Risk driving control method, system, terminal and medium based on vehicle collaboration

Abstract

The present invention discloses a risk driving control method, system, terminal and medium based on vehicle collaboration, which relates to the field of traffic safety. The key points of its technical solution are: the present invention dynamically selects multiple cooperative vehicles to establish short-range communication as the position of a target vehicle changes during driving, and then compares the first vehicle status data of the target vehicle and the second vehicle status data synchronously transmitted by multiple cooperative vehicles after alignment processing. This can eliminate the interference of road characteristics on the identification of risky driving behaviors without relying on road characteristics, and can reduce the influence of factors such as driver's behavioral habits and vehicle characteristics on the identification of risky driving behaviors, and can perform timely and reliable risk driving control on a single vehicle in a complex environment.

Description

Technical Field

[0001] The present invention relates to the field of traffic safety, and more specifically, to a risk driving control method, system, terminal and medium based on vehicle collaboration. Background Art

[0002] Risky driving behavior identification technology is an important research direction in the field of traffic safety. It identifies unsafe driving behaviors that may cause traffic accidents by analyzing the driver's behavior and / or vehicle status. Among them, the vehicle status generally includes information such as position, speed, direction, angle, acceleration, etc., and the factors that cause the vehicle status to change include not only the driver's behavior, but also road characteristics and weather conditions, road characteristics such as road slope, road curvature and other road linear data.

[0003] To this end, the prior art records risk driving identification technology that determines speed thresholds for different road sections based on road types and weather conditions, and determines that the vehicle is in a risky state when the actual driving speed of the vehicle exceeds the speed threshold. However, road types are mainly divided from the perspective of the overall speed limit of the road, and it is difficult to identify the risky driving of a single vehicle in real time and accurately; in addition, some prior arts also record risk driving identification technology that considers specific road linear data, and its implementation process requires continuous collection or acquisition of road linear data according to changes in vehicle position, which not only makes data collection difficult, but also makes risk driving identification more complex; in addition, due to certain differences in behavioral characteristics and risk preferences of different drivers, there is a certain recognition error when comparing the feature data processed for a single vehicle with the set data.

[0004] Therefore, how to research and design a risk driving control method, system, terminal and medium based on vehicle collaboration that can overcome the above-mentioned defects is a problem that we urgently need to solve. Summary of the invention

[0005] In order to address the deficiencies in the prior art, the purpose of the present invention is to provide a risk driving management and control method, system, terminal and medium based on vehicle collaboration, which can eliminate the interference of road characteristics on the identification of risky driving behavior without relying on road characteristics, and can reduce the influence of factors such as driver's behavioral habits and vehicle characteristics on the identification of risky driving behavior, and can perform timely and reliable risk driving management and control of a single vehicle in a complex environment.

[0006] The above technical objectives of the present invention are achieved through the following technical solutions: In the first aspect, a risk driving control method based on vehicle collaboration is provided, comprising the following steps: Determine the communication range of the target vehicle participating in vehicle coordination according to the positioning information of the target vehicle; Establishing short-range communication between the target vehicle and a plurality of cooperative vehicles within a corresponding communication range by means of an active communication request and / or a passive communication request; Collecting first vehicle status data of a target vehicle and receiving second vehicle status data synchronously transmitted by a plurality of coordinated vehicles; adjusting a timestamp of the first vehicle status data and / or the second vehicle status data to align the first vehicle status data with the second vehicle status data; analyzing driving behavior deviations between the target vehicle and the plurality of cooperative vehicles based on the aligned first vehicle state data and the second vehicle state data; The driving behavior deviations of all vehicle states are compared with the corresponding deviation thresholds, and a risky driving signal is generated when the driving behavior deviation of any vehicle state exceeds the corresponding deviation threshold.

[0007] Furthermore, the communication range determination process of the target vehicle participating in the vehicle collaboration is specifically as follows: Determine the maximum distance L for short-range communication, and determine the communication range with the target vehicle's positioning information D as the midpoint and the maximum distance L as the communication distance .

[0008] Furthermore, the communication range determination process of the target vehicle participating in the vehicle collaboration is specifically as follows: The distance coefficient is calculated according to the ratio of the number of remaining cooperative vehicles that have not established short-range communication with the target vehicle to the maximum communication number of the target vehicle; Determine the maximum distance L of short-range communication, and determine the communication range with the target vehicle's positioning information D as the midpoint and the product d of the maximum distance L and the distance coefficient as the communication distance .

[0009] Furthermore, the active communication request is a communication request sent by a vehicle within a communication range corresponding to the target vehicle, and the passive communication request is a communication request sent by a vehicle within a communication range corresponding to the target vehicle to the target vehicle.

[0010] Further, the priority of the target vehicle in selecting a vehicle to establish short-range communication is determined by the positioning distance between the vehicles, the number of lane crossings between the vehicles, and / or the safety status of the vehicles; The smaller the positioning distance between the vehicle and the target vehicle, the higher the priority of the target vehicle in selecting the corresponding vehicle to establish short-range communication; The fewer the number of lane crossings between the vehicle and the target vehicle, the higher the priority of the target vehicle in selecting the corresponding vehicle to establish short-range communication; And, the priority of the vehicle being in a non-risky driving state is higher than the priority of the vehicle being in a risky driving state.

[0011] Furthermore, the analytical expression of the driving behavior deviation is specifically: ; in, Indicates that the first vehicle status data With Second vehicle status data Vehicle status The driving behavior deviations analyzed; Indicates the collection period of the first vehicle status data and the second vehicle status data; Indicates the vehicle status in the first vehicle status data The corresponding data is based on the time deviation Adjust the aligned data; Indicates a time deviation for adjusting the timestamp of the first vehicle status data; Indicates Second vehicle status data middle Vehicle status at the moment The corresponding data; Indicates the maximum time deviation; Indicates that the first vehicle status data With multiple second vehicle status data Vehicle status The driving behavior deviations analyzed; Indicates the number of second vehicle status data.

[0012] Further, if the target vehicle generates a risky driving signal, the target vehicle is marked as being in a risky driving state; When the target vehicle and the coordinating vehicle with which short-range communication has been established are both marked as risky driving states, the corresponding target vehicle and the coordinating vehicle disconnect the short-range communication connection.

[0013] In a second aspect, a risk driving control system based on vehicle collaboration is provided, and the system is used to implement the risk driving control method based on vehicle collaboration as described in any one of the first aspects, including: A range determination module, used to determine the communication range of the target vehicle participating in the vehicle coordination according to the positioning information of the target vehicle; A communication establishment module, used to establish short-range communication between the target vehicle and a plurality of cooperative vehicles within a corresponding communication range in the form of an active communication request and / or a passive communication request; A data acquisition module, used for collecting first vehicle status data of a target vehicle and receiving second vehicle status data synchronously transmitted by a plurality of coordinated vehicles; a data alignment module, configured to adjust a timestamp of the first vehicle status data and / or the second vehicle status data to align the first vehicle status data with the second vehicle status data; A deviation analysis module, configured to analyze driving behavior deviations between a target vehicle and a plurality of cooperative vehicles based on the aligned first vehicle state data and the second vehicle state data; The risk analysis module is used to compare the driving behavior deviations of all vehicle states with the corresponding deviation thresholds, and generate a risky driving signal when the driving behavior deviation of any vehicle state exceeds the corresponding deviation threshold.

[0014] In a third aspect, a computer terminal is provided, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, a risk driving control method based on vehicle collaboration as described in any one of the first aspects is implemented.

[0015] In a fourth aspect, a computer-readable medium is provided, on which a computer program is stored, and the computer program is executed by a processor to implement the risk driving management method based on vehicle collaboration as described in any one of the first aspects.

[0016] Compared with the prior art, the present invention has the following beneficial effects: 1. The risk driving control method based on vehicle collaboration provided by the present invention dynamically selects multiple cooperative vehicles to establish short-range communication as the position of the target vehicle changes during driving, and then compares the first vehicle status data of the target vehicle and the second vehicle status data synchronously transmitted by multiple cooperative vehicles after alignment processing. It can eliminate the interference of road characteristics on the identification of risky driving behaviors without relying on road characteristics, and can reduce the influence of factors such as driver behavior habits and vehicle characteristics on the identification of risky driving behaviors, and can perform timely and reliable risk driving control on a single vehicle in a complex environment; 2. The present invention uses short-range communication technology to achieve data transmission between multiple close-range vehicles, which can better adapt to the iterative update of cooperative vehicles caused by frequent changes in vehicle positions, and can maintain stable and reliable data transmission in harsh environments; 3. The present invention dynamically determines the communication range according to the maximum distance of short-range communication, the positioning information of the target vehicle, and the number of remaining cooperative vehicles that have not established short-range communication with the target vehicle, and can realize the rapid establishment of short-range communication between vehicles on roads with different vehicle densities; 4. The present invention takes into account the driving habits of different drivers in different driving scenarios, and by aligning the first vehicle state data and / or the second vehicle state data, the analysis accuracy of driving behavior deviation can be made higher; 5. In the present invention, when the target vehicle and the coordinating vehicle that have established short-range communication are both marked as risky driving states, the corresponding target vehicle and the coordinating vehicle disconnect the short-range communication connection, which can effectively avoid the superposition of recognition errors. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The drawings described herein are used to provide a further understanding of the embodiments of the present invention, constitute a part of this application, and do not constitute a limitation of the embodiments of the present invention. In the drawings: Figure 1 is a flow chart of Embodiment 1 of the present invention; Figure 2 It is a system block diagram in Example 2 of the present invention. DETAILED DESCRIPTION

[0018] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with embodiments and drawings. The exemplary embodiments of the present invention and their description are only used to explain the present invention and are not intended to limit the present invention.

[0019] Example 1: Risk driving control method based on vehicle collaboration, such as Figure 1 As shown, the following steps are included: S1: Determine the communication range of the target vehicle participating in vehicle coordination according to the positioning information of the target vehicle; S2: establishing short-range communication between the target vehicle and a plurality of cooperative vehicles within a corresponding communication range by means of an active communication request and / or a passive communication request; S3: collecting first vehicle status data of the target vehicle and receiving second vehicle status data synchronously transmitted by multiple coordinated vehicles; S4: adjusting the timestamp of the first vehicle status data and / or the second vehicle status data to align the first vehicle status data with the second vehicle status data; S5: analyzing driving behavior deviations between the target vehicle and the plurality of cooperative vehicles based on the aligned first vehicle state data and the second vehicle state data; S6: Compare the driving behavior deviations of all vehicle states with corresponding deviation thresholds, and generate a risky driving signal when the driving behavior deviation of any vehicle state exceeds the corresponding deviation threshold.

[0020] In step S1, any vehicle on the road can be used as a target vehicle, and can also be a cooperative vehicle of other vehicles. The positioning information is the data collected by the vehicle itself.

[0021] As an optional implementation, the communication range determination process of the target vehicle participating in the vehicle collaboration is specifically as follows: determining the maximum distance L of short-range communication, and determining the communication range with the positioning information D of the target vehicle as the midpoint and the maximum distance L as the communication distance. .

[0022] As another optional implementation, the communication range determination process of the target vehicle participating in vehicle cooperation is specifically as follows: a distance coefficient is calculated based on the ratio of the number of remaining cooperative vehicles that have not established short-range communication with the target vehicle to the maximum communication number of the target vehicle; the maximum distance L of short-range communication is determined, and the communication range is determined with the positioning information D of the target vehicle as the midpoint and the product d of the maximum distance L and the distance coefficient as the communication distance. .

[0023] It should be noted that the communication range mainly refers to the distance range along the length of the road, covering all lanes within the range; in addition, in order to further accurately locate, the lane width can also be considered to calculate the distance.

[0024] In step S2, the active communication request is a communication request sent by a vehicle within the communication range corresponding to the target vehicle, and the passive communication request is a communication request sent by a vehicle within the communication range corresponding to the target vehicle to the target vehicle.

[0025] Generally, the target vehicle has both active communication requests and passive communication requests. For example, the maximum number of communications for a target vehicle is 6, and the number of remaining cooperative vehicles that have not established short-range communications with the target vehicle is 3. Then, the number of short-range communications allowed to be established with active communication requests can be allocated to 2, and the number of short-range communications allowed to be established with passive communication requests can be allocated to 1.

[0026] The number of active communication requests and passive communication requests allocated can be dynamically updated according to the change in the number of remaining cooperative vehicles that have not established short-range communication with the target vehicle.

[0027] In addition, the priority of the target vehicle when selecting a vehicle to establish short-range communication is determined by the positioning distance between vehicles, the number of lane changes between vehicles, or the safety status of the vehicles.

[0028] Specifically, if the positioning distance between the vehicle and the target vehicle is smaller, the target vehicle has a higher priority when selecting the corresponding vehicle to establish short-range communication; if the number of lane changes between the vehicle and the target vehicle is smaller, the target vehicle has a higher priority when selecting the corresponding vehicle to establish short-range communication; and, the priority of a vehicle in a non-risky driving state is higher than the priority of a vehicle in a risky driving state.

[0029] In addition, the priority is determined by the positioning distance between vehicles, the number of lane changes between vehicles, or the safety status of the vehicles.

[0030] In step S3, data between the two vehicles establishing short-range communication is transmitted bidirectionally, and the first vehicle status data of the target vehicle is collected by the device or sensor carried by the vehicle itself and can be directly called. The second vehicle status data of the cooperative vehicle needs to be transmitted.

[0031] In steps S4 and S5, the data needs to be aligned in consideration of the driving habits of different drivers in different driving scenarios and the order of vehicles. The alignment method can be to adjust the timestamp of the first vehicle status data or the second vehicle status data, or to adjust the timestamps of the first vehicle status data and the second vehicle status data at the same time, which is not limited here.

[0032] As an optional implementation, the alignment of a single pair of data can be achieved by minimizing the vehicle state deviation between the first vehicle state data and the single second vehicle state data as an optimization goal. The corresponding driving behavior deviation can be calculated by integrating and summing the deviations of the aligned data.

[0033] For example, the analytical expression of driving behavior deviation is: ; in, Indicates that the first vehicle status data With Second vehicle status data Vehicle status The driving behavior deviations analyzed; Indicates the collection period of the first vehicle status data and the second vehicle status data; Indicates the vehicle status in the first vehicle status data The corresponding data is based on the time deviation Adjust the aligned data; Indicates a time deviation for adjusting the timestamp of the first vehicle status data; Indicates Second vehicle status data middle Vehicle status at the moment The corresponding data; Indicates the maximum time deviation; Indicates that the first vehicle status data With multiple second vehicle status data Vehicle status The driving behavior deviations analyzed; Indicates the number of second vehicle status data.

[0034] As another optional implementation, the driving behavior deviation may be calculated by aligning the distribution of the peak features in the first vehicle state data and the single second vehicle state data, and then summing the difference in the peak features in the aligned data.

[0035] In step S6, after the target vehicle generates a risky driving signal, the driver can be prompted through the vehicle-mounted alarm device, or the risky driving signal can be uploaded to the host computer through the communication module to realize remote alarm.

[0036] When a target vehicle generates a risky driving signal, the target vehicle is marked as being in a risky driving state; when the target vehicle and the coordinating vehicle that have established short-range communication are both marked as being in a risky driving state, the corresponding target vehicle and the coordinating vehicle are disconnected from the short-range communication connection, which can effectively avoid the superposition of recognition errors.

[0037] Embodiment 2: A risk driving control system based on vehicle collaboration, the system is used to implement the risk driving control method based on vehicle collaboration as described in Embodiment 1, such as Figure 2 As shown, it includes a scope determination module, a communication establishment module, a data acquisition module, a data alignment module, a deviation analysis module and a risk analysis module.

[0038] Among them, a range determination module is used to determine the communication range of the target vehicle participating in vehicle cooperation according to the positioning information of the target vehicle; a communication establishment module is used to establish short-range communication between the target vehicle and multiple cooperative vehicles within the corresponding communication range in the form of active communication request and / or passive communication request; a data acquisition module is used to collect the first vehicle status data of the target vehicle and receive the second vehicle status data transmitted synchronously by multiple cooperative vehicles; a data alignment module is used to adjust the timestamp of the first vehicle status data and / or the second vehicle status data to align the first vehicle status data with the second vehicle status data; a deviation analysis module is used to analyze the driving behavior deviation between the target vehicle and multiple cooperative vehicles based on the aligned first vehicle status data and the second vehicle status data; a risk analysis module is used to compare the driving behavior deviations of all vehicle states with the corresponding deviation thresholds, and generate a risk driving signal when the driving behavior deviation of any vehicle state exceeds the corresponding deviation threshold.

[0039] The present invention also records a computer terminal, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, the risk driving control method based on vehicle collaboration as described in Example 1 is implemented.

[0040] The present invention also records a computer-readable medium on which a computer program is stored. The computer program is executed by a processor to implement the risk driving control method based on vehicle collaboration as described in Example 1.

[0041] Working principle: The present invention can dynamically select multiple cooperative vehicles to establish short-range communication as the position of the target vehicle changes during driving, and then compare the first vehicle status data of the target vehicle and the second vehicle status data synchronously transmitted by multiple cooperative vehicles after alignment processing. It can eliminate the interference of road characteristics on the identification of risky driving behaviors without relying on road characteristics, and can reduce the impact of factors such as driver's behavioral habits and vehicle characteristics on the identification of risky driving behaviors, and can perform timely and reliable risk driving control of individual vehicles in complex environments.

[0042] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0043] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0044] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0045] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0046] The specific implementation methods described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific implementation method of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. The risk driving control method based on vehicle collaboration is characterized by: The following steps are involved: Determine the communication range of the target vehicle participating in vehicle coordination according to the positioning information of the target vehicle; Establishing short-range communication between the target vehicle and a plurality of cooperative vehicles within a corresponding communication range by means of an active communication request and / or a passive communication request; Collecting first vehicle status data of a target vehicle and receiving second vehicle status data synchronously transmitted by a plurality of coordinated vehicles; adjusting a timestamp of the first vehicle status data and / or the second vehicle status data to align the first vehicle status data with the second vehicle status data; analyzing driving behavior deviations between the target vehicle and the plurality of cooperative vehicles based on the aligned first vehicle state data and the second vehicle state data; The driving behavior deviations of all vehicle states are compared with the corresponding deviation thresholds, and a risky driving signal is generated when the driving behavior deviation of any vehicle state exceeds the corresponding deviation threshold.

2. The risk driving control method based on vehicle collaboration according to claim 1 is characterized in that: The communication range determination process of the target vehicle participating in vehicle coordination is specifically as follows: Determine the maximum distance L for short-range communication, and determine the communication range with the target vehicle's positioning information D as the midpoint and the maximum distance L as the communication distance .

3. The risk driving control method based on vehicle collaboration according to claim 1 is characterized in that: The communication range determination process of the target vehicle participating in vehicle coordination is specifically as follows: The distance coefficient is calculated according to the ratio of the number of remaining cooperative vehicles that have not established short-range communication with the target vehicle to the maximum communication number of the target vehicle; Determine the maximum distance L of short-range communication, and determine the communication range with the target vehicle's positioning information D as the midpoint and the product d of the maximum distance L and the distance coefficient as the communication distance .

4. The risk driving control method based on vehicle collaboration according to claim 1 is characterized in that: The active communication request is a communication request sent by a vehicle within the communication range corresponding to the target vehicle, and the passive communication request is a communication request sent by a vehicle within the communication range corresponding to the target vehicle to the target vehicle.

5. The risk driving control method based on vehicle collaboration according to claim 1 is characterized in that: The priority of target vehicle selection when establishing short-range communication with a vehicle is determined by the positioning distance between vehicles, the number of lane crossings between vehicles, and / or the safety status of the vehicles; The smaller the positioning distance between the vehicle and the target vehicle, the higher the priority of the target vehicle in selecting the corresponding vehicle to establish short-range communication; The fewer the number of lane crossings between the vehicle and the target vehicle, the higher the priority of the target vehicle in selecting the corresponding vehicle to establish short-range communication; And, the priority of the vehicle being in a non-risky driving state is higher than the priority of the vehicle being in a risky driving state.

6. The risk driving control method based on vehicle collaboration according to claim 1 is characterized in that: The analytical expression of the driving behavior deviation is specifically: ； in, Indicates that the first vehicle status data With Second vehicle status data Vehicle status The driving behavior deviations analyzed; Indicates the collection period of the first vehicle status data and the second vehicle status data; Indicates the vehicle status in the first vehicle status data The corresponding data is based on the time deviation Adjust the aligned data; Indicates a time deviation for adjusting the timestamp of the first vehicle status data; Indicates Second vehicle status data middle Vehicle status at the moment The corresponding data; Indicates the maximum time deviation; Indicates that the first vehicle status data With multiple second vehicle status data Vehicle status The driving behavior deviations analyzed; Indicates the number of second vehicle status data.

7. The risk driving control method based on vehicle collaboration according to claim 1 is characterized in that: If the target vehicle generates a risky driving signal, the target vehicle is marked as being in a risky driving state; When the target vehicle and the coordinating vehicle with which short-range communication has been established are both marked as risky driving states, the corresponding target vehicle and the coordinating vehicle disconnect the short-range communication connection.

8. The risk driving control system based on vehicle collaboration is characterized by: The system is used to implement the risk driving control method based on vehicle collaboration as described in any one of claims 1 to 7, including: A range determination module, used to determine the communication range of the target vehicle participating in the vehicle coordination according to the positioning information of the target vehicle; A communication establishment module, used to establish short-range communication between the target vehicle and a plurality of cooperative vehicles within a corresponding communication range in the form of an active communication request and / or a passive communication request; A data acquisition module, used for collecting first vehicle status data of a target vehicle and receiving second vehicle status data synchronously transmitted by a plurality of coordinated vehicles; a data alignment module, configured to adjust a timestamp of the first vehicle status data and / or the second vehicle status data to align the first vehicle status data with the second vehicle status data; A deviation analysis module, configured to analyze driving behavior deviations between a target vehicle and a plurality of cooperative vehicles based on the aligned first vehicle state data and the second vehicle state data; The risk analysis module is used to compare the driving behavior deviations of all vehicle states with the corresponding deviation thresholds, and generate a risky driving signal when the driving behavior deviation of any vehicle state exceeds the corresponding deviation threshold.

9. A computer terminal comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the risk driving management method based on vehicle collaboration as described in any one of claims 1 to 7 is implemented.

10. A computer readable medium having a computer program stored thereon, characterized in that: The computer program is executed by a processor to implement the risk driving management method based on vehicle collaboration as described in any one of claims 1 to 7.

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