WO2021179340A1 - 一种基于车辆行驶的危险预警方法、系统及存储介质 - Google Patents

一种基于车辆行驶的危险预警方法、系统及存储介质 Download PDF

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WO2021179340A1
WO2021179340A1 PCT/CN2020/079785 CN2020079785W WO2021179340A1 WO 2021179340 A1 WO2021179340 A1 WO 2021179340A1 CN 2020079785 W CN2020079785 W CN 2020079785W WO 2021179340 A1 WO2021179340 A1 WO 2021179340A1
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terminal device
vehicle
risk
traffic
state information
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PCT/CN2020/079785
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English (en)
French (fr)
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董孝峰
钟波
宋靖涛
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博睿泰克科技（宁波）有限公司
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    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/16—Anti-collision systems
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/01—Detecting movement of traffic to be counted or controlled
    • G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/01—Detecting movement of traffic to be counted or controlled
    • G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
    • G08G1/0125—Traffic data processing

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  • the present invention relates to the field of communication technology, in particular to a dangerous early warning method, system and storage medium based on vehicle driving.
  • Vehicle driving safety is a system problem.
  • the unmanned driving system from the perspective of the individual, perceives road information through perceptual sensors such as vision sensors, laser sensors, and radar sensors. Relying on GPS+IMU to provide richer information such as yaw rate, angular acceleration, etc., to help the positioning and decision-making control of autonomous vehicles.
  • perceptual sensors such as vision sensors, laser sensors, and radar sensors.
  • GPS+IMU Relying on GPS+IMU to provide richer information such as yaw rate, angular acceleration, etc., to help the positioning and decision-making control of autonomous vehicles.
  • the application number 201910542034.6 “Active Collision Avoidance Enhanced Learning Control System and Method for Intelligent Connected Hybrid Electric Vehicles” discloses an active collision avoidance enhanced learning control system and method.
  • the vehicle obtains traffic information through the data perception module, and the vehicle autonomously detects The vehicle is in a safe state, and the vehicle speed is controlled through independent learning and feedback signals.
  • the application number 201910581894.0 “A Wi-Fi Wireless-based Intelligent Transportation System” document discloses the use of Wi-Fi wireless as the communication carrier of the traffic management system and the user's smart device, and creates an algorithm based on the optimized angle and spherical distance.
  • the application number 201910614671.X discloses a method for predicting the state of intelligent transportation based on machine learning.
  • this method establishes an Encoder-Decoder hybrid model based on LSTM, and realizes the intelligence of the traffic state through the training of the hybrid model Real-time prediction.
  • This method particularly emphasizes the effects of time and space, adds meteorological attributes, road network attributes, and social attributes, and can improve the accuracy of road traffic speed prediction.
  • a vehicle-based danger early warning method that aims to realize real-time judgment of whether there is a traffic risk according to the vehicles and pedestrians on the road.
  • a dangerous warning method based on vehicle driving which includes the following steps:
  • the terminal device represents a terminal device associated with a driving vehicle or pedestrian
  • acquiring the mobile state information of the terminal device includes:
  • a multi-antenna detection system is used to detect the coordinates, direction and speed of the terminal device.
  • the method for predicting the existence of traffic risks specifically includes the following steps:
  • a corresponding control instruction is generated and sent to the vehicle control system, and the vehicle control system controls the current vehicle to avoid the vehicle according to the control instruction.
  • a hazard warning system based on vehicle driving which includes:
  • the multi-antenna signal detection module is used to obtain the wireless signal of each terminal device on the road in real time; wherein, the terminal device represents a terminal device associated with a vehicle or a pedestrian; and
  • the risk perception module is used for predicting the terminal equipment with traffic risk based on the real-time position of each terminal device in the road map and combined with the movement state information of the terminal device.
  • the multi-antenna signal detection module is mainly composed of an active zero-IF antenna and a software baseband.
  • the risk perception module includes:
  • a position prediction unit configured to predict the next grid position of each terminal device in a road grid area formed by a unit area according to the movement state information of the terminal device
  • the judging unit is used to judge whether there is a situation in the grid area where the grid position is occupied at the same time. If so, it means that the vehicle or pedestrian associated with the terminal device that enters the current grid position at the same time There is a risk of collision.
  • it also includes a risk assessment module:
  • the risk assessment module is configured to generate a collision prompt message and send the collision prompt information to the corresponding terminal device when the risk perception module senses that there is a traffic risk; or
  • a corresponding control instruction is generated and sent to the vehicle control system, and the vehicle control system controls the current vehicle to avoid the vehicle according to the control instruction.
  • It also includes a storage medium, in which the following software is executed, and the software is used to execute the above-mentioned danger warning method.
  • the beneficial effects of the above technical solution are: through the above danger warning method and system, the pedestrians and vehicles participating in the traffic on the road can be monitored in real time, and the movement status information of the pedestrians or the vehicle-related terminal equipment on the road can be collected in real time. It predicts pedestrians and vehicles that are at traffic risk, thereby overcoming the problem of the inability to predict the risk in time due to emergencies such as pedestrian intrusion or the existence of detection blind spots when the vehicle detects the risk through the detector in the prior art.
  • FIG. 1 is a schematic flowchart of an embodiment of a method for warning of danger based on vehicle driving according to the present invention
  • FIG. 2 is a schematic flowchart of a method for predicting the existence of a traffic risk in an embodiment of a vehicle-driving-based danger warning method of the present invention
  • FIG. 3 is a schematic flowchart of another embodiment of a method for warning of danger based on vehicle driving according to the present invention
  • FIG. 4 is a schematic flowchart of another embodiment of a method for warning of danger based on vehicle driving according to the present invention.
  • FIG. 5 is a schematic flowchart of another embodiment of a dangerous early warning method based on vehicle driving according to the present invention.
  • Fig. 6 is a schematic structural diagram of an embodiment of a dangerous early warning system based on vehicle driving according to the present invention.
  • FIG. 7 is a schematic flowchart of a route prediction by a location prediction unit in an embodiment of a vehicle driving-based danger early warning system of the present invention.
  • FIG. 8 is a schematic diagram of the processing flow of a multi-antenna sensing module in an embodiment of a vehicle driving-based danger early warning system of the present invention
  • FIG. 9 is a schematic diagram of a multi-antenna structure of a front end with baseband signals in an embodiment of a dangerous early warning system based on vehicle driving of the present invention.
  • Fig. 10 is a schematic diagram of a zero-IF antenna structure in an embodiment of a vehicle-driving-based danger warning system of the present invention.
  • Multi-antenna signal detection module 2. Risk perception module; 3. Risk assessment module;
  • the technical scheme of the present invention provides a dangerous early warning method based on vehicle driving.
  • an embodiment of a dangerous warning method based on vehicle driving includes the following steps:
  • each terminal device in the road map According to the real-time location of each terminal device in the road map, and combined with the terminal device's movement status information, predict the terminal device that has a traffic risk.
  • the road grid area mainly composed of a unit area in the road map may specifically include the identification code of the terminal device and real-time coordinates, direction, speed parameters, etc. according to the received movement state information.
  • the risk factor of the terminal device holder is identified, the exercise schedule of the terminal device is weighted and predicted, the use time sequence of the real-time map grid and the traffic signal time sequence are read to determine whether the terminal device is Comply with traffic rules, so as to predict terminal equipment that does not comply with traffic rules in time.
  • the road surface is planned into a grid of unit area, and the use time sequence and use state are set for each grid.
  • the uplink signal transmitted by the terminal device is received, and the uplink signal processing is used to obtain each grid.
  • the movement status information of each terminal device such as the speed, direction, coordinates, and the user identification code of the terminal device. Based on the above terminal device information, predict the pedestrian or vehicle route timetable associated with each terminal device to schedule the grid occupancy time And time, if the grid occupancy time and time conflict, there is a traffic risk.
  • acquiring the mobile state information of the terminal device includes:
  • a multi-antenna detection system is used to detect the coordinates, direction and speed of the terminal equipment, as well as the user identification code. In order to ensure the coverage of all terminal equipment users on the entire road surface, it adopts a phased array radar time of arrival (TOA) lateral positioning method.
  • TOA phased array radar time of arrival
  • the method for predicting the presence of traffic risks specifically includes the following steps:
  • the mobile state information of the terminal device predict the next grid position of each terminal device in the road grid area constituted by the unit area;
  • the above technical solution determines the traffic risk coefficient according to the different degrees of conflict between grid occupancy time and time. The higher the risk coefficient, the greater the potential traffic hazard.
  • Step S11 In the grids formed by unit area, each grid is set with a usage sequence and an available state;
  • Step S12 Receive the uplink signal of the terminal equipment to obtain the movement state information of each terminal equipment;
  • Step S13 predict the next grid position of each terminal device according to the state information of the terminal device
  • Step S14 Determine whether there is a situation in which the grid position is occupied at the same time in the grid area;
  • step S15 If yes, go to step S15;
  • step S11 If not, return to step S11, continue to predict the trajectory and direction of the terminal device, and report the route schedule of pedestrians or vehicles associated with each terminal device;
  • Step S15 It is indicated that the vehicle or pedestrian associated with the terminal device that enters the current grid position at the same time has a traffic risk, and enters the risk assessment process, in which the sudden lane change and irregular rectangle of the terminal device are calculated as a risk factor during the risk assessment process. ; Save the driving risk in the database.
  • the terminal device is the vehicle control system of the vehicle
  • the corresponding control instruction is generated and sent to the vehicle control system, and the vehicle control system controls the current vehicle to avoid the vehicle according to the control instruction.
  • Step A1 In a grid composed of a unit area, accept the route schedule sent by the terminal device, and plan the forward route of the terminal device;
  • Step A2 in the terminal equipment list, maintain the timing and usage status of each grid
  • Step A3 Predict the use sequence and use state of the grid according to the motion state information of the terminal device.
  • the technical scheme of the present invention also includes a dangerous early warning system based on vehicle driving.
  • an embodiment of a hazard warning system based on vehicle driving includes:
  • the multi-antenna signal detection module is used to obtain the wireless signal of each terminal device on the road in real time; wherein, the terminal device refers to the terminal device associated with the vehicle or pedestrian; and
  • the risk perception module is used to predict the terminal devices that have traffic risks based on the real-time position of each terminal device in the road map and combined with the mobile status information of the terminal device.
  • the multi-antenna signal detection module further includes a multi-antenna sensing calculation module for obtaining the mobile state information of the terminal device according to the wireless signal processing of the terminal device;
  • the processing flow of the multi-antenna sensing module is as follows, as shown in Figure 8:
  • the multi-antenna signal detection module receives the uplink signal of the terminal equipment
  • the active multi-antenna system distinguishes the terminal equipment according to the user identification code and calculates the three-dimensional coordinates, moving direction and coordinates of the terminal equipment correspondingly;
  • the terminal equipment may include autonomous vehicles, ordinary smart phones, special equipment that have been installed with the terminal device data interface adapted to this technical solution, and all intelligent or non-intelligent terminal equipment data interfaces that are not adapted to this technical solution. smart phone.
  • the radar antenna is arranged on the road.
  • the distance of the phased array radar antenna is generally within a range, and the distance is relatively fixed.
  • the delay problem caused by the propagation path can be solved by setting the delay parameter.
  • this technical solution discloses two structural modes of the multi-antenna signal detection system, including a baseband signal front end deployment mode and a baseband signal front end deployment mode.
  • the baseband signal front end adds a clock synchronization module on the basis of a complete zero-IF receiver to synchronize multiple clocks with baseband signal front ends; adds a data transmission module to transmit baseband output demodulated and decoded digital signals To the multi-antenna perception calculation module; an independent transmitting antenna module is added to transmit early warning signals and prompt information to terminal equipment.
  • the baseband of the receiver realizes the demodulation and decoding of the received signal, and the decoded data and accurate time stamp are reported to
  • the multi-antenna perception and calculation module realizes the identification of the terminal device and calculates the position coordinates, speed and moving direction of the terminal device.
  • the multi-antenna perception and calculation module reports the coordinates, speed, direction and other parameters of the terminal device. Give the risk perception module.
  • the other is a multi-antenna structure without baseband signal front end, the radio frequency front end is separated from the baseband, and multiple baseband signal front ends share a software baseband.
  • the front-end without baseband signals deploys the front-end baseband with baseband signals to the back-end, and the data after the antenna receives the signal and completes the AD conversion is packaged and transmitted to the back-end software baseband by the data transmission module, and the data from multiple front-ends without baseband signals are aggregated to the software baseband.
  • the remote software baseband demodulates and decodes the digitized signal
  • the multi-antenna perception calculation module realizes the identification of the terminal device, calculates the position coordinate, speed and moving direction of the terminal device, and calculates it by the multi-antenna perception calculation module
  • the module reports the coordinates, speed, direction and other parameters of the terminal equipment to the risk perception module.
  • the multi-antenna signal detection module is mainly composed of an active zero-IF antenna and a software baseband.
  • the zero-IF antenna includes a receiving antenna, a pre-filter, a low-noise amplifier, a mixer, a low-pass filter, a programmable amplifier, an AD converter, a data transmission module, a clock synchronization module, and
  • the software baseband module can be deployed at the front end to form a baseband signal front end or at the back end to form a baseband signal front end.
  • the signal front-end and the multi-antenna sensing and calculation module jointly constitute the multi-antenna signal detection, which realizes the function of detecting and receiving the uplink signal of the terminal equipment.
  • the risk perception module includes:
  • the position prediction unit is used to predict the next grid position of each terminal device in the road grid area formed by the unit area according to the movement state information of the terminal device;
  • the judging unit is used to judge whether there is a situation in the grid area where the grid position is occupied at the same time. If so, it means that the vehicle or pedestrian associated with the terminal device that enters the current grid position at the same time is at risk of collision.
  • the system also includes a storage module (not shown in the figure).
  • the storage module stores a record of violations of each terminal device, and focuses on monitoring the terminal devices that frequently violate regulations. If the terminal device is detected In case of non-compliance, the risk assessment process is entered;
  • the traffic risks predicted by the specific risk perception module also include:
  • the terminal device continues to report the route schedule.
  • Step B1 Determine whether the terminal device has a planned route
  • step B4 If not, determine the direction of travel according to the lane of the terminal device, report the timetable to the road map according to the speed, and go to step B4;
  • step B2 If yes, go to step B2;
  • Step B2 Determine whether the current planned route needs to be re-planned
  • Step B3 re-plan the route
  • Step B4 according to the route timetable reported in real time, to register the usage sequence of the grid.
  • Step B4 also includes a risk assessment module:
  • the risk assessment module is used to generate a collision prompt message and send the collision prompt information to the corresponding terminal device when the risk perception module senses that there is a risk of collision;
  • the terminal device is the vehicle control system of the vehicle
  • the corresponding control instruction is generated and sent to the vehicle control system, and the vehicle control system controls the current vehicle to avoid the vehicle according to the control instruction.
  • the function of the risk assessment module is to assess which terminal devices may be affected by the possible trajectory of the risk maker. Sending warning information (collision prompt information) to the affected terminal equipment, or sending control instructions to the automatic driving system (vehicle control system), the affected terminal equipment includes direct impact and indirect impact.
  • this technical solution discloses an automatic driving interaction protocol, and terminal devices compatible with the protocol can receive the best parameters simulated by the system through a computer.
  • SD 128 characters; // ciphertext shadow.
  • It also includes a storage medium, in which the following software is executed, and the software is used to execute the above-mentioned danger warning method.
  • all or part of the steps in the above method embodiments can be implemented by a program instructing relevant hardware.
  • the above program can be stored in a computer readable storage medium.
  • the program is executed, the execution includes the above method implementation.
  • the aforementioned storage media include: ROM, RAM, magnetic disks, or optical disks and other media that can store program codes.

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Abstract

一种基于车辆行驶的危险预警方法、系统及存储介质，包括：实时获取每个终端设备的移动状态信息，所述终端设备是与行驶车辆或行人关联的终端设备；根据每个终端设备在道路地图中的实时位置，以及结合终端设备的移动状态信息，预测存在交通风险的终端设备。上述方法可以实时对道路上参与交通的行人和车辆进行监控，及时预测出存在交通风险的行人和车辆，克服了现有技术中的车辆通过探测器探测风险时由于突发情况如行人闯入或者探测盲区的存在导致无法及时预测风险的问题。

Description

一种基于车辆行驶的危险预警方法、系统及存储介质 技术领域
本发明涉及通信技术领域，尤其涉及一种基于车辆行驶的危险预警方法、系统及存储介质。
背景技术
车辆行驶安全是一个系统问题。无人驾驶系统，从个体的角度通过感知传感器如，视觉传感器、激光传感器、雷达传感器等感知路面信息。依靠GPS+IMU提供诸如横摆角速度、角加速度等更丰富的信息，帮助自动驾驶汽车的定位和决策控制。例如，申请号201910542034.6《智能网联混合动力汽车主动避撞增强学习控制系统和方法》文件中公开了一种主动避撞增强学习控制系统和方法，车辆通过数据感知模块获取交通信息，车辆自主检测车辆安全状态，并通过自主学习和反馈信号实现车辆速度的控制。
无人驾驶的最大优势的不知疲倦，完全依靠规则，缺点是突发事件和不可预知事件的处理。也有企业从车辆自身感知传感器以外寻找解决方案。比如，申请号201910581894.0《一种基于Wi-Fi无线的智能交通系统》文件中公开了使用Wi-Fi无线作为交通管理系统和用户智能设备的通讯载体，创建了根据优化角度、球面距离算法，判定行车方向、所属路段、速度；根据交通信号灯的周期规律，计算推荐用户最佳行车速度，以获得最大概率不停车在绿灯时通过前方路口，并将行车方案语音播报给用户，避免车辆在到达路口之前抢绿灯高速行驶造成安全隐患。再比如，申请号201910614671.X《一种机器学习的智能交通状态预测方法》文件中公开了一种机器学习的智能交通状态预测方法。该方法根据收集到的路网数据集、交通流量-速度数据集、气象数据集和社会属性数据集，建立一个基于LSTM的Encoder-Decoder混合模型，通过对该混合模型的训练实现交通状态的智能实时预测。该方法特别强调了时间与空间效应，增加了气象属性、路网属性、社会属性，能够提 升道路交通速度预测的准确度。
以上综述的技术方案对改善交通安全现状起到了积极的作用，自动驾驶技术的推广和辅助电子设备的使用，减少了很多人为因素的事故。但是有很多交通事故本来是可以避免的，但是还是发生了，不如对于“鬼探头”这样的事件，无论自动驾驶还是技术高超的驾驶员都是难以处置。
视线阻挡和探测器盲区是造成的交通事故重要原因，从根本上说还是由于个体不遵守交通规则造成。
发明内容
针对现有的无论是车辆还是行人在道路行驶或行走存在的上述问题，现提供一种旨在实现实时根据道路上的行驶的车辆和行人判断其是否存在交通风险的基于车辆行驶的危险预警方法、系统及存储介质。
具体技术方案如下：
一种基于车辆行驶的危险预警方法，其中，包括以下步骤：
实时获取每个所述终端设备的移动状态信息，其中，所述终端设备表示与行驶车辆或行人关联的终端设备；
根据每个所述终端设备在所述道路地图中的实时位置，以及结合所述终端设备的所述移动状态信息，预测存在交通风险的所述终端设备。
优选的，获取所述终端终端设备的所述移动状态信息包括：
采用多天线侦测系统侦测所述终端设备的坐标、方向以及速度。
优选的，预测存在交通风险的方法，具体包括以下步骤：
根据所述终端设备的移动状态信息，在由单位面积构成的道路网格区域中预测每个终端设备的下一网格位置；
判断所述网格区域中是否存在网格位置在同一时刻被占据的情形，如存在，则表示同时进入当前的所述网格位置的所述终端设备所关联的车辆或者行人存在发生碰撞的风险。
优选的，在判断存在交通风险后，包括以下步骤：
生成一条碰撞提示信息并将所述碰撞提示信息发送至对应的终端设备；或者
当所述终端设备为车辆的车控系统时，生成对应的控制指令并发送至所述车控系统，所述车控系统根据所述控制指令控制当前的车辆进行避让。
还包括一种基于车辆行驶的危险预警系统，其中，包括：
多天线信号侦测模块，用以实时获取道路上每个终端设备的无线信号；其中，所述终端设备表示与车辆或行人关联的终端设备；以及
用以根据所述终端设备的无线信号处理得到所述终端设备的移动状态信息；
风险感知模块，用以根据每个所述终端设备在道路地图中的实时位置，以及结合所述终端设备的所述移动状态信息，预测存在交通风险的所述终端设备。
优选的，所述多天线信号侦测模块主要由有源零中频天线和软件基带构成。
优选的，所述风险感知模块包括：
位置预测单元，用以根据所述终端设备的移动状态信息，在由单位面积构成的道路网格区域中预测每个终端设备的下一网格位置；
判断单元，用以判断所述网格区域中是否存在网格位置在同一时刻被占据的情形，如存在，则表示同时进入当前的所述网格位置的所述终端设备所关联的车辆或者行人存在发生碰撞的风险。
优选的，还包括风险评估模块：
所述风险评估模块用以在所述风险感知模块感知到存在交通风险时，生成一碰撞提示信息并将所述碰撞提示信息发送至对应的终端设备；或者
当所述终端设备为车辆的车控系统时，生成对应的控制指令并发送至所述车控系统，所述车控系统根据所述控制指令控制当前的车辆进行避让。
还包括一种存储介质，其中，执行以下软件，该软件用以执行上述的危险预警方法。
上述技术方案的有益效果是：通过上述的危险预警方法和系统，可以实时对道路上参与交通的行人和车辆进行实时监控，可通过收集道路上行人或者车辆关联的终端设备的移动状态信息，及时的预测出存在交通的风险的行人和车辆，从而克服了现有技术中的车辆通过探测器探测风险时由于突发情 况如行人闯入或者探测盲区的存在导致无法及时预测风险的问题。
另一方面可帮助驾驶人员视觉阻挡和其他不可预知的情况下即使发现风险并采取有效措施。
附图说明
图1为本发明的一种基于车辆行驶的危险预警方法的实施例的流程示意图；
图2为本发明的一种基于车辆行驶的危险预警方法的实施例中，关于预测存在交通风险的方法的流程示意图；
图3为本发明的一种基于车辆行驶的危险预警方法的另一实施例中的流程示意图；
图4为本发明的一种基于车辆行驶的危险预警方法的另一实施例中的流程示意图；
图5为本发明的一种基于车辆行驶的危险预警方法的另一实施例中的流程示意图；
图6为本发明的一种基于车辆行驶的危险预警系统的实施例的结构示意图；
图7为本发明的一种基于车辆行驶的危险预警系统的实施例中，位置预测单元预测路线的流程示意图；
图8为本发明的一种基于车辆行驶的危险预警系统的实施例中，多天线感知模块处理的流程示意图；
图9为本发明的一种基于车辆行驶的危险预警系统的实施例中，关于有基带信号前端多天线结构的示意图；
图10为本发明的一种基于车辆行驶的危险预警系统的实施例中，关于零中频天线结构的示意图。
上述附图标记表示：
1、多天线信号侦测模块；2、风险感知模块；3、风险评估模块；
21、位置预测单元；22、判断单元。
具体实施方式
下面结合附图和具体实施例对本发明作进一步说明，但不作为本发明的限定。
需要说明的是，在不冲突的前提下，以下描述的实施例以及实施例中的技术特征可以相互组合。
本发明的技术方案中提供一种基于车辆行驶的危险预警方法。
如图1，一种基于车辆行驶的危险预警方法的实施例，其中，包括以下步骤：
实时获取每个终端设备的移动状态信息，其中，终端设备表示与行驶车辆或行人关联的终端设备；
根据每个终端设备在道路地图中的实时位置，以及结合终端设备的移动状态信息，预测存在交通风险的终端设备。
上述技术方案中，道路地图中主要由单位面积构成的道路网格区域，根据接收的移动状态信息具体可包括终端设备的识别码和实时坐标、方向、速度参数等。
通过获取的终端设备的用户识别码，识别该终端设备持有者的风险系数，加权预测该终端设备的运动时刻表，读取实时地图网格的使用时序和交通信号时序，判断该终端设备是否符合交通规则，从而及时预测出不符合交通规则的终端设备。
具体而言，在道路的电子地图中，将路面规划成单位面积的网格，并为每个网格设定使用时序和使用状态，通过接收终端设备发射的上行信号，通过上行信号处理获得每个终端设备的移动状态信息如速度、方向、坐标以及终端设备的用户识别码，根据上述的终端设备信息，预测每个终端设备所关联的行人或者车辆的路线时刻表，以预定网格占用时刻和时间，如果网格占用时刻和时间发生冲突，则存在交通风险。
在一种较优的实施方式中，获取终端终端设备的移动状态信息包括：
采用多天线侦测系统侦测终端设备的坐标、方向以及速度以及用户识别 码。为了保证覆盖整个路面上的所有终端设备的用户，其采用相控阵雷达波达时间(TOA)侧向定位方法。
在一种较优的实施方式中，如图2所示，预测存在交通风险的方法，具体包括以下步骤：
根据终端设备的移动状态信息，在由单位面积构成的道路网格区域中预测每个终端设备的下一网格位置；
判断网格区域中是否存在网格位置在同一时刻被占据的情形，如存在，则表示同时进入当前的网格位置的终端设备所关联的车辆或者行人存在交通风险。
上述技术方案，根据网格占用时刻和时间发生冲突的不同程度，从而确定交通风险系数，风险系数越高交通隐患越大。
在另一实施例中，如图3所示，
步骤S11、在以单位面积构成的网格中，每一个网格均设定有使用时序以及可用状态；
步骤S12、接收终端设备的上行信号，以获取每个终端设备的移动状态信息；
步骤S13、根据终端设备的状态信息预测终端设备的预测每个终端设备的下一网格位置；
步骤S14、判断网格区域中是否存在网格位置在同一时刻被占据的情形；
若是，执行步骤S15；
若否，返回步骤S11、继续预测终端设备的轨迹和方向，并将每个终端设备所关联的行人或者车辆的路线时刻表上报；
步骤S15、表示同时进入当前的网格位置的终端设备所关联的车辆或者行人存在交通风险，进入风险评估过程，其中在进入风险评估过程中，计算终端设备突发变道和不规矩形成风险系数；将行车风险保存于数据库中。
在一种较优的实施方式中，在判断存在交通风险后，包括以下步骤：
生成一条碰撞提示信息并将碰撞提示信息发送至对应的终端设备；
或者；当终端设备为车辆的车控系统时，生成对应的控制指令并发送至车控系统，车控系统根据控制指令控制当前的车辆进行避让。
上述技术方案中，可根据交通风险系数是否超过一阈值来确定，是否向终端设备发送提示信息，或者向终端设备发送控制指令；
也可不根据阈值，当判断存在交通风险时，向终端设备发送提示信息，或者向终端设备发送控制指令；
通过上述方法，可有效的解决视觉盲区和视线阻挡的问题。进一步，对于具有不良驾驶行为的终端设备，系统提示规划足够的安全区间，给守法终端设备充分的反应时间区间，减少驾驶风险，其实时预测终端设备的行驶状态的过程如图4所示：
步骤A1、在以单位面积构成的网格中，接受终端设备发送的路线时刻表，规划终端设备的前进路线；
步骤A2、在终端设备列表中，维护每个网格的时序和使用状态；
步骤A3、根据终端设备的运动状态信息，预测网格的使用时序和使用状态。
本发明的技术方案中还包括种基于车辆行驶的危险预警系统。
如图5所示，一种基于车辆行驶的危险预警系统的实施例，其中，包括：
多天线信号侦测模块，用以实时获取道路上每个终端设备的无线信号；其中，终端设备表示与车辆或行人关联的终端设备；以及
用以根据终端设备的无线信号处理得到终端设备的移动状态信息；
风险感知模块，用以根据每个终端设备在道路地图中的实时位置，以及结合终端设备的移动状态信息，预测存在交通风险的终端设备。
上述技术方案中，多天线信号侦测模块还包括多天线感知计算模块，用以根据终端设备的无线信号处理得到终端设备的移动状态信息；
其中，多天线感知模块处理流程如下，图8所示：
通过路面部署的有源多天线系统；
多天线信号侦测模块接收终端设备的上行信号；
有源多天线系统根据用户识别码区别终端设备并且对应计算终端设备的三维坐标、移动方向和坐标；
将终端设备的坐标、速度、方向等参数发送至风险感知模块。
需要说明的是，终端设备可包括已经安装本适配本技术方案的终端设备 数据接口的自动驾驶汽车、普通智能手机、专用设备，和没有适配本技术方案的终端设备数据接口所有智能或者非智能手机。
为了保证覆盖整个路面上的所有终端设备的用户，其采用相控阵雷达波达时间(TOA)侧向定位方法。具体而言是在道路上布置雷达天线，相控阵雷达天线的布置的距离一般在一个范围以内，距离相对固定，可通过设置延迟参数可以解决传播路径造成的延迟问题。
同时为了克服信号馈线长度不一致造成传输时间延迟不确定的问题，本技术方案中，公开了多天线信号侦测系统两种结构模式，有基带信号前端部署模式和无基带信号前端部署模式。
其中，有基带信号前端多天线结构，远端天线与基带部署在一个硬件上构成一个独立的接收机系统，结构如图9所示。该有基带信号前端在一个完整的零中频接收机基础上增加了时钟同步模块用于同步多个有基带信号前端的时钟；增加了数据传输模块用于传输基带输出的解调解码后的数字信号到多天线感知计算模块；增加了独立发射天线模块用于向终端设备发射预警信号和提示信息，该接收机的基带实现对接收信号的解调和解码，解码之后的数据和精确时间标记报给多天线感知计算模块，由多天线感知计算模块实现对终端设备识别、计算终端设备的位置坐标、速度和移动方向，并由多天线感知计算模块，将终端设备的坐标、速度、方向等参数报给风险感知模块。
另一种，无基带信号前端多天线结构，射频前端与基带分离，多个无基带信号前端共用一个软件基带。该无基带信号前端将有基带信号前端基带部署到后端，天线接收到信号完成AD转换以后的数据由数据传输模块打包传输到后端软件基带，多个无基带信号前端的数据汇聚到软件基带处理模块，由远端软件基带对已经数字化的信号进行解调和解码，进一步由多天线感知计算模块实现对终端设备识别、计算终端设备的位置坐标、速度和移动方向，并由多天线感知计算模块，将终端设备的坐标、速度、方向等参数报给风险感知模块。在一种较优的实施方式中，多天线信号侦测模块主要由有源零中频天线和软件基带构成。
其中，如图10所示，零中频天线包括接收天线、前置滤波器、低噪放大器、混频器、低通滤波器、可编程放大器、AD转换器构成、数据传输模块、 时钟同步模块和独立发射天线，软件基带模块可以部署在前端形成有基带信号前端或者部署在后端形成无基带信号前端。
具体而言，信号前端和多天线感知计算模块共同构成了多天线信号侦测，实现侦测和接收终端设备的上行信号功能。
在一种较优的实施方式中，如图6所示，风险感知模块包括：
位置预测单元，用以根据终端设备的移动状态信息，在由单位面积构成的道路网格区域中预测每个终端设备的下一网格位置；
判断单元，用以判断网格区域中是否存在网格位置在同一时刻被占据的情形，如存在，则表示同时进入当前的网格位置的终端设备所关联的车辆或者行人存在发生碰撞的风险。
上述技术方案中，该系统还包括存储模块(未于图中示出)，该存储模块中存储有每个终端设备出现违章的记录，对于经常违章的终端设备进行重点监控，如果检测到终端设备存在不合规矩行为即进入风险评估过程；
具体的风险感知模块预测的交通风险还包括：
接收多天线信号侦测模块发出的终端设备的坐标、速度、方向等参数；
读取终端设备风险加权系数R，加权计算该终端设备关联的用户的路线时刻表；
读取实时地图中网格使用时序和交通信号时序；
判断两者是否存在冲突；
若是，进入风险评估流程；
若否，终端设备继续上报路线时刻表。
上述的位置预测单元的具体预测流程如下图7所示：
步骤B1、判断终端设备是否已经有规划路线；
若否，根据终端设备的车道判定行进方向，根据速度向道路地图上报时刻表，并转向步骤B4；
若是，执行步骤B2；
步骤B2、判断当前的已规划路线是否需要重新规划路线；
步骤B3、重新规划路线；
步骤B4、根据实时上报的路线时刻表，以登记网格的使用时序。在一种 较优的实施方式中，还包括风险评估模块：
风险评估模块用以在风险感知模块感知到存在碰撞风险时，生成一条碰撞提示信息并将碰撞提示信息发送至对应的终端设备；或者
当终端设备为车辆的车控系统时，生成对应的控制指令并发送至车控系统，车控系统根据控制指令控制当前的车辆进行避让。
上述技术方案中，风险评估模块的作用是评估风险制造者的可能轨迹会影响到哪几个终端设备。向受影响的终端设备发出警示信息即(碰撞提示信息)，或者向自动驾驶系统即(车控系统)发出控制指令，受影响的终端设备包括直接影响和间接影响。
其中需要说明的是，为了有效的规避风险本技术方案中公开一种自动驾驶交互协议，兼容该协议的终端设备可以收到本系统通过计算机模拟出来的最佳参数。
其协议结构如下：
UID：18位字符；
RL：1-10级；//定义风险级别
AO：2字符；//动作指令
AD：1字符；//动作方向
SN：4字符：//实时速度
Di：1字符；//实时方向
SD：128字符；//密文shadow。
还包括一种存储介质，其中，执行以下软件，该软件用以执行上述的危险预警方法。
上述技术方案中，实现上述方法实施例的全部或部分步骤可以通过程序指令相关的硬件未完成，前述的程序可以存储于计算机可读取存储介质中，该程序在执行时，执行包括上述方法实施例的步骤：而前述的存储介质包括：ROM、RAM、磁碟或者光盘等各种可以存储程序代码的介质。
以上所述仅为本发明较佳的实施例，并非因此限制本发明的实施方式及保护范围，对于本领域技术人员而言，应当能够意识到凡运用本发明说明书 及图示内容所作出的等同替换和显而易见的变化所得到的方案，均应当包含在本发明的保护范围内。

Claims (9)

  1. 一种基于车辆行驶的危险预警方法，其特征在于，包括以下步骤：
    实时获取每个所述终端设备的移动状态信息，其中，所述终端设备表示与行驶车辆或行人关联的终端设备；
    根据每个所述终端设备在所述道路地图中的实时位置，以及结合所述终端设备的所述移动状态信息，预测存在交通风险的所述终端设备。
  2. 根据权利要求1所述的危险预警方法，其特征在于，获取所述终端设备的所述移动状态信息包括：
    采用多天线侦测系统侦测所述终端设备的坐标、方向以及速度。
  3. 根据权利要求1所述的危险预警方法，其特征在于，预测存在交通风险的所述终端设备的方法，具体包括以下步骤：
    根据所述终端设备的移动状态信息，在由单位面积构成的道路网格区域中预测每个终端设备的下一网格位置；
    判断所述网格区域中是否存在网格位置在同一时刻被占据的情形，如存在，则表示同时进入当前的所述网格位置的所述终端设备所关联的车辆或者行人存在交通风险。
  4. 根据权利要求3所述的危险预警方法，其特征在于，在存在交通风险后，包括以下步骤：
    生成一条碰撞提示信息并将所述碰撞提示信息发送至对应的终端设备；或者
    当所述终端设备为车辆的车控系统时，生成对应的控制指令并发送至所述车控系统，所述车控系统根据所述控制指令控制当前的车辆进行避让。
  5. 一种基于车辆行驶的危险预警系统，其特征在于，包括：
    多天线信号侦测模块，用以实时获取道路上每个终端设备的无线信号；其中，所述终端设备表示与车辆或行人关联的终端设备；以及
    用以根据所述终端设备的无线信号处理得到所述终端设备的移动状态信息；
    风险感知模块，用以根据每个所述终端设备在道路地图中的实时位置，以及结合所述终端设备的所述移动状态信息，预测存在交通风险的所述终端 设备。
  6. 根据权利要求5所述的危险预警系统，其特征在于，所述多天线信号侦测模块主要由有源零中频天线和软件基带构成。
  7. 根据权利要求5所述的危险预警系统，其特征在于，所述风险感知模块包括：
    位置预测单元，用以根据所述终端设备的移动状态信息，在由单位面积构成的道路网格区域中预测每个终端设备的下一网格位置；
    判断单元，用以判断所述网格区域中是否存在网格位置在同一时刻被占据的情形，如存在，则表示同时进入当前的所述网格位置的所述终端设备所关联的车辆或者行人存在交通风险。
  8. 根据权利要求7所述的危险预警系统，其特征在于，还包括风险评估模块：
    所述风险评估模块用以在所述风险感知模块感知到存在交通风险时，生成一条碰撞提示信息并将所述碰撞提示信息发送至对应的终端设备；或者
    当所述终端设备为车辆的车控系统时，生成对应的控制指令并发送至所述车控系统，所述车控系统根据所述控制指令控制当前的车辆进行避让。
  9. 一种存储介质，其特征在于，执行以下软件，该软件用以执行权利要求1-4中任一所述的危险预警方法。
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Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113702963A (zh) * 2021-09-24 2021-11-26 河南交投通汇高速公路有限责任公司 基于视觉和微波探测的道路预警方法、装置及电子设备
CN114153203A (zh) * 2021-11-08 2022-03-08 北京三快在线科技有限公司 一种无人设备控制方法、装置、设备及存储介质
CN114475502A (zh) * 2022-03-24 2022-05-13 中国第一汽车股份有限公司 一种乘车人员下车安全保护方法及保护装置
CN114821968A (zh) * 2022-05-09 2022-07-29 西南交通大学 动车司机疲劳驾驶干预方法、装置、设备及可读存储介质
CN115223367A (zh) * 2022-07-28 2022-10-21 福建工程学院 一种基于物联网的道路横风预警系统
CN117576880A (zh) * 2024-01-19 2024-02-20 广州瑞港消防设备有限公司 应用于蓄电池包监控的火灾预警系统

Families Citing this family (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112466158B (zh) * 2020-11-26 2022-04-29 东南大学 一种面向平面交叉口的车辆碰撞风险评估及预测方法
JP7203908B1 (ja) * 2021-06-22 2023-01-13 本田技研工業株式会社 制御装置、移動体、制御方法、及びプログラム
CN113822487A (zh) * 2021-09-29 2021-12-21 一汽出行科技有限公司 运营车辆的风险预警方法、装置、存储介质及计算机设备

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104346955A (zh) * 2014-10-16 2015-02-11 浙江吉利汽车研究院有限公司 基于人车通信的行人避撞方法和避撞系统
CN105427669A (zh) * 2015-12-04 2016-03-23 重庆邮电大学 一种基于dsrc车车通信技术的防撞预警方法
CN106828388A (zh) * 2016-12-30 2017-06-13 浙江吉利控股集团有限公司 针对行人的车辆主动报警系统及方法和车辆
CN108898795A (zh) * 2018-06-12 2018-11-27 广州小鹏汽车科技有限公司 一种基于移动设备的行人状态实时分析方法及系统
CN110419070A (zh) * 2017-02-08 2019-11-05 住友电气工业株式会社 信息提供系统、服务器、移动终端和计算机程序
CN111179624A (zh) * 2018-11-13 2020-05-19 奥迪股份公司 碰撞预警方法、装置、计算机设备和存储介质

Family Cites Families (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103778783B (zh) * 2013-12-04 2015-12-30 北京航空航天大学 基于专用短程通信的十字路口非机动车和行人位置检测方法
CN105321362B (zh) * 2015-10-30 2017-10-13 湖南大学 一种交叉口车辆智能协同通行方法
CN106846818B (zh) * 2017-04-24 2019-12-10 河南省城乡规划设计研究总院有限公司 基于Simulink仿真的路网动态交通流预测方法
CN107731009A (zh) * 2017-11-28 2018-02-23 吉林大学 一种适用于无信号灯交叉路口车辆避人、避撞系统及方法
CN110310481A (zh) * 2019-06-28 2019-10-08 浙江吉利控股集团有限公司 一种车辆碰撞预警方法、装置及设备
CN110544377A (zh) * 2019-08-31 2019-12-06 武汉理工大学 基于车路协同的交叉口行人避撞方法

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104346955A (zh) * 2014-10-16 2015-02-11 浙江吉利汽车研究院有限公司 基于人车通信的行人避撞方法和避撞系统
CN105427669A (zh) * 2015-12-04 2016-03-23 重庆邮电大学 一种基于dsrc车车通信技术的防撞预警方法
CN106828388A (zh) * 2016-12-30 2017-06-13 浙江吉利控股集团有限公司 针对行人的车辆主动报警系统及方法和车辆
CN110419070A (zh) * 2017-02-08 2019-11-05 住友电气工业株式会社 信息提供系统、服务器、移动终端和计算机程序
CN108898795A (zh) * 2018-06-12 2018-11-27 广州小鹏汽车科技有限公司 一种基于移动设备的行人状态实时分析方法及系统
CN111179624A (zh) * 2018-11-13 2020-05-19 奥迪股份公司 碰撞预警方法、装置、计算机设备和存储介质

Cited By (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113702963A (zh) * 2021-09-24 2021-11-26 河南交投通汇高速公路有限责任公司 基于视觉和微波探测的道路预警方法、装置及电子设备
CN114153203A (zh) * 2021-11-08 2022-03-08 北京三快在线科技有限公司 一种无人设备控制方法、装置、设备及存储介质
CN114475502A (zh) * 2022-03-24 2022-05-13 中国第一汽车股份有限公司 一种乘车人员下车安全保护方法及保护装置
CN114821968A (zh) * 2022-05-09 2022-07-29 西南交通大学 动车司机疲劳驾驶干预方法、装置、设备及可读存储介质
CN114821968B (zh) * 2022-05-09 2022-09-13 西南交通大学 动车司机疲劳驾驶干预方法、装置、设备及可读存储介质
CN115223367A (zh) * 2022-07-28 2022-10-21 福建工程学院 一种基于物联网的道路横风预警系统
CN115223367B (zh) * 2022-07-28 2023-11-03 福建工程学院 一种基于物联网的道路横风预警系统
CN117576880A (zh) * 2024-01-19 2024-02-20 广州瑞港消防设备有限公司 应用于蓄电池包监控的火灾预警系统

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