WO2022063331A1 - 一种基于v2x的编队行驶智能网联客车 - Google Patents

一种基于v2x的编队行驶智能网联客车 Download PDF

Info

Publication number
WO2022063331A1
WO2022063331A1 PCT/CN2021/127695 CN2021127695W WO2022063331A1 WO 2022063331 A1 WO2022063331 A1 WO 2022063331A1 CN 2021127695 W CN2021127695 W CN 2021127695W WO 2022063331 A1 WO2022063331 A1 WO 2022063331A1
Authority
WO
WIPO (PCT)
Prior art keywords
formation
vehicle
information
bus
domain controller
Prior art date
Application number
PCT/CN2021/127695
Other languages
English (en)
French (fr)
Inventor
陈笃廉
李春
王尔烈
聂石启
司炎鑫
陆小霏
谭福伦
王俊红
Original Assignee
金龙联合汽车工业（苏州）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.)
Filing date
Publication date
Application filed by 金龙联合汽车工业（苏州）有限公司 filed Critical 金龙联合汽车工业（苏州）有限公司
Publication of WO2022063331A1 publication Critical patent/WO2022063331A1/zh

Links

Images

Classifications

    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/02—Control of position or course in two dimensions
    • G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0287—Control of position or course in two dimensions specially adapted to land vehicles involving a plurality of land vehicles, e.g. fleet or convoy travelling
    • G05D1/0291—Fleet control
    • G05D1/0295—Fleet control by at least one leading vehicle of the fleet
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60R—VEHICLES, VEHICLE FITTINGS, OR VEHICLE PARTS, NOT OTHERWISE PROVIDED FOR
    • B60R16/00—Electric or fluid circuits specially adapted for vehicles and not otherwise provided for; Arrangement of elements of electric or fluid circuits specially adapted for vehicles and not otherwise provided for
    • B60R16/02—Electric or fluid circuits specially adapted for vehicles and not otherwise provided for; Arrangement of elements of electric or fluid circuits specially adapted for vehicles and not otherwise provided for electric constitutive elements
    • B60R16/023—Electric or fluid circuits specially adapted for vehicles and not otherwise provided for; Arrangement of elements of electric or fluid circuits specially adapted for vehicles and not otherwise provided for electric constitutive elements for transmission of signals between vehicle parts or subsystems
    • B60R16/0231—Circuits relating to the driving or the functioning of the vehicle

Definitions

  • the invention belongs to the technical field of intelligent network-connected automatic driving vehicles, and in particular relates to an intelligent network-connected passenger vehicle based on V2X for platooning.
  • the intelligent network-connected bus uses technologies such as intelligent control, V2X (Vehicle to Everything) information interconnection, machine vision, navigation and positioning, and information fusion to realize autonomous vehicle control and formation driving, and to ensure its driving maneuverability and safety without driving. operator control.
  • intelligent and connected buses will fundamentally change the control methods of traditional buses and the travel modes of urban and rural residents, which can greatly improve the safety and traffic efficiency of modern transportation systems, reduce environmental pollution, and provide other information services.
  • the Chinese invention patent application with application number: 201910123370.7 discloses a V2X-based autonomous driving vehicle, method and device, using multiple sensors and multiple radars to identify lane lines and obstacles, combined with V2X to identify vehicles ahead, using GPS positioning, through The control module generates a driving path.
  • the Chinese invention patent application with the application number: 201710083950.9 discloses a method for intelligent vehicle formation driving. The leader obtains the own vehicle information and sends it to the follower, and the vehicle analyzes the financial planning path of the leader and completes the follow-up control of the leader. Keep a certain relative distance and speed between the leader and the follower.
  • Application number: 201710184207.2 The Chinese invention patent application discloses a fleet formation driving system and method.
  • the first car is manually driven, and at least one slave car can follow the first car to drive automatically, so as to reduce the driver error rate and labor intensity.
  • Application number: US15989805 US invention patent application discloses an automatic driving system, which can formulate an appropriate planning route according to the current state of the car, and avoid improper driving of the car in abnormal conditions such as rain and snow by presetting the control target value of the car route planning.
  • the existing intelligent networked vehicles are mostly aimed at passenger cars or trucks, and most of them are only aimed at a single vehicle, or the fixed head vehicle/main vehicle adopts manual or automatic driving mode, and does not realize the formation driving coordination of multi-passenger vehicles control; most of the existing ICVs can only track pre-calibrated routes and cannot cope with complex traffic scenarios; the existing ICVs are difficult to achieve autonomous driving in the absence of high-precision maps and roadside units; It is still difficult for intelligent and connected buses to drive in a fully autonomous formation under complex road conditions in real cities.
  • the purpose of the present invention is to provide a V2X-based intelligent network-connected bus for platooning, which realizes the coordinated control of platooning of multiple buses. Stability, security and reliability.
  • a V2X-based intelligent network-connected bus for platooning comprising a perception and positioning device connected to an intelligent network-connected automatic driving domain controller and a V2X information interconnection system, the intelligent network-connected bus is equipped with an on-board unit, and the intelligent network-connected automatic driving The domain controller is also connected to the intelligent networking chassis domain controller;
  • the intelligent network-connected autonomous driving domain controller is used to process the multi-source information collected by the sensing and positioning device through data processing of the coupling algorithm, output the status information of the intelligent network-connected bus in real time, and construct a route tracking map.
  • the driving process it locates its own position and attitude according to the vehicle itself, the information around the vehicle and the map information, realizes automatic driving and navigation, performs algorithm fusion according to the current state data of all formation vehicles, plans the driving path, and decides the formation driving state. output the target speed and target acceleration of path tracking to the intelligent networked chassis domain controller;
  • the sensing and positioning device includes an environment sensing unit and a positioning and navigation unit.
  • the environment sensing unit is used to collect the posture of the intelligent networked bus and the surrounding environment information of the intelligent connected bus.
  • the positioning and navigation unit obtains intelligent information in real time. The location, speed and direction of the connected bus;
  • the V2X information interconnection system is used to obtain real-time vehicle information, road information, and pedestrian information, including WIFI whip antenna, CAN bus, and Ethernet cable.
  • the vehicle-mounted unit and the vehicle end conduct data through CAN bus and Ethernet cable.
  • Communication, the on-board unit broadcasts the status information of the intelligent network-connected bus to other formation vehicles through the CAN data channel transparent transmission method, and each formation vehicle receives the broadcast data through the Ethernet channel;
  • the intelligent network-connected chassis domain controller is used for the path tracking control of the network-connected bus, including speed control and direction control.
  • the speed control drives the electronic accelerator through the CAN bus for acceleration control, and the motor brake and service brake are used for acceleration control. Deceleration control, the direction control is carried out by driving the motor through the CAN bus, and the chassis domain controller sends straight, left or right turns to the steering motor controller through the CAN bus according to the position information, heading information and steering information of the passenger car. command request.
  • the speed control method of the intelligent network-connected chassis domain controller includes: according to the deviation between the actual vehicle speed and the expected vehicle speed, calculating the expected acceleration through the vehicle speed control law, and controlling the The vehicle travels at the desired speed.
  • the environment perception unit includes 1 lidar, 4 mid-range angle millimeter-wave radars, 5 vehicle-mounted cameras and multiple ultrasonic radars.
  • the controller communicates with the millimeter-wave radar, and the millimeter-wave radar uses a high-speed CAN bus to communicate with the intelligent network-connected automatic driving domain controller.
  • the vehicle camera and the ultrasonic radar use a low-speed CAN bus to communicate with the intelligent network-connected automatic driving domain controller.
  • the intelligent networked chassis domain controller includes an input conditioning circuit, an output conditioning circuit, a processor, a power supply module and a communication module, and the power supply module performs voltage regulation and voltage division processing on the DC power provided by the vehicle DC power supply , supply power to the processor and each conditioning circuit.
  • the input conditioning circuit includes a multi-channel analog signal processing circuit, a digital signal processing circuit and a switching signal processing circuit.
  • the analog signal processing circuit is used for optoelectronic isolation circuits, RC filtering and amplification steering.
  • the output conditioning circuit includes a multi-channel frequency drive circuit, a switch drive circuit and a digital drive circuit.
  • the frequency drive circuit drives the service brake solenoid valve after signal amplification and photoelectric isolation.
  • the switch drive circuit After signal amplification and photoelectric isolation processing, the handbrake switch, turn signal and door switch are driven.
  • the digital drive circuit drives the gear position after signal amplification and photoelectric isolation processing. Drive control commands for dynamic and electronic accelerators.
  • the intelligent network-connected autonomous driving domain controller to decide the formation driving state includes establishing a non-linear control model of vehicle distance control according to the current vehicle speed range, and judging and adjusting the current main vehicle according to the current formation state, or whether there is a current slave vehicle.
  • a vehicle applies to become the main vehicle, it will be based on the current formation topology, formation path, distance between ICVs in the formation, formation speed and target formation topology, formation path, distance between ICVs in the formation, Based on the speed of the formation and the actual state of each vehicle in the formation, a new main vehicle is generated according to the set election algorithm.
  • the WIFI whip antenna in the V2X information interconnection system is connected to the vehicle-mounted unit, and the WIFI whip antenna broadcasts the identity sign, vehicle speed, acceleration, steering angle, heading angle and latitude and longitude positioning information of the vehicle.
  • the WIFI whip antenna receives the broadcast information of other passenger cars in the formation, the broadcast information includes the identity sign, vehicle speed, acceleration, steering angle, heading angle and latitude and longitude positioning information, and the WIFI whip antenna inputs the received broadcast information
  • An on-board unit the on-board unit sends broadcast information to an intelligent network-connected autonomous driving domain controller through an Ethernet channel.
  • the present invention can realize the coordinated control of formation driving of multi-passenger vehicles, and can complete autonomous formation driving in real urban complex road conditions.
  • the chassis domain controller hardware adopts dual redundant design, which improves the stability, safety and reliability of formation driving. sex.
  • the formation system can re-elect the certified master vehicle according to the actual state of the current formation and the actual status of the current master and slave vehicles, so as to realize the formation driving without a fixed master vehicle and ensure the stability, safety and reliability of the formation driving.
  • Fig. 1 is the principle block diagram of the intelligent network-connected passenger car based on V2X of the present invention
  • FIG. 2 is a system architecture diagram of a V2X-based intelligent networked passenger vehicle for platooning of the present invention
  • Fig. 3 is the block diagram of the chassis domain controller of the intelligent network-connected bus of the present invention.
  • FIG. 4 is a flow chart of the formation driving control of passenger cars according to the present invention.
  • a V2X-based formation driving intelligent network-connected bus realizes V2X-based formation driving, with various autonomous formation driving modes. Using 5G communication technology, it can realize big data monitoring on the intelligent transportation cloud platform.
  • the intelligent network-connected bus integrates bus intelligent control, V2X information interconnection, environmental perception, planning and navigation, and human-computer interaction, and can recognize road signs, autonomous overtaking, autonomous avoidance, and automatic pull-over parking.
  • each intelligent networked bus is equipped with an on-board unit, and the intelligent networked automatic driving Domain controllers are also connected to intelligent networked chassis domain controllers.
  • the intelligent network bus has no pedals, steering wheel and cab, and the motion control of the bus is completed by the chassis domain controller.
  • the intelligent networked chassis domain controller is shown in Figure 3. It adopts a centralized electronic and electrical architecture and fully adopts SMD sensors, which effectively reduces the difficulty of software and hardware development and the difficulty and cost of sensor installation.
  • the structure is mainly composed of input conditioning circuits. , output conditioning circuit, processor, power supply module and communication module.
  • the chassis domain controller power module performs voltage regulation and voltage division processing on the DC power provided by the vehicle DC power supply, and supplies power to the processor and each conditioning circuit.
  • the input conditioning circuit of the chassis domain controller includes a multi-channel analog signal processing circuit, a multi-channel digital signal processing circuit and a multi-channel switch signal processing circuit.
  • RC filtering and amplifying analog voltage signals such as steering angle displacement, braking pressure, etc.
  • switching signal processing circuit is used for photoelectric isolation, RC filtering and level limiting handbrake, door, transmission gear and other switching voltage signals
  • digital signal processing circuit is used for Photoelectric isolation, RC filtering and amplifying digital signals such as wheel speed and vehicle speed.
  • the output conditioning circuit includes multiple frequency drive circuits, multiple switch drive circuits and multiple digital drive circuits.
  • the frequency drive circuit drives the service brake solenoid valve after signal amplification and photoelectric isolation, and the switch drive circuit passes signal amplification and photoelectric isolation.
  • the rear drive handbrake switch, turn signal, door switch, and the digital drive circuit drives the gear position through signal amplification and photoelectric isolation.
  • the chassis domain controller hardware adopts dual redundant design to improve system security.
  • the chassis domain controller obtains the vehicle's posture, state and target requirements through the vehicle CAN line network and various input conditioning circuits.
  • the processor performs comprehensive arithmetic processing on these real-time information and outputs control instructions.
  • the processor of the chassis domain controller realizes the drive control of the motor steering, motor braking, and electronic throttle through the vehicle CAN line network, so as to realize the precise control of the speed and direction of the intelligent connected bus.
  • After the control instructions of the processor of the chassis domain controller are processed by the signal amplification and photoelectric isolation of the output conditioning circuit, it drives the control of the corresponding service brake solenoid valve, handbrake switch, door switch, turn signal, brake light, gear position, etc. .
  • V2X mainly includes vehicle-to-vehicle V2V (Vehicle to Vehicle, such as collision avoidance, etc.), vehicle-to-person V2P (Vehicle to Pedestrian, such as safety warning, etc.), vehicle and traffic roadside infrastructure V2I (Vehicle to Infrastructure, such as traffic lights, etc.), Vehicle to network V2N (Vehicle to Network, such as providing real-time traffic flow reports, cloud services, etc.) is the information interconnection between vehicles and various physical terminals that may affect the vehicle, as shown in Figure 1.
  • V2V Vehicle to Vehicle to Vehicle, such as collision avoidance, etc.
  • vehicle-to-person V2P Vehicle to Pedestrian, such as safety warning, etc.
  • vehicle and traffic roadside infrastructure V2I Vehicle to Infrastructure, such as traffic lights, etc.
  • Vehicle to network V2N Vehicle to Network, such as providing real-time traffic flow reports, cloud services, etc.
  • V2X adopts LTE-V communication technology to provide real-time vehicle information, road information, pedestrian information and a series of traffic information for intelligent networked buses, as well as long-distance environmental signals, for the planning of the intelligent networked bus formation automatic driving system of the present invention , decision-making, control, etc. to provide information support and fault-tolerant redundancy.
  • LTE-V includes two communication interfaces, one is the short-distance direct communication interface PC5 such as V2V and V2I, and the other is the cellular communication interface Uu to realize V2N long-distance and wider-range reliable communication.
  • the V2X information interconnection is mainly completed through the onboard unit (OnBoardUnit, OBU) host, and also includes necessary auxiliary equipment such as WIFI whip antenna, CAN adapter cable, Ethernet cable, and 12V DC/DC power adapter.
  • OBU onboard unit
  • Each of the intelligent connected buses in the formation is equipped with an OBU.
  • Data communication between the OBU and the vehicle end is carried out through CAN lines and Ethernet lines.
  • the signs, vehicle speed and acceleration of the intelligent connected buses are transmitted.
  • steering angle, heading angle, longitude and latitude positioning and other data information are broadcast to other formation vehicles.
  • the current state data of all formation vehicles is algorithmically fused to reasonably plan the driving path and command vehicles.
  • the intelligent control system realizes the multi-vehicle formation driving function.
  • the data transmission and transparent transmission channels are smooth, the packet loss rate is low, and the accuracy rate is 100%.
  • the vehicle Before the vehicle enters the congested road section, it can know the traffic flow on the road ahead, so as to carry out reasonable path planning, avoid waiting or re-select the route, and improve the efficiency of traffic operation.
  • the perception and positioning set realizes the two functions of environment perception and positioning and navigation.
  • the surrounding environment of the connected bus, etc. provides a timely, accurate and reliable decision-making basis for the safe driving of the autonomous driving intelligent connected bus.
  • the intelligent networked bus adopts a design scheme of multi-sensor perception and information fusion, and takes into account information redundancy and safety.
  • the environment perception system of each intelligent network-connected bus driving in formation includes one laser radar, four medium-range angle millimeter-wave radars, five on-board cameras, and several ultrasonic radars.
  • the lidar uses Ethernet to communicate with the intelligent driving domain controller
  • the millimeter-wave radar uses a high-speed CAN line to communicate with the intelligent driving domain controller
  • the vehicle visual camera and ultrasonic radar use a low-speed CAN bus to communicate with the intelligent driving domain controller.
  • Positioning and navigation is used to provide information such as the position and direction of the vehicle.
  • the invention adopts the combined positioning and navigation based on GNSS+INS, and the system consists of an INS inertial gyro navigation unit, a dual-antenna RTK satellite navigation receiver and a 5G differential module.
  • the 5G differential module receives RTCM differential information such as location through the 5G network and sends it to the satellite navigation board.
  • the navigation computer receives the information of the 3-axis inertial gyroscope and the guard board card, and obtains the precise position, speed and direction of the system carrier, that is, the intelligent networked bus in real time.
  • the vehicle-mounted autonomous driving domain controller will perceive the multi-source information collected by the positioning set, and through the data processing of the coupling algorithm, it will output the accurate attitude, direction, position, speed, acceleration and other data of the carrier (i.e. the intelligent network bus) in real time, and provide the information It is safe and redundant, and at the same time builds a route tracking map.
  • the intelligent network bus can locate its own position and attitude according to the vehicle itself and the information around the vehicle and map information during the driving process, so as to realize automatic driving and navigation.
  • the intelligent network-connected bus also adopts a human-computer interaction system for the information exchange between the safety officer and the vehicle.
  • the safety officer can query and set vehicle parameters, issue control instructions, switch automatic driving modes, and use audio and video through voice control and touch-screen buttons. Entertainment system control and other functions.
  • each passenger car in the formation ( ⁇ 2 passenger cars) is equipped with an OBU.
  • Figure 4 shows the control of passenger cars when they drive in formation.
  • the control flow of formation driving is as follows:
  • Perceptual positioning set sensor obtains environmental perception information such as lanes and traffic
  • chassis domain controller obtains vehicle speed, acceleration, steering angle and other information
  • perception positioning set sensor and chassis domain controller transmit the acquired information to the autonomous driving domain controller ;
  • the automatic driving domain controller After the automatic driving domain controller processes the information, it transmits the information to the OBU by transparent transmission of the CAN data channel.
  • the whip antenna is connected to the OBU, and the whip antenna transmits the identity sign, speed, acceleration, steering angle of the vehicle , course angle and longitude and latitude positioning and other information broadcast;
  • the whip antenna receives the broadcast information of other passenger cars (other cars) in the formation, and the broadcast information also includes information such as identity signs, vehicle speed, acceleration, steering angle, heading angle, and latitude and longitude positioning;
  • the broadcast information received by the whip antenna is input to the OBU, and the OBU sends these broadcast information to the automatic driving domain controller through the Ethernet channel;
  • the autonomous driving domain controller fuses the chassis domain controller information, the perception positioning set information, and the information downloaded by the OBU to analyze the formation driving state, such as whether the formation topology, vehicle spacing, driving path, vehicle speed, etc. are reasonable, and then make a decision.
  • the optimal formation driving state of the ICVs including the formation topology without a fixed main vehicle, the formation path, the distance between ICVs in the formation, and the formation speed, etc.;
  • the automatic driving domain controller outputs the target speed and target acceleration of path tracking to the chassis domain controller according to the decision result of the optimal formation driving state
  • the chassis domain controller realizes the path tracking control of the connected bus, in which the speed control drives the electronic accelerator through the CAN bus for acceleration control, the motor brake and the service brake for deceleration control, and the direction control drives the motor through the CAN bus for direction control. control;
  • the chassis domain controller calculates the expected acceleration through the vehicle speed control law according to the deviation between the actual vehicle speed and the expected vehicle speed, and then realizes the smooth running of the vehicle according to the expected vehicle speed through the coordinated control of the electronic accelerator and motor braking;
  • the chassis domain controller sends travel command requests such as going straight, turning left or turning right to the steering motor controller through CAN according to the position information, heading information and steering information of the bus, so as to realize the precise route of the intelligent networked bus track.
  • the vehicle speed control law adopts the control strategy of feedforward and feedback to decide the expected acceleration of the intelligent connected bus, and the current master vehicle acceleration information is used as the forward speed.
  • the feed amount realizes the rapid response of the state, and the following error and speed difference are used as the feedback amount to reduce the control error.
  • the formation is based on the current speed (low speed, medium speed, high speed three). segment) to establish a non-linear control model of vehicle distance control, and consider the influence of actual communication delay.
  • the formation system will use the current formation topology, formation path, and intelligent network-connected buses in the formation according to the current formation topology. distance, formation speed and target formation topology, formation path, distance between intelligent networked buses in formation, formation speed and actual status of each vehicle in formation, and re-elects new main vehicles to achieve no fixed
  • the formation of the main vehicle ensures the stability, safety and reliability of the formation.
  • the automatic driving formation driving function of the intelligent network-connected bus specifically realized by the present invention includes:
  • the autopilot domain controller acts as the arbitration controller of the control mode, judges whether the conditions of autopilot and formation mode are met, and decides whether to enter the autopilot and formation mode;
  • 5G is applied in formation driving to realize network-connected V2X technology, V2X and sensor fusion technology, formation driving and intelligent dispatch coordination technology, formation driving control strategy, formation driving functional safety and information security technology, etc. Utilize the performance advantages of low latency, large bandwidth and high speed of 5G to ensure the safety, synchronization, smoothness and stability of vehicle formation driving;
  • the formation system can re-elect the certified master vehicle according to the actual state of the current formation and the actual status of the current master and slave vehicles, so as to realize the formation driving without a fixed master vehicle and ensure the stability, safety and reliability of the formation driving;
  • the formation fleet adopts the mechanism of no fixed main vehicle, and the vehicles in the formation can automatically change lanes, accelerate, and overtake each other.
  • the intelligent network-connected bus driving alone on the road merges into the main road, it can automatically join the running autonomous driving formation;
  • the vehicle can still accurately obtain the location, driving speed, acceleration and other information of surrounding vehicles, even at intersections with special road conditions (such as trees, tall buildings) Accurately obtain the traffic information around the vehicle in real time, especially when following the vehicle, the rear vehicle can pre-judgment and timely control the braking of the vehicle by acquiring the deceleration information involved in real time, so as to prevent the occurrence of rear-end collisions and improve braking. smoothness;

Landscapes

  • Engineering & Computer Science (AREA)
  • Automation & Control Theory (AREA)
  • Aviation & Aerospace Engineering (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Mechanical Engineering (AREA)
  • Control Of Driving Devices And Active Controlling Of Vehicle (AREA)
  • Traffic Control Systems (AREA)

Abstract

本发明公开了一种基于V2X的编队行驶智能网联客车，包括与自动驾驶域控制器连接的感知定位装置、V2X信息互联***和底盘域控制器；自动驾驶域控制器将采集的多源信息决策编队行驶状态，输出路径跟踪的目标速度和加速度；感知定位装置包括环境感知单元和定位导航单元；V2X信息互联***将客车状态信息广播给其它编队车辆；底盘域控制器用于网联客车的路径跟踪控制，通过CAN总线驱动电子油门进行加速控制，通过电机制动和行车制动进行减速控制，通过CAN总线向转向电机控制器发送直行、左转或右转的行进命令请求。可以实现多客车的编队行驶协同控制，底盘域控制器硬件采用双冗余设计，提高了编队行驶的稳定性、安全性和可靠性。

Description

一种基于V2X的编队行驶智能网联客车 技术领域
本发明属于智能网联自动驾驶汽车技术领域，具体地涉及一种基于V2X的编队行驶智能网联客车。
背景技术
随着5G技术、智能网联技术和智慧公路技术的飞速发展应用，汽车将成为智能交通***的一个端子，车与车、车与周围事物之间的数据通信与联系变得越来越紧密频繁。智能网联客车集中运用了智能控制、V2X(VehicletoEverything)信息互联、机器视觉、导航定位、信息融合等技术，实现了车辆自主控制和编队行驶，并能保证其驾驶操纵性与安全性且无需驾驶员操控。智能网联客车的出现将从根本上改变传统客车的控制方式以及城乡居民的出行方式，能够大幅提升现代交通***的安全性与通行效率、降低环境污染以及提供其它信息服务。
申请号：201910123370.7的中国发明专利申请公开了一种基于V2X的自动驾驶车辆、方法和装置，使用多个传感器和多个雷达识别车道线与障碍物，结合V2X识别前方车辆，采用GPS定位，通过控制模块生成行驶路径。申请号：201710083950.9的中国发明专利申请公开了一种智能车辆编队行驶方法，领车获取自车信息并发送给随车，随车解析领车的资助规划路径并完成对领车的跟随控制，同时领车和随车保持一定的相对距离和速度。申请号：201710184207.2中国发明专利申请公开了一种车队编队驾驶***及方法，首车通过人工驾驶，至少一辆从车都能跟随首车自动驾驶，以降低驾驶员失误率和劳动强度。申请号：US15989805的美国发明专利申请公开了一种自动驾驶***，能够根据汽车当前状态制定适当的规划路线，通过预设汽车的控制目标值来避免雨雪天气等非正常状态下汽车的不当行驶路线规划。
针对上述几种专利：现有智能网联汽车多针对乘用车或卡车，且大多只针对单一车辆，或固定头车/主车采用人工或自动驾驶模式，并未实现多客车的编队行驶协同控制；现有智能网联汽车大多只能跟踪事先标定的路线行驶，无法应对复杂交通场景；现有智能网联汽车在缺少高精地图和路侧单元的情况下难以实现自主驾驶；因此，现有智能网联客车还难以在真实城市复杂路况下的完全自主编队行驶。
发明内容
针对上述存在的技术问题，本发明的目的是提供一种基于V2X的编队行驶智能网联客 车，实现多客车的编队行驶协同控制，底盘域控制器硬件采用双冗余设计，提高了编队行驶的稳定性、安全性和可靠性。
本发明的技术方案是：
一种基于V2X的编队行驶智能网联客车，包括与智能网联自动驾驶域控制器连接的感知定位装置和V2X信息互联***，所述智能网联客车搭载车载单元，所述智能网联自动驾驶域控制器还连接智能网联底盘域控制器；
所述智能网联自动驾驶域控制器，用于将感知定位装置采集的多源信息，通过耦合算法数据处理，实时输出智能网联客车状态信息，构建路线跟踪地图，根据智能网联客车在自动驾驶过程中根据车辆自身、车辆周围信息和地图信息进行自身方位与姿态的定位，实现自动驾驶和导航，根据所有编队车辆的当前状态数据进行算法融合，规划行驶路径，决策编队行驶状态，根据决策的编队行驶状态向智能网联底盘域控制器输出路径跟踪的目标速度和目标加速度；
所述感知定位装置，包括环境感知单元和定位导航单元，所述环境感知单元，用于采集智能网联客车自身姿态及智能网联客车行驶的周围环境信息，所述定位导航单元，实时得到智能网联客车的位置、速度、方向；
所述V2X信息互联***，用于获取实时的车辆信息、道路信息、行人信息，包括WIFI鞭状天线、CAN总线、及以太网线，所述车载单元与整车端通过CAN总线、以太网线进行数据通讯，所述车载单元通过CAN数据通道透传方式将智能网联客车状态信息广播给其它编队车辆，各编队车辆通过以太网通道接收广播数据；
所述智能网联底盘域控制器，用于网联客车的路径跟踪控制，包括速度控制和方向控制，所述速度控制通过CAN总线驱动电子油门进行加速控制，通过电机制动和行车制动进行减速控制，所述方向控制通过CAN总线驱动电机进行方向控制，底盘域控制器根据客车的位置信息、航向信息和转向信息，通过CAN总线向转向电机控制器发送直行、左转或右转的行进命令请求。
优选的技术方案中，所述智能网联底盘域控制器的速度控制方法包括，根据实际车速与期望车速偏差，通过车速控制律计算出期望加速度，通过电子油门和电机制动的协同控制，控制车辆按照期望车速行驶。
优选的技术方案中，所述环境感知单元包括1个激光雷达、4个中距角毫米波雷达、5个车载摄像头及多个超声波雷达，所述激光雷达通过以太网与智能网联自动驾驶域控制器进行通讯，所述毫米波雷达采用高速CAN总线与智能网联自动驾驶域控制器进行通讯，所述 车载摄像头和超声波雷达采用低速CAN总线与智能网联自动驾驶域控制器进行通讯。
优选的技术方案中，所述智能网联底盘域控制器包括输入调理电路、输出调理电路、处理器、电源模块和通讯模块，所述电源模块将车载直流电源提供的直流电进行稳压分压处理，向处理器和各调理电路供电，所述输入调理电路包括多路模拟信号处理电路、数字信号处理电路和开关信号处理电路，所述模拟信号处理电路用于光电隔离电路、RC滤波及放大转向角位移、制动压力信号，所述开关信号处理电路用于光电隔离、RC滤波及电平限幅手刹、车门、变速器档位信号，所述数字信号处理电路用于光电隔离、RC滤波及放大轮速、车速，所述输出调理电路包括多路频率驱动电路、开关驱动电路和数字驱动电路，所述频率驱动电路通过信号放大、光电隔离处理后驱动行车制动电磁阀，所述开关驱动电路通过信号放大、光电隔离处理后驱动手刹开关、转向灯、车门开关，所述数字驱动电路通过信号放大、光电隔离处理后驱动档位；所述处理器通过车辆CAN总线发送对电机转向、电机制动、电子油门的驱动控制指令。
优选的技术方案中，所述智能网联自动驾驶域控制器决策编队行驶状态包括，根据当前车速大小区间建立车距控制非线性控制模型，根据当前编队状态判断调整当前主车，或有当前从车申请成为主车时，根据当前编队拓扑形态、编队路径、编队内智能网联客车之间的距离、编队行驶速度及目标编队拓扑形态、编队路径、编队内智能网联客车之间的距离、编队行驶速度及编队内各车实际状态，根据设定的选举算法产生新的主车。
优选的技术方案中，所述V2X信息互联***中WIFI鞭状天线与车载单元相连，所述WIFI鞭状天线将自车的身份标志、车速、加速度、转向角、航向角和经纬度定位信息广播出去；所述WIFI鞭状天线接收编队内其它客车的广播信息，所述广播信息包含身份标志、车速、加速度、转向角、航向角和经纬度定位信息，所述WIFI鞭状天线将接收的广播信息输入车载单元，所述车载单元通过以太网通道将广播信息发送给智能网联自动驾驶域控制器。
与现有技术相比，本发明的有益效果是：
1、本发明可以实现多客车的编队行驶协同控制，可以在真实城市复杂路况下的完全自主编队行驶，底盘域控制器硬件采用双冗余设计，提高了编队行驶的稳定性、安全性和可靠性。
2、编队***可根据当前编队实际形态及当前主、从车实际状态需要，重新选举认证主车，从而实现无固定主车的编队行驶，保证编队行驶的稳定性、安全性和可靠性。
附图说明
下面结合附图及实施例对本发明作进一步描述：
图1是本发明基于V2X的编队行驶智能网联客车的原理框图；
图2是本发明基于V2X的编队行驶智能网联客车的***架构图；
图3是本发明智能网联客车底盘域控制器框图；
图4为本发明客车编队行驶控制流程图。
具体实施方式
为使本发明的目的、技术方案和优点更加清楚明了，下面结合具体实施方式并参照附图，对本发明进一步详细说明。应该理解，这些描述只是示例性的，而并非要限制本发明的范围。此外，在以下说明中，省略了对公知结构和技术的描述，以避免不必要地混淆本发明的概念。
实施例：
如图1、2所示，一种基于V2X的编队行驶智能网联客车，实现基于V2X的编队行驶，自主编队行驶模式多样，采用5G通信技术，可实现智能交通云平台大数据监控。智能网联客车整合客车智能控制、V2X信息互联、环境感知、规划导航、人机交互为一体，并可识别道路标志、自主超车、自主避让和自动靠边停车等。包括以下模块，智能网联自动驾驶域控制器，与智能网联自动驾驶域控制器连接的感知定位装置和V2X信息互联***，每个智能网联客车均搭载有车载单元，智能网联自动驾驶域控制器还连接智能网联底盘域控制器。
各模块具体说明如下：
1、智能网联底盘域控制器
智能网联客车没有踏板、方向盘和驾驶室，客车运动控制通过底盘域控制器完成。智能网联底盘域控制器如图3所示，采用集中式电子电气架构，并充分采用贴片式传感器，有效降低了软硬件开发难度和传感器安装难度及成本，从结构上主要由输入调理电路、输出调理电路、处理器、电源模块和通讯模块组成。
底盘域控制器电源模块将车载直流电源提供的直流电进行稳压分压处理，向处理器和各调理电路供电。根据传感器测量信号的不同处理及数量需要，底盘域控制器输入调理电路包括多路模拟信号处理电路、多路数字信号处理电路和多路开关信号处理电路，其中，模拟信号处理电路采用光电隔离、RC滤波及放大转向角位移、制动压力等模拟电压信号，开关信号处理电路用于光电隔离、RC滤波及电平限幅手刹、车门、变速器档位等开关电压信号，数字信号处理电路用于光电隔离、RC滤波及放大轮速、车速等数字信号。
输出调理电路包括多路频率驱动电路、多路开关驱动电路和多路数字驱动电路，频率驱动电路通过信号放大、光电隔离处理后驱动行车制动电磁阀，开关驱动电路通过信号放大、光电隔离处理后驱动手刹开关、转向灯、车门开关，数字驱动电路通过信号放大、光电隔离处理后驱动档位。底盘域控制器硬件采用双冗余设计，提高***安全性。
底盘域控制器通过车辆CAN线网络和各输入调理电路获得整车位姿、状态和目标需求，处理器对这些实时信息进行综合运算处理，输出控制指令。底盘域控制器的处理器通过车辆CAN线网络实现对电机转向、电机制动、电子油门的驱动控制，从而实现对智能网联客车速度和方向的精确控制。底盘域控制器的处理器的控制指令通过输出调理电路的信号放大、光电隔离等处理后，驱动相应行车制动电磁阀、手刹开关、车门开关、转向灯、制动灯、档位等的控制。
2、V2X信息互联***
V2X主要包括车与车V2V(VehicletoVehicle,如防撞等)、车与人V2P(Vehicle to Pedestrian,如安全预警等)、车与交通路侧基础设施V2I(Vehicle to Infrastructure,如交通信号灯等)、车与网络V2N(Vehicle to Network,如提供实时交通流量报告、云服务等)等车与可能影响车的各实体端子之间的信息互联，如图1所示。V2X采用LTE-V通信技术，为智能网联客车提供实时的车辆信息、道路信息、行人信息等一系列交通信息，并提供远距离环境信号，为本发明的智能网联客车编队自动驾驶***规划、决策、控制等提供信息支持和容错冗余。LTE-V包含了两种通信接口，一种是V2V、V2I等短距离直接通信接口PC5，另一种是蜂窝通信接口Uu实现V2N长距离和更大范围的可靠通信。
V2X信息互联主要通过车载单元(OnBoardUnit,OBU)主机完成，以及还包括WIFI鞭状天线、CAN转接线、以太网线、转12V的DC/DC电源适配器等必需的辅助设备。编队中的智能网联客车每车均搭载有一个OBU，OBU与整车端之间通过CAN线、以太网线进行数据通讯，依托CAN数据通道透传方式将智能网联客车的标志、车速、加速度、转向角、航向角和经纬度定位等数据信息广播给其它编队车辆，各编队客车通过以太网通道接收到广播数据后，将所有编队车辆的当前状态数据做算法融合，合理规划行驶路径、命令车辆智能控制***实现多车编队行驶功能。数据传输与透传通道通畅、丢包率低、正确率100％。
车辆进入拥堵路段前可提获知前方道路的交通流情况，从而进行合理的路径规划，可避让等待或重新选择路线，提高交通运行效率。
3、感知定位集
在编队行驶的自动驾驶智能网联客车中，感知定位集实现环境感知和定位导航两部分功能，环境感知负责采集智能网联客车自动驾驶所需的信息，包括感知智能网联客车自身姿态以及智能网联客车行驶的周围环境等，为自动驾驶智能网联客车的安全行驶提供及时、准确、可靠的决策依据。基于各传感设备的功能、性能及工作条件的特点，智能网联客车采用多传感器感知与信息融合的设计方案，并兼顾信息冗余安全。本发明中编队行驶的每台智能网联客 车的环境感知***均包括1个激光雷达、4个中距角毫米波雷达、5个车载摄像头及若干超声波雷达。其中激光雷达采用以太网与智驾域控制器进行通讯，毫米波雷达采用高速CAN线与智驾域控制器进行通讯，车载视觉摄像头和超声波雷达采用低速CAN总线与智驾域控制器进行通讯。
定位导航用来提供车辆的位置、方向等信息。本发明采用基于GNSS+INS组合定位导航，***由INS惯性陀螺导航单元、双天线RTK卫星导航接收机和5G差分模块组成。5G差分模块通过5G网络接收位置等RTCM差分信息，发送给卫星导航板卡。导航计算机接收3轴惯性陀螺和卫导板卡信息，实时得到***载体即智能网联客车的精确位置、速度、方向。
4、自动驾驶域控制器
车载自动驾驶域控制器将感知定位集采集的多源信息，通过耦合算法数据处理，实时输出准确的载体(即智能网联客车)的姿态、方向、位置、速度、加速度等数据，并提供信息安全冗余，同时构建路线跟踪地图，根据智能网联客车自动驾驶时刻，在行驶过程中根据车辆自身和车辆周围信息和地图信息进行自身方位与姿态的定位，实现自动驾驶和导航。此外，智能网联客车还采用人机交互***用于安全员与车辆的信息交互，安全员通过语音控制及触屏按键实现对车辆参数查询设定、控制指令下发、自动驾驶模式切换、影音娱乐***操控等功能。
客车编队行驶
如图2所示，编队(≥2台客车)里的每台客车均搭载有OBU。客车编队行驶时的控制如图4所示。编队行驶控制流程如下：
1)智能网联客车、底盘域控制器、感知定位集传感器、自动驾驶域控制器等***上电，智能网联客车选择编队行驶模式；
2)感知定位集传感器获取车道和交通等环境感知信息，底盘域控制器获取车辆速度、加速度、转向角等信息，感知定位集传感器和底盘域控制器将获取的信息传输给自动驾驶域控制器；
3)自动驾驶域控制器将这些信息加工处理后，采用CAN数据通道透传方式将信息传输给OBU，鞭状天线与OBU相连，鞭状天线将自车的身份标志、车速、加速度、转向角、航向角和经纬度定位等信息广播出去；
4)同时，鞭状天线接收编队内其它客车(它车)的广播信息，广播信息同样包含身份标志、车速、加速度、转向角、航向角和经纬度定位等信息；
5)鞭状天线接收的广播信息输入OBU，OBU通过以太网通道将这些广播信息发送给自动 驾驶域控制器；
6)自动驾驶域控制器将底盘域控制器信息、感知定位集信息、OBU下载的信息进行融合运算，分析编队行驶状态，如编队拓扑、车间距、行驶路径、车速等是否合理，进而决策出智能网联客车的最佳编队行驶状态，包括无固定主车的编队拓扑形态、编队路径、编队内智能网联客车之间的距离、编队行驶速度等；
7)自动驾驶域控制器根据最佳编队行驶状态决策结果向底盘域控制器输出路径跟踪的目标速度和目标加速度；
8)底盘域控制器实现网联客车的路径跟踪控制，其中，速度控制通过CAN总线驱动电子油门进行加速控制，通过电机制动和行车制动进行减速控制，方向控制通过CAN总线驱动电机进行方向控制；
9)速度控制时，底盘域控制器根据实际车速与期望车速偏差，通过车速控制律计算出期望加速度，进而通过电子油门和电机制动的协同控制实现车辆按照期望车速平稳行驶；
10)方向控制时，底盘域控制器根据客车的位置信息、航向信息和转向信息，通过CAN向转向电机控制器发送直行、左转或右转的等行进命令请求，实现智能网联客车路线精准跟踪。
在编队行车过程中，为保证当前从车能够快速、准确跟随当前主车速度，车速控制律采用前馈加反馈的控制策略来决策智能网联客车的期望加速度，将当前主车加速度信息作为前馈量实现状态的快速响应，并将跟随误差以及速度差作为反馈量来缩小控制误差，同时为避免客车频繁加速、制动的现象，编队根据当前车速大小(分低速、中速、高速三个区段)建立车距控制非线性控制模型，并考虑实际通信延时的影响。若前主车网络故障，或编队***根据当前编队状态认为应当调整当前主车，或有当前从车申请成为主车时，编队***根据当前编队拓扑形态、编队路径、编队内智能网联客车之间的距离、编队行驶速度及目标编队拓扑形态、编队路径、编队内智能网联客车之间的距离、编队行驶速度及编队内各车实际状态，重新选举产生新的主车，从而实现无固定主车的编队行驶，保证编队行驶的稳定性、安全性和可靠性。
交通高峰可以多车编队行驶，非高峰期就可以少辆车编队行驶，或者一辆车行驶，为智能网联客车科学合理调度给出了更多可能性。
本发明具体实现的智能网联客车自动驾驶编队行驶功能包括：
自动驾驶域控制器作为控制模式的仲裁控制器，判断是否满足自动驾驶和编队模式的条件，决定当前是否进入自动驾驶和编队模式；
编队行驶应用5G实现网联V2X技术、V2X与传感器融合技术、编队行驶与智能调度协同 技术、编队行驶控制策略、编队行驶功能安全及信息安全技术等。利用5G的低时延、大带宽、高速率的性能优势，保障车辆编队行驶的安全性、同步性、平顺性和稳定性；
编队***可根据当前编队实际形态及当前主、从车实际状态需要，重新选举认证主车，从而实现无固定主车的编队行驶，保证编队行驶的稳定性、安全性和可靠性；
在无人工干预的情况下，编队车队采用无固定主车机制，各编队车辆可自动变道、加速、互相超越，在主干道编队行驶的客车可以自动脱离编队进入支道行驶，同时，在支道单独行驶的智能网联客车汇入主干道时可以自动加入正在行驶的自动驾驶编队；
能实现红绿灯识别与通讯、避让行人、主动换道、避障、主动超车、隧道通行、驼峰桥通行、跟车、进站以及精确停靠、十字路口通行、车路协同等功能，具备批量运营的能力；具体实现功能的方式可以采用现有公开的技术实现，本申请不再赘述。
提高交通安全性。在浓雾、雨雪、阴暗等恶劣的气候环境条件下，车辆依然能够准确的获取周围车辆所在位置、行驶速度、加速度等信息，即使在特殊路况(如树木、高楼遮挡)的交叉口仍可以实时准确的获取本车周围交通信息，特别是在跟车行驶时，后方车辆通过实时获取牵扯的减速信息，对本车制动进行预判和及时的控制，防止车辆追尾事故的发生、提升制动平顺性；
应当理解的是，本发明的上述具体实施方式仅仅用于示例性说明或解释本发明的原理，而不构成对本发明的限制。因此，在不偏离本发明的精神和范围的情况下所做的任何修改、等同替换、改进等，均应包含在本发明的保护范围之内。此外，本发明所附权利要求旨在涵盖落入所附权利要求范围和边界、或者这种范围和边界的等同形式内的全部变化和修改例。

Claims (6)

  1. 一种基于V2X的编队行驶智能网联客车，包括与智能网联自动驾驶域控制器连接的感知定位装置和V2X信息互联***，其特征在于，所述智能网联客车搭载车载单元，所述智能网联自动驾驶域控制器还连接智能网联底盘域控制器；
    所述智能网联自动驾驶域控制器，用于将感知定位装置采集的多源信息，通过耦合算法数据处理，实时输出智能网联客车状态信息，构建路线跟踪地图，根据智能网联客车在自动驾驶过程中根据车辆自身、车辆周围信息和地图信息进行自身方位与姿态的定位，实现自动驾驶和导航，根据所有编队车辆的当前状态数据进行算法融合，规划行驶路径，决策编队行驶状态，根据决策的编队行驶状态向智能网联底盘域控制器输出路径跟踪的目标速度和目标加速度；
    所述感知定位装置，包括环境感知单元和定位导航单元，所述环境感知单元，用于采集智能网联客车自身姿态及智能网联客车行驶的周围环境信息，所述定位导航单元，实时得到智能网联客车的位置、速度、方向；
    所述V2X信息互联***，用于获取实时的车辆信息、道路信息、行人信息，包括WIFI鞭状天线、CAN总线、及以太网线，所述车载单元与整车端通过CAN总线、以太网线进行数据通讯，所述车载单元通过CAN数据通道透传方式将智能网联客车状态信息广播给其它编队车辆，各编队车辆通过以太网通道接收广播数据；
    所述智能网联底盘域控制器，用于网联客车的路径跟踪控制，包括速度控制和方向控制，所述速度控制通过CAN总线驱动电子油门进行加速控制，通过电机制动和行车制动进行减速控制，所述方向控制通过CAN总线驱动电机进行方向控制，底盘域控制器根据客车的位置信息、航向信息和转向信息，通过CAN总线向转向电机控制器发送直行、左转或右转的行进命令请求。
  2. 根据权利要求1所述的基于V2X的编队行驶智能网联客车，其特征在于，所述智能网联底盘域控制器的速度控制方法包括，根据实际车速与期望车速偏差，通过车速控制律计算出期望加速度，通过电子油门和电机制动的协同控制，控制车辆按照期望车速行驶。
  3. 根据权利要求1所述的基于V2X的编队行驶智能网联客车，其特征在于，所述环境感知单元包括1个激光雷达、4个中距角毫米波雷达、5个车载摄像头及多个超声波雷达，所述激光雷达通过以太网与智能网联自动驾驶域控制器进行通讯，所述毫米波雷达采用高速CAN总线与智能网联自动驾驶域控制器进行通讯，所述车载摄像头和超声波雷达采用低速CAN总线与智能网联自动驾驶域控制器进行通讯。
  4. 根据权利要求1所述的基于V2X的编队行驶智能网联客车，其特征在于，所述智能网联 底盘域控制器包括输入调理电路、输出调理电路、处理器、电源模块和通讯模块，所述电源模块将车载直流电源提供的直流电进行稳压分压处理，向处理器和各调理电路供电，所述输入调理电路包括多路模拟信号处理电路、数字信号处理电路和开关信号处理电路，所述模拟信号处理电路用于光电隔离电路、RC滤波及放大转向角位移、制动压力信号，所述开关信号处理电路用于光电隔离、RC滤波及电平限幅手刹、车门、变速器档位信号，所述数字信号处理电路用于光电隔离、RC滤波及放大轮速、车速，所述输出调理电路包括多路频率驱动电路、开关驱动电路和数字驱动电路，所述频率驱动电路通过信号放大、光电隔离处理后驱动行车制动电磁阀，所述开关驱动电路通过信号放大、光电隔离处理后驱动手刹开关、转向灯、车门开关，所述数字驱动电路通过信号放大、光电隔离处理后驱动档位；所述处理器通过车辆CAN总线发送对电机转向、电机制动、电子油门的驱动控制指令。
  5. 根据权利要求1所述的基于V2X的编队行驶智能网联客车，其特征在于，所述智能网联自动驾驶域控制器决策编队行驶状态包括，根据当前车速大小区间建立车距控制非线性控制模型，根据当前编队状态判断调整当前主车，或有当前从车申请成为主车时，根据当前编队拓扑形态、编队路径、编队内智能网联客车之间的距离、编队行驶速度及目标编队拓扑形态、编队路径、编队内智能网联客车之间的距离、编队行驶速度及编队内各车实际状态，根据设定的选举算法产生新的主车。
  6. 根据权利要求1所述的基于V2X的编队行驶智能网联客车，其特征在于，所述V2X信息互联***中WIFI鞭状天线与车载单元相连，所述WIFI鞭状天线将自车的身份标志、车速、加速度、转向角、航向角和经纬度定位信息广播出去；所述WIFI鞭状天线接收编队内其它客车的广播信息，所述广播信息包含身份标志、车速、加速度、转向角、航向角和经纬度定位信息，所述WIFI鞭状天线将接收的广播信息输入车载单元，所述车载单元通过以太网通道将广播信息发送给智能网联自动驾驶域控制器。
PCT/CN2021/127695 2020-09-25 2021-10-29 一种基于v2x的编队行驶智能网联客车 WO2022063331A1 (zh)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
CN202011022083.6A CN112256020A (zh) 2020-09-25 2020-09-25 一种基于v2x的编队行驶智能网联客车
CN202011022083.6 2020-09-25

Publications (1)

Publication Number Publication Date
WO2022063331A1 true WO2022063331A1 (zh) 2022-03-31

Family

ID=74233156

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CN2021/127695 WO2022063331A1 (zh) 2020-09-25 2021-10-29 一种基于v2x的编队行驶智能网联客车

Country Status (2)

Country Link
CN (1) CN112256020A (zh)
WO (1) WO2022063331A1 (zh)

Cited By (18)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114783170A (zh) * 2022-05-17 2022-07-22 厦门金龙联合汽车工业有限公司 一种智能无人驾驶车辆编队***
CN114783186A (zh) * 2022-04-26 2022-07-22 交通运输部公路科学研究所 智能网联环境下道路风险预警控制器优化布设方法及***
CN114866372A (zh) * 2022-04-22 2022-08-05 锦图计算技术(深圳)有限公司 驾驶域的智能安全网关
CN114995405A (zh) * 2022-05-19 2022-09-02 同济大学 一种基于开放动态环境多目标协同理论的agv协作搬运方法
CN115206081A (zh) * 2022-07-07 2022-10-18 智道网联科技(北京)有限公司 自动驾驶车辆的编队控制***
CN115240445A (zh) * 2022-07-06 2022-10-25 上海电气集团智能交通科技有限公司 一种基于磁钉的v2x路口优先方法
CN115240403A (zh) * 2022-07-28 2022-10-25 同济大学 一种危险敏感型的编队驾驶控制方法
CN115273450A (zh) * 2022-08-19 2022-11-01 北京航空航天大学 一种网联自动驾驶环境下车辆进入编队的换道方法
CN115311839A (zh) * 2022-08-03 2022-11-08 九识(苏州)智能科技有限公司 一种低速自动驾驶车辆组队通过复杂场景的方法
CN115384528A (zh) * 2022-09-05 2022-11-25 中兴智能汽车有限公司 一种集中式底盘域控制架构及方法
CN115457763A (zh) * 2022-08-15 2022-12-09 同济大学 一种后向跟随的智能网联车队拓扑结构及其编队方法
CN116125983A (zh) * 2023-01-03 2023-05-16 广州汽车集团股份有限公司 车辆限速调整方法、装置、电子设备及存储介质
CN116257069A (zh) * 2023-05-16 2023-06-13 睿羿科技(长沙)有限公司 一种无人车辆编队决策与速度规划的方法
CN116390148A (zh) * 2023-06-02 2023-07-04 联友智连科技有限公司 用于对c-v2x无线通信设备的通信距离进行测试的方法和装置
CN116740956A (zh) * 2023-06-29 2023-09-12 西部科学城智能网联汽车创新中心(重庆)有限公司 智能网联车辆速度规划方法及装置
CN117022146A (zh) * 2023-06-16 2023-11-10 智达信科技术股份有限公司 一种客运车辆的双域电子电气架构、工作方法及客运车辆
CN117727183A (zh) * 2024-02-18 2024-03-19 南京淼瀛科技有限公司 结合车路协同的自动驾驶安全预警方法及***
CN118015819A (zh) * 2024-04-10 2024-05-10 济南卓伦智能交通技术有限公司 一种基于驾驶任务的车队协同驾驶方法及***

Families Citing this family (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112256020A (zh) * 2020-09-25 2021-01-22 金龙联合汽车工业（苏州）有限公司 一种基于v2x的编队行驶智能网联客车
CN113200003A (zh) * 2021-06-18 2021-08-03 北京理工华创电动车技术有限公司 一种商用车整车多域集成控制***及方法
CN113511203B (zh) * 2021-07-01 2023-03-28 宁波吉利汽车研究开发有限公司 车辆编队跟驰行驶控制方法、***、设备及存储介质
CN113460066B (zh) * 2021-08-11 2022-12-09 东南大学 一种检测自动驾驶车辆队列中车辆数据传输准确性的方法
CN113885528A (zh) * 2021-11-02 2022-01-04 苏州挚途科技有限公司 动态事件触发机制的固定时间收敛编队控制***和方法
CN113997945A (zh) * 2021-11-25 2022-02-01 东风悦享科技有限公司 一种基于v2x的车辆编队行驶***及方法
CN114319187B (zh) * 2021-12-02 2023-05-16 北京国家新能源汽车技术创新中心有限公司 智能网联汽车控制出入口道闸***
CN114919599B (zh) * 2022-05-17 2023-08-29 厦门金龙联合汽车工业有限公司 一种在自动驾驶车辆上实现车辆编队的装置
CN115497313A (zh) * 2022-08-12 2022-12-20 黑芝麻智能科技(重庆)有限公司 网联车队智能协同控制方法、***、电子设备及存储介质
CN115052023A (zh) * 2022-08-15 2022-09-13 理工雷科智途(北京)科技有限公司 一种高级辅助驾驶***数据传输方法及装置
CN115583249B (zh) * 2022-12-13 2023-06-02 深圳佑驾创新科技有限公司 一种模块化自动驾驶硬件***

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107798861A (zh) * 2017-11-30 2018-03-13 湖北汽车工业学院 一种车辆协作式编队行驶方法及***
CN108011947A (zh) * 2017-11-30 2018-05-08 湖北汽车工业学院 一种车辆协作式编队行驶***
CN109962744A (zh) * 2019-02-25 2019-07-02 北京交通大学 一种c-v2v的资源分配方法及装置
CN111422196A (zh) * 2020-04-16 2020-07-17 金龙联合汽车工业（苏州）有限公司 一种适用于微巴的智能网联自动驾驶***及方法
CN112256020A (zh) * 2020-09-25 2021-01-22 金龙联合汽车工业（苏州）有限公司 一种基于v2x的编队行驶智能网联客车

Family Cites Families (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110308716B (zh) * 2018-03-27 2022-02-25 上海汽车集团股份有限公司 一种基于集群的自动驾驶车辆的方法、装置及车辆
CN109714421B (zh) * 2018-12-28 2021-08-03 国汽(北京)智能网联汽车研究院有限公司 基于车路协同的智能网联汽车运行***
CN109917765B (zh) * 2019-03-28 2020-09-11 东软睿驰汽车技术（沈阳）有限公司 一种基于自动驾驶***的网络架构的集散式域控制器***
CN111369882A (zh) * 2020-04-24 2020-07-03 山东科技大学 展开式投影箱及使用方法

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107798861A (zh) * 2017-11-30 2018-03-13 湖北汽车工业学院 一种车辆协作式编队行驶方法及***
CN108011947A (zh) * 2017-11-30 2018-05-08 湖北汽车工业学院 一种车辆协作式编队行驶***
CN109962744A (zh) * 2019-02-25 2019-07-02 北京交通大学 一种c-v2v的资源分配方法及装置
CN111422196A (zh) * 2020-04-16 2020-07-17 金龙联合汽车工业（苏州）有限公司 一种适用于微巴的智能网联自动驾驶***及方法
CN112256020A (zh) * 2020-09-25 2021-01-22 金龙联合汽车工业（苏州）有限公司 一种基于v2x的编队行驶智能网联客车

Cited By (29)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114866372A (zh) * 2022-04-22 2022-08-05 锦图计算技术(深圳)有限公司 驾驶域的智能安全网关
CN114783186A (zh) * 2022-04-26 2022-07-22 交通运输部公路科学研究所 智能网联环境下道路风险预警控制器优化布设方法及***
CN114783186B (zh) * 2022-04-26 2022-11-22 交通运输部公路科学研究所 智能网联环境下道路风险预警控制器优化布设方法及***
CN114783170A (zh) * 2022-05-17 2022-07-22 厦门金龙联合汽车工业有限公司 一种智能无人驾驶车辆编队***
CN114783170B (zh) * 2022-05-17 2023-08-22 厦门金龙联合汽车工业有限公司 一种智能无人驾驶车辆编队***
CN114995405A (zh) * 2022-05-19 2022-09-02 同济大学 一种基于开放动态环境多目标协同理论的agv协作搬运方法
CN115240445A (zh) * 2022-07-06 2022-10-25 上海电气集团智能交通科技有限公司 一种基于磁钉的v2x路口优先方法
CN115240445B (zh) * 2022-07-06 2023-09-29 上海电气集团智能交通科技有限公司 一种基于磁钉的v2x路口优先方法
CN115206081A (zh) * 2022-07-07 2022-10-18 智道网联科技(北京)有限公司 自动驾驶车辆的编队控制***
CN115240403A (zh) * 2022-07-28 2022-10-25 同济大学 一种危险敏感型的编队驾驶控制方法
CN115240403B (zh) * 2022-07-28 2023-10-10 同济大学 一种危险敏感型的编队驾驶控制方法
CN115311839A (zh) * 2022-08-03 2022-11-08 九识(苏州)智能科技有限公司 一种低速自动驾驶车辆组队通过复杂场景的方法
CN115311839B (zh) * 2022-08-03 2024-05-17 九识(苏州)智能科技有限公司 一种低速自动驾驶车辆组队通过复杂场景的方法
CN115457763A (zh) * 2022-08-15 2022-12-09 同济大学 一种后向跟随的智能网联车队拓扑结构及其编队方法
CN115457763B (zh) * 2022-08-15 2023-08-29 同济大学 一种后向跟随的智能网联车队拓扑结构及其编队方法
CN115273450A (zh) * 2022-08-19 2022-11-01 北京航空航天大学 一种网联自动驾驶环境下车辆进入编队的换道方法
CN115273450B (zh) * 2022-08-19 2023-10-17 北京航空航天大学 一种网联自动驾驶环境下车辆进入编队的换道方法
CN115384528A (zh) * 2022-09-05 2022-11-25 中兴智能汽车有限公司 一种集中式底盘域控制架构及方法
CN116125983A (zh) * 2023-01-03 2023-05-16 广州汽车集团股份有限公司 车辆限速调整方法、装置、电子设备及存储介质
CN116257069B (zh) * 2023-05-16 2023-08-08 睿羿科技(长沙)有限公司 一种无人车辆编队决策与速度规划的方法
CN116257069A (zh) * 2023-05-16 2023-06-13 睿羿科技(长沙)有限公司 一种无人车辆编队决策与速度规划的方法
CN116390148A (zh) * 2023-06-02 2023-07-04 联友智连科技有限公司 用于对c-v2x无线通信设备的通信距离进行测试的方法和装置
CN116390148B (zh) * 2023-06-02 2023-08-11 联友智连科技有限公司 用于c-v2x无线通信设备的通信距离测试方法和装置
CN117022146A (zh) * 2023-06-16 2023-11-10 智达信科技术股份有限公司 一种客运车辆的双域电子电气架构、工作方法及客运车辆
CN117022146B (zh) * 2023-06-16 2024-06-11 智达信科技术股份有限公司 一种客运车辆的双域电子电气架构、工作方法及客运车辆
CN116740956A (zh) * 2023-06-29 2023-09-12 西部科学城智能网联汽车创新中心(重庆)有限公司 智能网联车辆速度规划方法及装置
CN117727183B (zh) * 2024-02-18 2024-05-17 南京淼瀛科技有限公司 结合车路协同的自动驾驶安全预警方法及***
CN117727183A (zh) * 2024-02-18 2024-03-19 南京淼瀛科技有限公司 结合车路协同的自动驾驶安全预警方法及***
CN118015819A (zh) * 2024-04-10 2024-05-10 济南卓伦智能交通技术有限公司 一种基于驾驶任务的车队协同驾驶方法及***

Also Published As

Publication number Publication date
CN112256020A (zh) 2021-01-22

Similar Documents

Publication Publication Date Title
WO2022063331A1 (zh) 一种基于v2x的编队行驶智能网联客车
WO2020187254A1 (zh) 自动驾驶车辆的纵向控制方法***
CN108109415B (zh) 一种具有防拥堵功能的网联自动驾驶控制***及方法
CN111422196A (zh) 一种适用于微巴的智能网联自动驾驶***及方法
CN106774291B (zh) 一种自动驾驶电动汽车的电控***
CN107161075B (zh) 一种基于自动驾驶的转向信号灯自动控制方法及***
RU2659670C1 (ru) Устройство и способ управления движением для транспортного средства
CN208477372U (zh) 一种自动驾驶***
CA3159409A1 (en) Control of automated following in vehicle convoys
CN108922177A (zh) 一种无人驾驶车辆通过交叉路口时速度控制***及方法
RU2671457C1 (ru) Устройство управления движением и способ управления движением
EP3626569B1 (en) Driving assistance device and driving assistance method
JP7271259B2 (ja) 車両管理システム、車両管理装置、および車両管理方法
CN111508254A (zh) 一种高效通过交通路口的控制方法及控制***
CN110412980B (zh) 汽车自动驾驶并线控制方法
CN113570845A (zh) 一种网联式车辆编队行驶方法和***
JP2022060080A (ja) 車両の運転支援装置
WO2020258276A1 (zh) 一种智能驾驶车辆让行方法、装置及车载设备
CN115951678A (zh) 一种用于电子导向胶轮车的自动驾驶***
CN109389846A (zh) 一种固定线路车辆辅助控制方法及***
CN109656242A (zh) 一种自动驾驶行车路径规划***
JP3983414B2 (ja) 自動追従走行システムにおけるターンシグナル制御装置
GB2566648A (en) Electronic map-and electronic compass-based autonomous driving system
CN208477371U (zh) 基于捷联惯导的高速公路自动驾驶***
CN114822083B (zh) 智慧车辆编队辅助控制***

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 21871700

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

122 Ep: pct application non-entry in european phase

Ref document number: 21871700

Country of ref document: EP

Kind code of ref document: A1