确率。
动态要素的标识信息用于在地图中标识该动态要素。动态要素的标识信息可以是一个或多个字符的组合，其中，字符可以是数字，字母以及其他符号中的一种或多种，例如一个或多个数字的组合，或者一个或多个数据和字母的组合。
另一具体实施中，碰撞指示信息还包括碰撞的标识信息、碰撞所在的瓦片的标识信息、碰撞所在的道路的标识信息和预警信息中的至少一项，且这些信息均为碰撞指示信息的可选信息。
其中，瓦片可以理解为：将一定范围内的地图按照一定的尺寸和格式，以及不同的地图分辨率，切成若干行和列的矩形栅格图片，对切片后的矩形栅格图片称为瓦片(Tile)。
碰撞的标识信息用于该碰撞；瓦片的标识信息用于标识地图中的瓦片，道路的标识信息用于标识地图中的道路。碰撞的标识信息、瓦片的标识信息或道路的标识信息可以是一个或多个字符的组合，其中，字符可以是数字，字母以及其他符号中的一种或多种，例如一个或多个数字的组合，或者一个或多个数据和字母的组合。可以看出，将碰撞与地图瓦片的标识关联，可以基于地图瓦片的标识实现碰撞的快速索引。将碰撞与道路的标识关联，可以基于道路的标识实现碰撞的快速索引。由此，可节省碰撞的搜索时间，提高碰撞的搜索效率。
预警信息例如可以是“请注意，时刻1在区域1有碰撞风险”，也可以是“时刻1在区域1内与车辆A有碰撞风险，概率为0.8，请及时调整运动状态”，还可以是“时刻1有0.6的概率发生碰撞，请注意”，或者其他具有风险提示功能的信息，本申请实施例在此不作具体限定。预警信息可以通过语音播报或者文字显示的方式展示。可以看出，通过预警信息，可以及时提醒驾驶员预测到的碰撞，提高车辆行驶的安全性。
在本申请实施例中，碰撞指示信息可以存储于碰撞的标识对应的数据结构中。在一些可能的实施例中，碰撞指示信息也可以作为地图数据存储，例如，作为地图的动态图层数据存储。碰撞指示信息作为地图数据存储时，预测到的碰撞也可以称作地图中的碰撞事件，则碰撞的标识信息即为碰撞事件的标识信息。
参见图6A，图6A是本申请实施例提供的一种碰撞指示信息的数据结构示意图。在图6A中，以碰撞事件1为例说明碰撞事件1对应的碰撞指示信息，碰撞指示信息包括时间信息和概率信息，其中，时间信息用于指示预测碰撞事件1将发生的时间，概率信息用于指示预测碰撞事件1发生的概率。在一些可能的实施例中，碰撞指示信息还包括下述预测的信息中的至少一项：碰撞等级信息、碰撞类型信息、与目标车辆发生碰撞的移动物体的标识、影响碰撞事件1的动态要素的标识、预警信息、碰撞事件1所在的瓦片的标识、碰撞事件1所在的道路的标识和碰撞事件1的标识中的至少一项。图6A所示的各个信息具体可参考上述实施例中的相关内容的叙述，为了说明书的简洁，在此不再赘述。
在一些可能的实施例中，预测到有多个移动物体与目标车辆碰撞，且对于不同的移动物体，与目标车辆发生碰撞的位置不同时，则预测到的目标车辆与不同的移动物体的碰撞可以分开单独表示。可以理解，若以图6A中的碰撞事件表示，即意味着一个目标车辆对应多个碰撞事件。
一具体实施中，在预测到有多个移动物体与目标车辆碰撞时，若这多个移动物体中各个移动物体与目标车辆发生碰撞的位置近似为同一个地理区域范围时，换句话说，当多个移动物体中任意两个移动物体与目标车辆发生碰撞的位置之间的距离均满足预设距离条件时，则目标车辆与多个移动物体的碰撞可以通过一个碰撞事件进行综合存储和表达。其中，预设距离条件可以是两个位置之间的距离小于等于预设距离阈值，或者，两个位置之间的重合面积大于等于预设面积阈值，或者其他条件，在此不作具体限定。
当目标车辆与多个移动物体的碰撞通过同一个碰撞事件进行表达时，不同的移动物体对应的时间信息、概率信息、碰撞等级信息、碰撞类型信息等中的至少一项也可能不同。在此情况下，还可以进一步存储与目标车辆碰撞的移动物体的标识、时间信息、概率信息、碰撞等级信息和碰撞类型信息之间的映射关系，例如，可以以表、图等形式存储上述信息之间的映射关系。
参见图6B，图6B是本申请实施例提供的又一种碰撞指示信息的数据结构示意图。在图6B中，以目标车辆的碰撞事件1为例，可以看出目标车辆对应的有多个未来可能发生碰撞的移动物体，包括移动物体A、移动物体B等，且这多个移动物体对应相同的位置信息，故目标车辆与多个移动物体的碰撞可以基于碰撞事件1进行统一表达。在图6B中，碰撞指示信息包括位置信息、碰撞事件1的标识以及多个移动物体中每个移动物体对应的时间信息、概率信息、碰撞等级信息、碰撞类型信息和预警信息等，例如，移动物体A对应的时间信息用于指示预测目标车辆与移动物体A发生碰撞的时间；移动物体A对应的概率用于指示预测目 标车辆与移动物体A发生碰撞的概率；移动物体A对应的碰撞等级信息用于指示预测目标车辆与移动物体A发生碰撞的严重程度；移动物体A对应的碰撞类型信息用于指示预测目标车辆与移动物体A发生碰撞的预测类型。在一些可能的实施例中，碰撞指示信息还包括碰撞事件1所在的瓦片的标识、碰撞事件1所在的道路的标识和影响碰撞事件1的动态要素的标识。
在一些可能的实施例中，图6B所示的各个移动物体对应的碰撞等级信息也可以缺省，而设置碰撞事件1的碰撞等级信息，碰撞事件1的碰撞等级信息由目标车辆与各个移动物体发生碰撞的严重程度确定。
需要说明的是，上述图6A和图6B所示的碰撞指示信息的数据结构示意图只是一种示例，本申请实施例并不限定碰撞指示信息的数据结构示意图仅为图6A或图6B所示。
下面结合图4具体说明碰撞指示信息的获取过程：
在图4中，在获取预测轨迹信息(此过程具体可参考上述S101相关描述)以及获取道路环境信息后，基于道路环境信息和预测轨迹信息可以是：根据道路环境信息，获得风险区域信息；根据预测轨迹信息和风险区域信息获得碰撞指示信息，碰撞指示信息包括上述第一时间信息和第一概率信息。在一些可能的实施例中，碰撞指示信息还包括位置信息、碰撞等级信息、碰撞类型信息、与目标车辆发生碰撞的移动物体的积标识等。
一具体实施中，基于道路环境信息和预测轨迹信息获得碰撞指示信息，可以是：根据预测轨迹信息，获得碰撞预测结果，碰撞预测结果包括目标车辆发生碰撞的第二时间信息和第二概率信息；输入道路环境信息至第一人工智能(Artificial Intelligence，AI)模型，输出风险区域信息，风险区域信息包括风险区域的位置信息和风险区域的风险等级；根据风险区域信息校正碰撞预测结果，获得碰撞指示信息。可以看出，由于环境风险对碰撞预测有影响，例如，某路段的路面结冰会对在该路段行驶的车辆的刹车性能有影响进而影响车辆的行驶轨迹，因此，在根据预测轨迹信息获得碰撞预测结果后，基于风险区域信息(即表征了环境风险)对碰撞预测结果进行修正以获得碰撞指示信息，有效了提高预测的目标车辆的碰撞的精准性。
其中，第一人工智能AI模型也可以称作环境风险预测模型，第一AI模型是基于历史碰撞数据和历史道路环境数据训练获得，历史碰撞数据包括车辆的历史碰撞对应的时间信息、位置信息、碰撞类型信息和碰撞等级信息等，历史道路环境数据用于指示历史碰撞对应的移动物体的历史轨迹所在的道路的行驶环境。历史道路环境数据可参考S102中相应内容的叙述。
示例性地，第一AI模型的训练过程可以是：先根据历史碰撞的碰撞等级评估历史碰撞所在区域的风险等级，以建立历史碰撞的碰撞等级、历史碰撞所在区域以及区域对应的风险等级之间的映射关系。例如，历史碰撞的碰撞等级越高(表示碰撞程度越严重)，则该历史碰撞所在区域的风险等级越高(表示区域的安全度越低)。将区域的风险等级作为训练目标，将历史碰撞数据和历史道路环境数据输入第一AI模型，第一AI模型输出风险区域的预测位置信息和风险区域对应的预测风险等级，根据预测位置信息和区域的真实位置信息、预测风险等级和区域的真实风险等级获得第一AI模型的预测误差，基于第一AI模型的预测误差调整第一AI模型的模型参数，当第一AI模型的预误差小于预设误差阈值时，第一AI模型训练完毕，训练好的第一AI模型能够基于道路环境信息准确地预测风险区域以及风险区域对应的风险等级。
另一具体实施中，基于道路环境信息和预测轨迹信息获得碰撞指示信息，也可以是：将 道路环境信息输入至第一AI模型，获得风险区域信息，风险区域信息包括风险区域的位置信息和风险区域的风险等级；将风险区域信息和预测轨迹信息输入第二AI模型，获得碰撞指示信息。其中，第二AI模型能够融合环境风险以及各个移动物体的轨迹实现对目标车辆的碰撞预测，第二AI模型是基于历史运动轨迹数据、历史碰撞数据和历史道路环境数据训练获得，历史运动轨迹数据包括历史碰撞对应的移动物体的历史轨迹，有关历史碰撞数据、历史道路环境数据具体可参考上述第一AI模型的相关内容的叙述，在此不再赘述。
示例性地，第一AI模型或第二AI模型可以是人工神经网络(Artificial Neural Network，ANN)、长短期记忆(Long Short-Term Memory，LSTM)神经网络、随机森林、支持向量机、或其他预测算法。
S104：向目标车辆发送碰撞指示信息。
在本申请实施例中，向目标车辆发送碰撞指示信息，可以是：网络侧设备生成碰撞指示信息后，向目标车辆发送该碰撞指示信息。
在本申请实施例中，向目标车辆发送碰撞指示信息，可以是：从目标车辆接收碰撞预测服务请求，碰撞预测服务请求用于请求网络侧设备为目标车辆提供碰撞预测服务，碰撞预测服务请求包括目标车辆的标识；响应于该碰撞预测服务请求，向目标车辆发送碰撞指示信息。也就是说，目标车辆预先向网络侧设备订阅碰撞预测服务，当目标车辆行驶时，可以向网络侧设备发送携带自身标识的碰撞预测服务请求，以获取与目标车辆相关的碰撞指示信息。
在本申请实施例中，向目标车辆发送碰撞指示信息，还可以是：在满足下述条件中的至少一项时，向目标车辆发送碰撞指示信息：
(1)预测碰撞发生的概率大于第一阈值；
(2)目标车辆当前的位置与预测碰撞将发生的位置之间的最小距离小于第二阈值；
(3)预测碰撞将发生的位置所属的道路为目标车辆所在的道路；和
(4)预测碰撞将发生的位置所属的瓦片为目标车辆所在的瓦片。
在一些可能的实施例中，网络侧设备提前向目标车辆发送碰撞指示信息，即网络侧设备向目标车辆发送碰撞指示信息的时刻是早于预测的目标车辆将发生碰撞的时间。如此，目标车辆可以提前知晓该碰撞，从而可以及时作出针对碰撞的应对措施，例如，调整自身的运动策略，以尽可能避免碰撞的发生。
在一些可能的实施例中，网络侧设备还可以向预测的与目标车辆发生碰撞的移动物体发送碰撞指示信息，以提示相应地移动物体具有与目标车辆发生碰撞的风险。
在一些可能的实施例中，网络侧设备还可以周期性地向目标车辆发送碰撞指示信息。这是因为目标车辆的运动状态、与目标车辆发生碰撞的移动物体的运动状态、周围的道路环境信息是高频变化的，故网络侧设备可以按照预设周期获取更新的道路环境信息以及预测轨迹信息，并基于更新的道路环境信息和更新的预测轨迹信息对碰撞指示信息进行更新，并将更新后的碰撞指示信息发送给目标车辆。
在一些可能的实施例中，更新碰撞指示信息也可以是：在多个移动物体的轨迹发生变化时和/或影响碰撞的地图中动态要素发生变化时，更新碰撞指示信息或者删除碰撞指示信息。其中，更新碰撞指示信息具体包括修改碰撞指示信息中的第一时间信息、第一位置信息、碰撞等级信息、碰撞类型信息、预警信息、影响碰撞的动态要素的标识信息中的至少一项。
其中，删除碰撞指示信息包括下述情况中的至少一种：更新后的碰撞等级信息小于下限 风险阈值(在此情况下，可认为碰撞的风险低或者无风险)；更新后的第一概率信息指示的碰撞预测概率小于下限概率阈值(在此情况下，可认为碰撞发生的概率低或碰撞不会发生)。碰撞指示信息被删除，意味着预测到的该碰撞不会发生。
可选地，在一些可能的实施例中，还可以执行：
S105：根据碰撞指示信息，执行交通监控、交通调度或对目标车辆的控制。
一具体实施中，根据碰撞指示信息，执行交通监控可以是：在预测碰撞将发生的位置，根据碰撞指示信息执行路况监控。如此，网络侧设备可以监测预测的碰撞将发生的位置附近是否有碰撞发生，在监测到有碰撞发生时，可以及时通知交管部门人员前去事故现场。
一具体实施中，根据碰撞指示信息，执行交通调度可以是：根据碰撞指示信息确定碰撞在地图中所在的道路区域，向该道路区域内的车辆提示该碰撞，或者，管控该道路区域的车流量。
网络侧设备向碰撞所在的道路区域内的车辆提示该碰撞，使得道路区域内的车辆可以预先知晓周围有目标车辆存在碰撞风险，从而能及时调整自身的行驶速度以与目标车辆保持安全距离，防止连环追尾。网络设备还可以管控碰撞所在的道路区域的车流量，以防止该道路区域的车流量过大，从而有效减少道路区域内因碰撞发生导致的拥堵程度。
一具体实施中，根据碰撞指示信息，执行对目标车辆的控制可以是：确定目标车辆即将到达碰撞将发生的位置时，控制目标车辆执行以下操作中的至少一项：变换车道；调整行驶速度；更新导航路线；开启警示灯；和向驾驶员提示碰撞。一种实施方式中，网络侧设备执行对目标车辆的控制之前，目标车辆预先向网络设备定制碰撞预测服务，使得网络侧设备可以及时控制目标车辆准确应对该碰撞，以尽可能避免碰撞的发生。
可以看到，实施本申请实施例，能够为车辆提供具有参考意义的、实时动态的碰撞指示信息，且在生成碰撞指示信息的过程中不仅考虑了车辆及其周围移动物体的轨迹，还综合考虑了轨迹所在道路的行驶环境，提高了预测的目标车辆可能发生的碰撞的精准性，有利于提高车辆出行的安全率。
参见图7，图7是本申请实施例提供的一种数据使用方法的流程图，应用于目标车辆。该方法包括但不限于以下步骤：
S201：接收碰撞指示信息，碰撞指示信息包括第一时间信息和第一概率信息，第一时间信息用于指示预测目标车辆将发生碰撞的时间，第一概率信息用于指示预测碰撞发生的概率。碰撞指示信息具体可参考图3实施例中S103有关碰撞指示信息的相关描述，这里不再赘述。
在本申请实施例中，接收碰撞指示信息，可以是：从网络侧设备或路侧设备接收碰撞指示信息。
在本申请实施例中，在满足下述条件中的至少一项时，目标车辆接收碰撞指示信息：
(1)预测碰撞发生的概率大于第一阈值；
(2)目标车辆当前的位置与预测碰撞将发生的位置之间的最小距离小于第二阈值；
(3)预测碰撞将发生的位置所属的道路为目标车辆所在的道路；和
(4)预测碰撞将发生的位置所属的瓦片为目标车辆所在的瓦片。
S202：根据碰撞指示信息，执行对自身的控制。
一具体实施中，根据碰撞指示信息，执行对自身的控制，可以是：目标车辆在确定自身 即将到达碰撞发生的位置时，控制自身执行以下操作中的至少一项：变换车道；调整行驶速度；更新导航路线；开启警示灯；和向驾驶员提示该碰撞。如此，在行驶过程中，目标车辆基于碰撞指示信息，可以及时采取措施应对碰撞，有利于提高碰撞的应对效率。
例如，在图1中，假设目标车辆为车辆1，车道2中的路段BC出现路面结冰，车辆1当前位于车道2的位置A处，车辆1欲到达位置D且车辆1的导航路线为A→E→B→C→H→D，假设车辆1在位置A接收到来自网络侧设备，例如云端设备的碰撞指示信息，碰撞指示信息指示车辆1与车辆2(碰撞预测对象)在未来的时刻10:15、车道2中的区域1(碰撞预测区域)内有碰撞风险以及碰撞概率为0.8。在此情况下，有多种应对策略可供车辆1选择：
应对策略1：依次执行减速→变道→变道。具体地，车辆1先减速行驶，在车辆1与车辆2之间的距离满足安全变道距离时，车辆1再执行变道实现从车道2切换至车道1，在车道1上行驶以避开车道2的路段BC，当经过C点后再变道至车道2并行驶至位置D。
应对策略2：更新导航路线为A→E→F→G→H→D。具体地，车辆1根据碰撞指示信息结合接收到的车流量管控信息，确定路段EF、路段FG和路段GH的车流量少且路面状态良好，故车辆1更新导航路线，按照更新后的导航路线A→E→F→G→H→D行驶，从而避免车辆1与车辆2发生碰撞。
应对策略3：匀速和减速组合使用。具体地，车辆1始终保持在车道2上行驶，实时关注自身与碰撞预测对象车辆2之间的距离，通过匀速和减速组合使用的方式灵活调控自身的实时速度，使得自身与车辆2之间的距离大于安全距离直至车辆1到达位置D。
需要说明的是，上述应对策略1-应对策略3只是一种示例，目标车辆还可以选择其他应对策略，避免碰撞的发生或者尽可能减少碰撞发生时对人身的伤害。
一具体实施中，根据碰撞指示信息，执行对自身的控制，可以是：在预测碰撞发生的概率大于第一预设阈值，且在目标车辆将发生碰撞的时间距离当前时间的时间差小于第二预设阈值时，执行对目标车辆的控制。如此，进一步从碰撞发生的概率和时间两个维度上对触发控制目标车辆的条件进行了限制，在碰撞的发生具有较大的可能性且目标车辆的剩余碰撞时间满足条件时，目标车辆才对自身进行控制，提高目标车辆应对碰撞的效率。
一具体实施中，在目标车辆将发生碰撞的时间距离当前时间的时间差小于第三预设阈值和/或目标车辆的当前位置距离碰撞发生的位置之间的距离小于第四预设阈值时，控制目标车辆在当前车道紧急制动或者变道。在一些可能的实施例中，第三预设阈值小于等于上述第二预设阈值。
可以理解，当碰撞将发生的时间距离当前时间的剩余时间较短，或者，目标车辆的当前位置距离碰撞将发生的位置较近时，目标车辆已无法通过缓慢平稳降速避开与移动物体的碰撞，在此情况下，目标车辆可以通过紧急制动实现快速降速甚至停车，或者，目标车辆可以通过变道避开与移动物体的碰撞，如此，保证了目标车辆的驾驶安全性。
在一些可能的实施例中，目标车辆在执行紧急制动时，还可以同时鸣笛或开双闪灯以提醒周围车辆注意保持车距避免碰撞的发生。
一具体实施中，在预测到有多个移动物体同时与目标车辆发生碰撞时，根据目标车辆与每个移动物体碰撞的严重程度，获得目标车辆的应对策略。
例如，假设预测到车辆1在位置A处将同时与车辆2和车辆3发生碰撞，其中，预测车辆1与车辆2碰撞的严重程度为“轻微”，预测车辆1与车辆3碰撞的严重程度为“重大”，则 车辆1比较各个碰撞的严重程度，确定自身与车辆3碰撞的严重程度高于自身与车辆2碰撞的严重程度，车辆1的应对策略可以是优先应对自身与车辆3的碰撞，以尽可能避开与车辆3的碰撞，如此，可使得风险降低到最小，有利于提高车辆1自身的安全性。
可以看出，目标车辆较好地使用了碰撞等级信息，基于碰撞等级信息可以分清碰撞的轻重缓急，有利于快速确定应对碰撞的先后顺序，优先应对最大严重程度的碰撞，最大限度地提高目标车辆在行驶过程中的安全性。
上述为目标车辆对碰撞等级信息的应用示例。在一些可能的实施例中，目标车辆还可以结合碰撞指示信息中的多项信息确定应对策略。例如，目标车辆也可以结合剩余碰撞时间信息和碰撞等级信息确定应对策略，目标车辆优先应对时间最紧急的碰撞，即预测的最早发生的碰撞，在剩余碰撞时间较充足的情况下，目标车辆可以优先应对最大严重程度的碰撞。
在一些可能的实施例中，当预测到有多个移动物体将同时与目标车辆发生碰撞时，还可以根据移动物体的属性确定目标车辆的应对策略。例如，假设预测到车辆1将同时与前方的无人快递车和小轿车发生碰撞，当车辆1无法同时避开与无人快递车、小轿车的碰撞时，根据移动物体是否有生命或者是否承载人这一属性，车辆1的应对策略可以是优先避免与乘坐了人的小轿车发生碰撞。
可选地，在一些可能的实施例中，还可以执行：
S203：根据碰撞指示信息生成显示界面。
在本申请实施例中，目标车辆在接收到碰撞指示信息后，可以在目标车辆的显示装置上显示碰撞指示信息，显示装置可以是车机平板、车载显示器或抬头显示(head up display，HUD)系统等，在此不作具体限定。
在本申请实施例中，可以通过下述至少一种方式在显示界面上呈现碰撞指示信息：
(1)呈现预测的将与目标车辆发生碰撞的移动物体；
(2)呈现预测碰撞发生的时间距离当前时间的时间差；
(3)呈现预测发生碰撞的概率超过第五预设阈值的碰撞对应的碰撞指示信息；
(4)呈现预测发生碰撞的等级超过第六预设阈值的碰撞对应的碰撞指示信息；
(5)呈现预测的在导航路径上发生的碰撞对应的碰撞指示信息；
(6)呈现用户选择的等级或用户选择的类型的碰撞对应的碰撞指示信息；
(7)用不同颜色呈现不同等级的碰撞对应的碰撞指示信息；和
(8)用不同颜色呈现不同类型的碰撞对应的碰撞指示信息。
其中，在显示界面上呈现将与目标车辆发生碰撞的移动物体，直观地显示了预测的待碰撞的移动物体相对于目标车辆自身的位置方位，准确地提醒目标车辆注意碰撞风险的方位来源，有利于提高目标车辆对事件的应对效率。
在显示界面上动态显示预测的目标车辆的剩余碰撞时间信息，实现了预测碰撞将发生的时间的倒计时式提醒，增加了随着时间流逝碰撞即将到达的紧迫感。在一些可能的实施例中，也可以根据剩余碰撞时间的长短采用不同的颜色显示，以更好地提醒驾驶员。在一些可能的实施例中，随着剩余碰撞时间的缩短，还可以通过增加指示灯的闪烁频率、提高提示音音量等方式进一步提醒驾驶员当前时刻越来越接近预测的碰撞将发生的时间，需及时作出应对决策。
在显示界面呈现预测发生碰撞的概率超过第五预设阈值的碰撞对应的碰撞指示信息，直 观地显示了最有可能发生的碰撞，以使目标车辆可以及时采取相应策略应对该碰撞，尽可能减少碰撞发生时对人的伤害。
在显示界面呈现预测发生碰撞的等级超过第六预设阈值的碰撞对应的碰撞指示信息，直观地显示了危险程度较高或者较为严重的碰撞，以使用户重点关注危险程度较高的碰撞。
在显示界面上呈现导航路径上发生的碰撞对应的碰撞指示信息，其中，导航路径上发生的碰撞包括预测目标车辆将发生的碰撞和/或其他车辆在目标车辆的导航路径上将发生的但目标车辆未参与的碰撞。如此可以直观、有效提醒目标车辆在其导航路径上未来可能发生的碰撞，提高了目标车辆在驾驶过程中的安全性。
在显示界面，用不同颜色呈现不同等级的碰撞所对应的碰撞指示信息，直观地展示了不同碰撞等级的碰撞在地图中的分布，用户基于颜色也可以有效区分不同等级的碰撞。
在显示界面，用不同颜色呈现不同类型的碰撞所对应的碰撞指示信息，直观地展示了不同碰撞类型的碰撞在地图中的分布，用户基于颜色也可以有效区分不同类型的碰撞。
用户还可以自主选择感兴趣或者当前想要查看的类型或等级的碰撞对应的碰撞指示信息，使其在显示界面上显示，提高了用户的交互体验感。
在一些可能的实施例中，用户的选择可以基于用户在显示界面上的点触、滑动、拖动等触控操作生成，也可以是基于用户的语音指令生成的。
参见图8，图8是本申请实施例提供的一种显示装置的界面示意图。在图8中，左侧为用户操作界面，右侧为显示界面。在用户操作界面中，设置有“碰撞列表”，其中，碰撞列表下的各个碰撞为预测到的该车辆可能发生的碰撞，可以看出，碰撞列表下显示有“碰撞1”、“碰撞2”和“碰撞3”，即意味着车辆有三个碰撞，假设选中“碰撞2”，右侧罗列有“时间信息”、“概率信息”、“位置信息”、“碰撞等级信息”等多个选项框，当用户选中“位置信息”时，则在右侧的显示界面的显示区域显示预测碰撞2将发生的位置。另外，用户操作界面还设置有语音识别框，当检测到用户有输入语音指令时，则自动识别该语音指令，并在右侧的显示界面的显示区域显示语音指令指示内容。
在图8中，若用户的选择操作是点击碰撞2的“位置信息”的选项框，则在图8所示的显示区域对该位置信息指示的位置进行高亮显示。若用户的选择操作是拖动“碰撞2”键至显示区域的拖动操作，则在图8所示的显示区域显示碰撞2对应的时间信息、概率信息、位置信息和碰撞等级信息等。在一些可能的实施例中，用户的选择操作还可以是“显示本车辆所有可能发生的碰撞的详细信息”、“显示未来最早一次碰撞的详细信息”、“显示距离当前位置最近的碰撞将发生的位置”等语音指令。
需要说明的是，图8只是一种显示装置的显示界面的示例图，本申请实施例并不限定显示装置的界面仅为图8所示形式。
可选地，在显示界面对碰撞指示信息进行呈现时，可以结合地图进行显示，例如，将碰撞指示信息嵌入地图中。
在本申请实施例中，在显示界面对碰撞指示信息进行呈现时，可以呈现碰撞指示信息的全部信息，也可以呈现碰撞指示信息中的部分信息。例如，对碰撞将发生的位置进行标记显示。又例如，除了显示碰撞所在的位置外，还可以在地图中对预测的与目标车辆碰撞的移动物体、进行标记显示。又例如，还可以以弹框等方式显示碰撞指示信息的详细内容，例如，时间信息、概率信息、碰撞等级信息、碰撞类型信息、剩余碰撞时间信息、关联的动态要素 等中的多项。
参见图9，图9是本申请实施例提供的一种显示界面的示意图。在图9中，可以看到，道路中的椭圆形区域表示本车辆将发生碰撞的位置，即区域B，且旁边有一个弹框显示了该碰撞的详细信息，具体显示了“概率信息为0.8、时间信息为10:15，位置信息为区域B、待碰撞的移动物体为车辆A、碰撞等级信息为一般”等信息。另外，还可以在地图中对待碰撞的移动物体即车辆A进行高亮标记。除此之外，还可以在地图中对该碰撞关联的动态要素进行标记，例如，道路内的四边形区域表示该碰撞关联的路面结冰这一动态要素所在的区域范围。
在一些可能的实施例中，还可以在图9中显示本车辆的剩余碰撞时间。例如，在图9中，右上方设置有一个倒计时的进度条，其中，进度条的深色部分表示当前的剩余碰撞时间。随着进度条的深色部分逐渐缩短，可以通过高频闪烁灯或者提示语音等方式警示用户即将到达碰撞的时刻。
在一些可能的实施例中，图9所示的画面也可以显示在图8所示的显示界面的显示区域中。
在一些可能的实施例中，当预测到有多个移动物体与目标车辆发生碰撞时，可以优先显示大于等于预设等级阈值的碰撞等级对应的移动物体。另一具体实施中，也可以使用不同颜色以区分不同等级对应的移动物体。
在一些可能的实施例中，除了显示碰撞指示信息外，还可以在地图中显示目标车辆的轨迹和其他移动体的轨迹，如此，可以直观地显示碰撞将发生的位置为各条轨迹的交叉位置。
可以看到，实施本申请实施例，车辆可获取具有参考意义的碰撞指示信息，车辆基于碰撞指示信息可以及时控制自身车辆灵活地应对碰撞，不仅提高了车辆对碰撞的应对效率，还有利于提高车辆在行驶过程中的安全性。另外，基于碰撞指示信息还可以获得显示界面，直观地显示了地图中的碰撞的分布。
本申请实施例还提供了一种电子地图或电子地图数据结构，该电子地图或电子地图数据结构包括碰撞指示信息，碰撞指示信息包括第一时间信息和第一概率信息，第一时间信息用于指示预测目标车辆将发生碰撞的时间，第一概率信息用于指示预测碰撞发生的概率。该电子地图或电子地图数据被用于第一设备中，该第一设备将该包括碰撞指示信息的电子地图数据发送给第二设备，第二设备基于该电子地图执行交通调度、对车辆的控制等操作。第一设备例如为网络侧设备，例如云端设备；或路侧设备；第二设备例如为车辆。
一具体实施中，碰撞指示信息还包括位置信息，位置信息用于指示预测碰撞将发生的位置。
一具体实施中，碰撞指示信息还包括下述预测的信息中的至少一项：
与目标车辆碰撞的移动物体的标识信息、碰撞等级信息、碰撞类型信息、剩余碰撞时间信息、碰撞的标识信息、碰撞所在的瓦片的标识信息、碰撞所在的道路的标识信息、影响碰撞的地图中动态要素的标识信息和预警信息；其中，碰撞等级信息用于指示碰撞的严重程度，碰撞类型信息用于指示碰撞的类型，剩余碰撞时间信息用于指示碰撞将发生的时间距离当前时间的时间差，预警信息用于指示基于碰撞向驾驶员或驾驶系统提醒的内容。
一具体实施中，该碰撞指示信息在电子地图中作为动态图层数据存储。
参见图10，图10是本申请实施例提供的一种数据生成装置的功能结构示意图，数据生成装置30包括处理单元310和发送单元312。该数据生成装置30可以通过硬件、软件或者软硬件结合的方式来实现。
其中，处理单元310，用于基于道路环境信息和预测轨迹信息获得碰撞指示信息，预测轨迹信息用于指示预测的多个移动物体的轨迹，多个移动物体包括目标车辆，道路环境信息用于指示轨迹所在的道路的行驶环境，碰撞指示信息包括第一时间信息和第一概率信息，第一时间信息用于指示预测目标车辆将发生碰撞的时间，第一概率信息用于指示预测碰撞发生的概率；发送单元312，用于向目标车辆发送碰撞指示信息。
该数据生成装置30可用于实现图3实施例所描述的方法。在图3实施例中，处理单元310可用于执行S101、S102和S103，发送单元312可用于执行S104。在一些可能的实施例中，处理单元310还可以用于执行S105。
以上图10所示实施例中的各个单元的一个或多个可以软件、硬件、固件或其结合实现。所述软件或固件包括但不限于计算机程序指令或代码，并可以被硬件处理器所执行。所述硬件包括但不限于各类集成电路，如中央处理单元(central processing unit，CPU)、数字信号处理器(digital signal processor，DSP)、现场可编程门阵列(field-programmable gate array，FPGA)或专用集成电路(application-specific integrated circuit，ASIC)。
参见图11，图11是本申请实施例提供的一种数据使用装置的功能结构示意图，数据使用装置40包括接收单元410和处理单元412。该数据使用装置40可以通过硬件、软件或者软硬件结合的方式来实现。
其中，接收单元410，用于接收碰撞指示信息，碰撞指示信息包括第一时间信息和第一概率信息，第一时间信息用于指示预测目标车辆将发生碰撞的时间，第一概率信息用于指示预测碰撞发生的概率；处理单元412，用于根据碰撞指示信息，执行对目标车辆的控制。
在一些可能的实施例中，数据使用装置40还包括显示单元414，显示单元414用于根据碰撞指示信息生成显示界面。
该数据使用装置40可用于实现图7实施例所描述的方法。在图7实施例中，接收单元410可用于执行S201，处理单元412可用于执行S202，显示单元414可用于执行S203。
以上图11所示实施例中的各个单元的一个或多个可以软件、硬件、固件或其结合实现。所述软件或固件包括但不限于计算机程序指令或代码，并可以被硬件处理器所执行。所述硬件包括但不限于各类集成电路，如中央处理单元(central processing unit，CPU)、数字信号处理器(digital signal processor，DSP)、现场可编程门阵列(field-programmable gate array，FPGA)或专用集成电路(application-specific integrated circuit，ASIC)。
本申请还提供一种数据处理装置。如图12所示，数据处理装置50包括：处理器501、通信接口502、存储器503和总线504。处理器501、存储器503和通信接口502之间通过总线504通信。应理解，本申请不限定数据处理装置50中的处理器、存储器的个数。
一具体实施中，数据处理装置50可以是碰撞指示信息的生成端，数据处理装置50例如可以是网络侧设备或路侧设备。其中，网络侧设备例如可以是部署在网络侧的服务器(例如应用服务器)，或者为该服务器中的组件或者芯片。路侧设备例如可以是路侧单元(Road Side  Unit，RSU)、多接入边缘计算(Multi-Access Edge Computing，MEC)或者传感器等装置，或者是这些装置内部的组件或者芯片，也可以是由RSU和MEC组成的系统级设备，或者是由RSU和传感器组成的系统级设备，还可以是由RSU、MEC和传感器组成的系统级设备。
另一具体实施中，数据处理装置50可以是碰撞指示信息的使用端，数据处理装置50例如可以是网络侧设备、路侧设备或车辆。其中，网络侧设备例如可以是使用碰撞指示信息提供服务的应用服务器，或者为该应用服务器中的组件或者芯片。路侧设备例如可以是使用碰撞指示信息提供路侧服务的路侧单元(Road Side Unit，RSU)、多接入边缘计算(Multi-Access Edge Computing，MEC)或者传感器等装置，或者是这些装置内部的组件或者芯片，也可以是由RSU和MEC组成的系统级设备，或者是由RSU和传感器组成的系统级设备，还可以是由RSU、MEC和传感器组成的系统级设备。车辆例如可以是使用碰撞指示信息进行驾驶的车辆、车辆内的装置、部件或芯片，例如车载单元(On Board Unit，OBU)，本申请实施例不做具体限定。
总线504可以是外设部件互连标准(peripheral component interconnect，PCI)总线或扩展工业标准结构(extended industry standard architecture，EISA)总线等。总线可以分为地址总线、数据总线、控制总线等。为便于表示，图12中仅用一条线表示，但并不表示仅有一根总线或一种类型的总线。总线504可包括在数据处理装置50各个部件(例如，存储器503、处理器501、通信接口502)之间传送信息的通路。
处理器501可以包括中央处理器(central processing unit，CPU)、微处理器(micro processor，MP)或者数字信号处理器(digital signal processor，DSP)等处理器中的任意一种或多种。
存储器503用于提供存储空间，存储空间中可以存储操作系统和计算机程序等数据。存储器503可以是随机存取存储器(random access memory，RAM)、可擦除可编程只读存储器(erasable programmable read only memory，EPROM)、只读存储器(read-only memory，ROM)，或便携式只读存储器(compact disc read memory，CD-ROM)等中的一种或者多种的组合。存储器503可以单独存在，也可以集成于处理器501内部。
通信接口502可用于为处理器501提供信息输入或输出。或者可替换的，该通信接口502可用于接收外部发送的数据和/或向外部发送数据，可以为包括诸如以太网电缆等的有线链路接口，也可以是无线链路(如Wi-Fi、蓝牙、通用无线传输等)接口。或者可替换的，通信接口502还可以包括与接口耦合的发射器(如射频发射器、天线等)，或者接收器等。
在一些可能的实施例中，数据处理装置50还包括显示器505，显示器505与处理器501通过总线504连接或耦合。显示器505用于在显示界面上对碰撞指示信息进行呈现。显示器505可以是显示屏，显示屏可以是液晶显示器(Liquid Crystal Display，LCD)、有机或无机发光二极管(Organic Light-Emitting Diode，OLED)、有源矩阵有机发光二极体面板(Active Matrix/Organic Light Emitting Diode，AMOLED)等。显示器505也可以是车机平板、车载显示器或者抬头显示系统(Head up Display，HUD)等。
该数据处理装置50中的处理器501用于读取存储器503中存储的计算机程序，用于执行前述的方法，例如图3或图7所描述的方法。
在一种可能的设计方式中，数据处理装置50可为执行图3所示方法的执行主体中的一个或多个模块，该处理器501可用于读取存储器中存储的一个或多个计算机程序，用于执行以下操作：
基于道路环境信息和预测轨迹信息获得碰撞指示信息，预测轨迹信息用于指示预测的多个移动物体的轨迹，多个移动物体包括目标车辆，道路环境信息用于指示轨迹所在的道路的行驶环境，碰撞指示信息包括第一时间信息和第一概率信息，第一时间信息用于指示预测目标车辆将发生碰撞的时间，第一概率信息用于指示预测碰撞发生的概率；
通过发送单元312向目标车辆发送碰撞指示信息。
在另一种可能的设计方式中，数据处理装置50可为执行图7所示方法的执行主体中的一个或多个模块，该处理器501可用于读取存储器中存储的一个或多个计算机程序，用于执行以下操作：
通过接收单元410接收碰撞指示信息，碰撞指示信息包括第一时间信息和第一概率信息，第一时间信息用于指示预测目标车辆将发生碰撞的时间，第一概率信息用于指示预测碰撞发生的概率；
根据碰撞指示信息，执行对目标车辆的控制。
本申请实施例还提供了一种通信系统，该通信系统包括数据生成装置和数据使用装置，其中，数据生成装置例如可以是图10所示的数据生成装置30，也可以是图12所述的生成碰撞指示信息的数据处理装置50；数据使用装置例如可以是图11所示的数据使用装置40，也可以是图12所述的使用碰撞指示信息的数据处理装置50。数据生成装置可用于执行上述图3实施例所描述的方法，数据使用装置可用于执行上述图7实施例所描述的方法。
在本文上述的实施例中，对各个实施例的描述都各有侧重，某个实施例中没有详细描述的部分，可以参见其他实施例的相关描述。
需要说明的是，本领域普通技术人员可以看到上述实施例的各种方法中的全部或部分步骤是可以通过程序来指令相关的硬件来完成，该程序可以存储于一计算机可读存储介质中，存储介质包括只读存储器(Read-Only Memory，ROM)、随机存储器(Random Access Memory，RAM)、可编程只读存储器(Programmable Read-only Memory，PROM)、可擦除可编程只读存储器(Erasable Programmable Read Only Memory，EPROM)、一次可编程只读存储器(One-time Programmable Read-Only Memory，OTPROM)、电子抹除式可复写只读存储(Electrically-Erasable Programmable Read-Only Memory，EEPROM)、只读光盘(Compact Disc Read-Only Memory，CD-ROM)或其他光盘存储器、磁盘存储器、磁带存储器、或者能够用于携带或存储数据的计算机可读的任何其他介质。
本申请的技术方案本质上或者说对现有技术做出贡献的部分或者该技术方案的全部或部分可以以软件产品的形式体现出来，该计算机程序产品存储在一个存储介质中，包括若干指令用以使得一个设备(可以是个人计算机，服务器，或者网络设备、机器人、单片机、芯片、机器人等)执行本申请各个实施例所述方法的全部或部分步骤。

Claims (41)

  1. 一种数据生成方法，其特征在于，所述方法包括：
    基于道路环境信息和预测轨迹信息获得碰撞指示信息，所述预测轨迹信息用于指示预测的多个移动物体的轨迹，所述多个移动物体包括目标车辆，所述道路环境信息用于指示所述轨迹所在的道路的行驶环境，所述碰撞指示信息包括第一时间信息和第一概率信息，所述第一时间信息用于指示预测所述目标车辆将发生碰撞的时间，所述第一概率信息用于指示预测所述碰撞发生的概率；
    向所述目标车辆发送所述碰撞指示信息。
  2. 根据权利要求1所述的方法，其特征在于，行驶环境包括以下内容中的至少一项：天气、能见度、光照强度、道路类型、车道数量、道路平坦程度、道路光滑程度、道路施工情况、交通行为历史统计情况和交通流量情况。
  3. 根据权利要求1或2所述的方法，其特征在于，所述碰撞指示信息还包括位置信息，所述位置信息用于指示预测所述碰撞将发生的位置。
  4. 根据权利要求1-3任一项所述的方法，其特征在于，所述碰撞指示信息还包括下述预测的信息中的至少一项：
    与所述目标车辆碰撞的所述移动物体的标识信息、碰撞等级信息、碰撞类型信息、剩余碰撞时间信息、所述碰撞的标识信息、所述碰撞所在的瓦片的标识信息、所述碰撞所在的道路的标识信息、影响所述碰撞的地图中动态要素的标识信息和预警信息；
    其中，所述碰撞等级信息用于指示所述碰撞的严重程度，所述碰撞类型信息用于指示所述碰撞的类型，所述剩余碰撞时间信息用于指示所述碰撞将发生的时间距离当前时间的时间差，所述预警信息用于指示基于所述碰撞向驾驶员或驾驶系统提醒的内容。
  5. 根据权利要求1-4任一项所述的方法，其特征在于，所述方法还包括：
    在所述多个移动物体的轨迹发生变化时和/或影响所述碰撞的地图中动态要素发生变化时，更新所述碰撞指示信息或者删除所述碰撞指示信息。
  6. 根据权利要求1-5任一项所述的方法，其特征在于，所述方法还包括：
    根据所述碰撞指示信息，执行交通监控、交通调度或对所述目标车辆的控制。
  7. 根据权利要求1-6任一项所述的方法，其特征在于，所述方法还包括：
    确定所述目标车辆即将到达所述碰撞将发生的位置时，控制所述目标车辆执行以下操作中的至少一项：
    变换车道；
    调整行驶速度；
    更新导航路线；
    开启警示灯；和
    向驾驶员提示所述碰撞。
  8. 根据权利要求1-7任一项所述的方法，其特征在于，向所述目标车辆发送所述碰撞指示信息，包括：
    在满足下述至少一个条件时，向所述目标车辆发送所述碰撞指示信息：
    预测所述碰撞发生的概率大于第一阈值；
    所述目标车辆当前的位置与预测所述碰撞将发生的位置之间的最小距离小于第二阈值；
    预测所述碰撞将发生的位置所属的道路为所述目标车辆所在的道路；和
    预测所述碰撞将发生的位置所属的瓦片为所述目标车辆所在的瓦片。
  9. 根据权利要求1-8任一项所述的方法，其特征在于，所述道路环境信息是基于地图中的动态图层数据和静态图层数据获得，所述预测轨迹信息是基于所述多个移动物体的运动状态数据和驾驶员信息获得。
  10. 根据权利要求1-9任一项所述的方法，其特征在于，所述方法还包括：
    将所述碰撞指示信息作为地图数据进行存储。
  11. 一种数据使用方法，应用于目标车辆，其特征在于，所述方法包括：
    获取碰撞指示信息，所述碰撞指示信息包括第一时间信息和第一概率信息，所述第一时间信息用于指示预测所述目标车辆将发生碰撞的时间，所述第一概率信息用于指示预测所述碰撞发生的概率；
    根据所述碰撞指示信息，执行对所述目标车辆的控制。
  12. 根据权利要求11所述的方法，其特征在于，所述碰撞指示信息还包括位置信息，所述位置信息用于指示预测所述碰撞将发生的位置。
  13. 根据权利要求11或12所述的方法，其特征在于，所述碰撞指示信息还包括下述信息中的至少一项：
    与所述目标车辆碰撞的所述移动物体的标识信息、碰撞等级信息、碰撞类型信息、剩余碰撞时间信息、所述碰撞的标识信息、所述碰撞所在的瓦片的标识信息、所述碰撞所在的道路的标识信息、影响所述碰撞的地图中动态要素的标识信息和预警信息；
    其中，所述碰撞等级信息用于指示所述碰撞的严重程度，所述碰撞类型信息用于指示所述碰撞的类型，所述剩余碰撞时间信息用于指示所述碰撞将发生的时间距离当前时间的时间差，所述预警信息用于指示基于所述碰撞向驾驶员或驾驶系统提醒的内容。
  14. 根据权利要求11-13任一项所述的方法，其特征在于，根据所述碰撞指示信息，执行对所述目标车辆的控制，包括：
    确定所述目标车辆即将到达所述碰撞发生的位置时，控制所述目标车辆执行以下操作中的至少一项：
    变换车道；
    调整行驶速度；
    更新导航路线；
    开启警示灯；和
    向驾驶员提示所述碰撞。
  15. 根据权利要求11-13任一项所述的方法，其特征在于，根据所述碰撞指示信息，执行对所述目标车辆的控制，包括：
    在预测所述碰撞发生的概率大于第一预设阈值，且在所述目标车辆将发生碰撞的时间距离当前时间的时间差小于第二预设阈值时，执行对所述目标车辆的控制。
  16. 根据权利要求11-15任一项所述的方法，其特征在于，所述方法还包括：
    在所述目标车辆将发生碰撞的时间距离当前时间的时间差小于第三预设阈值和/或所述目标车辆的当前位置距离所述碰撞发生的位置之间的距离小于第四预设阈值时，控制所述目标车辆在当前车道紧急制动或者变道。
  17. 根据权利要求11-16任一项所述的方法，其特征在于，所述方法还包括：
    在预测到有多个移动物体同时与所述目标车辆发生碰撞时，根据所述目标车辆与每个移动物体碰撞的严重程度，获得所述目标车辆的应对策略。
  18. 根据权利要求11-17任一项所述的方法，其特征在于，所述方法还包括：通过以下方式中的至少一种在所述目标车辆的显示界面上呈现所述碰撞指示信息：
    呈现预测的将与所述目标车辆发生碰撞的所述移动物体；
    呈现预测所述碰撞发生的时间距离当前时间的时间差；
    呈现预测发生碰撞的概率超过第五预设阈值的碰撞对应的所述碰撞指示信息；
    呈现预测发生碰撞的等级超过第六预设阈值的碰撞对应的所述碰撞指示信息；
    呈现预测的在导航路径上发生的碰撞对应的所述碰撞指示信息；
    呈现用户选择的等级或用户选择的类型的碰撞对应的所述碰撞指示信息；
    用不同颜色呈现不同等级的碰撞对应的所述碰撞指示信息；和
    用不同颜色呈现不同类型的碰撞对应的所述碰撞指示信息。
  19. 一种数据生成装置，其特征在于，所述装置包括：
    获取单元，基于道路环境信息和预测轨迹信息获得碰撞指示信息，所述预测轨迹信息用于指示预测的多个移动物体的轨迹，所述多个移动物体包括目标车辆，所述道路环境信息用于指示所述轨迹所在的道路的行驶环境，所述碰撞指示信息包括第一时间信息和第一概率信息，所述第一时间信息用于指示预测所述目标车辆将发生碰撞的时间，所述第一概率信息用于指示预测所述碰撞发生的概率；
    发送单元，用于向所述目标车辆发送所述碰撞指示信息。
  20. 根据权利要求19所述的装置，其特征在于，行驶环境包括以下内容中的至少一项：天气、能见度、光照强度、道路类型、车道数量、道路平坦程度、道路光滑程度、道路施工情况、交通行为历史统计情况和交通流量情况。
  21. 根据权利要求19或20所述的装置，其特征在于，所述碰撞指示信息还包括位置信息，所述位置信息用于指示预测所述碰撞将发生的位置。
  22. 根据权利要求19-21任一项所述的装置，其特征在于，所述碰撞指示信息还包括下述预测的信息中的至少一项：
    与所述目标车辆碰撞的所述移动物体的标识信息、碰撞等级信息、碰撞类型信息、剩余碰撞时间信息、所述碰撞的标识信息、所述碰撞所在的瓦片的标识信息、所述碰撞所在的道路的标识信息、影响所述碰撞的地图中动态要素的标识信息和预警信息；
    其中，所述碰撞等级信息用于指示所述碰撞的严重程度，所述碰撞类型信息用于指示所述碰撞的类型，所述剩余碰撞时间信息用于指示所述碰撞将发生的时间距离当前时间的时间差，所述预警信息用于指示基于所述碰撞向驾驶员或驾驶系统提醒的内容。
  23. 根据权利要求19-22任一项所述的装置，其特征在于，所述装置还包括处理单元，用于：在所述多个移动物体的轨迹发生变化时和/或影响所述碰撞的地图中动态要素发生变化时，更新所述碰撞指示信息或者删除所述碰撞指示信息。
  24. 根据权利要求19-23任一项所述的装置，其特征在于，所述处理单元，还用于：
    根据所述碰撞指示信息，执行交通监控、交通调度或对所述目标车辆的控制。
  25. 根据权利要求19-24任一项所述的装置，其特征在于，所述处理单元，还用于：
    确定所述目标车辆即将到达所述碰撞将发生的位置时，控制所述目标车辆执行以下操作中的至少一项：
    变换车道；
    调整行驶速度；
    更新导航路线；
    开启警示灯；和
    向驾驶员提示所述碰撞。
  26. 根据权利要求19-25任一项所述的装置，其特征在于，所述发送单元，具体用于：
    在满足下述至少一个条件时，向所述目标车辆发送所述碰撞指示信息：
    预测所述碰撞发生的概率大于第一阈值；
    所述目标车辆当前的位置与预测所述碰撞将发生的位置之间的最小距离小于第二阈值；
    预测所述碰撞将发生的位置所属的道路为所述目标车辆所在的道路；和
    预测所述碰撞将发生的位置所属的瓦片为所述目标车辆所在的瓦片。
  27. 根据权利要求19-26任一项所述的装置，其特征在于，所述道路环境信息是基于地图中的动态图层数据和静态图层数据获得，所述预测轨迹信息是基于所述多个移动物体的运动状态数据和驾驶员信息获得。
  28. 根据权利要求19-27任一项所述的装置，其特征在于，所述装置还包括存储单元，用于：将所述碰撞指示信息作为地图数据进行存储。
  29. 一种数据使用装置，其特征在于，所述装置包括：
    接收单元，获取碰撞指示信息，所述碰撞指示信息包括第一时间信息和第一概率信息，所述第一时间信息用于指示预测所述目标车辆将发生碰撞的时间，所述第一概率信息用于指示预测所述碰撞发生的概率；
    处理单元，用于根据所述碰撞指示信息，执行对所述目标车辆的控制。
  30. 根据权利要求29所述的装置，其特征在于，所述碰撞指示信息还包括位置信息，所述位置信息用于指示预测所述碰撞将发生的位置。
  31. 根据权利要求29或30所述的装置，其特征在于，所述碰撞指示信息还包括下述信息中的至少一项：
    与所述目标车辆碰撞的所述移动物体的标识信息、碰撞等级信息、碰撞类型信息、剩余碰撞时间信息、所述碰撞的标识信息、所述碰撞所在的瓦片的标识信息、所述碰撞所在的道路的标识信息、影响所述碰撞的地图中动态要素的标识信息和预警信息；
    其中，所述碰撞等级信息用于指示所述碰撞的严重程度，所述碰撞类型信息用于指示所述碰撞的类型，所述剩余碰撞时间信息用于指示所述碰撞将发生的时间距离当前时间的时间差，所述预警信息用于指示基于所述碰撞向驾驶员或驾驶系统提醒的内容。
  32. 根据权利要求29-31任一项所述的装置，其特征在于，所述处理单元，具体用于：
    确定所述目标车辆即将到达所述碰撞发生的位置时，控制所述目标车辆执行以下操作中的至少一项：
    变换车道；
    调整行驶速度；
    更新导航路线；
    开启警示灯；和
    向驾驶员提示所述碰撞。
  33. 根据权利要求29-31任一项所述的装置，其特征在于，所述处理单元，具体用于：
    在预测所述碰撞发生的概率大于第一预设阈值，且在所述目标车辆将发生碰撞的时间距离当前时间的时间差小于第二预设阈值时，执行对所述目标车辆的控制。
  34. 根据权利要求29-33任一项所述的装置，其特征在于，所述处理单元，还用于：
    在所述目标车辆将发生碰撞的时间距离当前时间的时间差小于第三预设阈值和/或所述目标车辆的当前位置距离所述碰撞发生的位置之间的距离小于第四预设阈值时，控制所述目标车辆在当前车道紧急制动或者变道。
  35. 根据权利要求29-34任一项所述的装置，其特征在于，所述处理单元，还用于：
    在预测到有多个移动物体同时与所述目标车辆发生碰撞时，根据所述目标车辆与每个移动物体碰撞的严重程度，获得所述目标车辆的应对策略。
  36. 根据权利要求29-35任一项所述的装置，其特征在于，所述装置还包括显示单元，所述显示单元用于通过以下方式中的至少一种在所述目标车辆的显示界面上呈现所述碰撞指示信息：
    呈现预测的将与所述目标车辆发生碰撞的所述移动物体；
    呈现预测所述碰撞发生的时间距离当前时间的时间差；
    呈现预测发生碰撞的概率超过第五预设阈值的碰撞对应的所述碰撞指示信息；
    呈现预测发生碰撞的等级超过第六预设阈值的碰撞对应的所述碰撞指示信息；
    呈现预测的在导航路径上发生的碰撞对应的所述碰撞指示信息；
    呈现用户选择的等级或用户选择的类型的碰撞对应的所述碰撞指示信息；
    用不同颜色呈现不同等级的碰撞对应的所述碰撞指示信息；和
    用不同颜色呈现不同类型的碰撞对应的所述碰撞指示信息。
  37. 一种电子地图，其特征在于，所述地图包括碰撞指示信息，所述碰撞指示信息包括时间信息和概率信息，所述时间信息用于指示目标车辆将发生碰撞的时间，所述概率信息用于指示所述碰撞发生的概率。
  38. 一种数据生成装置，其特征在于，所述装置包括存储器和处理器，所述存储器存储计算机程序指令，所述处理器运行所述计算机程序指令以使所述装置执行如权利要求1-10任一项所述的方法。
  39. 一种数据使用装置，其特征在于，所述装置包括存储器和处理器，所述存储器存储计算机程序指令，所述处理器运行所述计算机程序指令以使所述装置执行如权利要求11-18任一项所述的方法。
  40. 一种车辆，其特征在于，所述车辆包括如权利要求29-36或39任一项所述的装置。
  41. 一种计算机可读存储介质，其特征在于，所述计算机可读存储介质存储有程序指令，所述程序指令用于实现权利要求1-10或权利要求11-18中任一项所述的方法。
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