CN106708057B - Intelligent vehicle formation driving method - Google Patents
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- 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
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- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/10—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration
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- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
- G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/42—Determining position
- G01S19/45—Determining position by combining measurements of signals from the satellite radio beacon positioning system with a supplementary measurement
- G01S19/47—Determining position by combining measurements of signals from the satellite radio beacon positioning system with a supplementary measurement the supplementary measurement being an inertial measurement, e.g. tightly coupled inertial
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- 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
- G05D1/0231—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means
- G05D1/0246—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using a video camera in combination with image processing means
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- 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
- G05D1/0257—Control of position or course in two dimensions specially adapted to land vehicles using a radar
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- 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
- G05D1/0268—Control of position or course in two dimensions specially adapted to land vehicles using internal positioning means
- G05D1/027—Control of position or course in two dimensions specially adapted to land vehicles using internal positioning means comprising intertial navigation means, e.g. azimuth detector
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- 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
- G05D1/0276—Control of position or course in two dimensions specially adapted to land vehicles using signals provided by a source external to the vehicle
- G05D1/0278—Control of position or course in two dimensions specially adapted to land vehicles using signals provided by a source external to the vehicle using satellite positioning signals, e.g. GPS
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- 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
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Abstract
The invention relates to an intelligent vehicle formation driving method, which comprises the following steps: judging the types of vehicles in the formation, and registering vehicle information; the piloting vehicle acquires the information of the self vehicle and sends the information to the following vehicle; the following vehicle analyzes the pilot vehicle information self-planning path sent by the pilot vehicle to complete the control of the following vehicle; the following vehicle packages the information of the vehicle per se and sends the information to the piloting vehicle; and the pilot vehicle analyzes the received following vehicle information and adjusts the self action. When the method is used for formation driving, the following vehicles can be effectively ensured to drive along the driving path of the pilot vehicle, and the relative distance and speed of the driving vehicles are ensured; when encountering an emergency, a pilot vehicle driver can immediately find the danger and make corresponding response to the danger, so that accidents are avoided, and the safety and the stability of vehicle formation are greatly improved.
Description
Technical Field
The invention relates to the technical field of vehicle formation, in particular to an intelligent vehicle formation driving method.
Background
Currently, the automatic driving technology has become one of the hot spots for the development of new technology for automobiles. The development of domestic intelligent automobiles is greatly improved under the promotion of national science foundation committee and other power organizations, and the future challenge games of the Chinese intelligent automobiles attract the participation of various colleges and universities and research organizations in China, and greatly promote the development of domestic automatic driving technologies. The crossing danger-ground unmanned system challenge race' promotes the application of the automatic driving technology in the field complex environment.
The intelligent vehicles can complete complex tasks which cannot be completed by a single intelligent vehicle when being formed into a team and driven through mutual cooperation among individuals, and the intelligent vehicles have important significance for keeping certain formation in the process of executing some complex tasks, such as safety patrol, guard and the like. The development of the automatic driving technology has great positive significance for enhancing the safety of the vehicle, improving the economy of the vehicle and reducing the environmental pollution caused by emission. In the development of the automatic driving technology, the formation driving method of the intelligent vehicles has obvious effects on relieving road congestion, improving the traffic capacity of roads, enhancing the safety of the vehicles and improving the fuel economy of the vehicles. At present, the environment adaptability of the intelligent vehicle formation driving technology is poor, the guiding-following requirements under different environments cannot be met, and the safety and the stability are insufficient.
Disclosure of Invention
In view of the above analysis, the present invention aims to provide an intelligent vehicle formation driving method, so as to solve the problems of poor adaptability and insufficient safety and stability of the existing formation driving environment.
The purpose of the invention is mainly realized by the following technical scheme:
an intelligent vehicle formation driving method is characterized by comprising the following steps:
step S1, judging the type of the vehicle in the formation and registering the vehicle information;
specifically, whether the vehicle is a piloting vehicle or a following vehicle is judged, wherein the piloting vehicle is in a manual driving mode, and the following vehicle is in an automatic driving mode;
s2, the pilot vehicle acquires the information of the vehicle and the information of the following vehicles and sends the information to each following vehicle;
step S3, the following vehicles analyze the pilot vehicle information sent by the pilot vehicle and the information of other following vehicles in formation;
s4, the following vehicles autonomously plan paths according to the route map information, the positioning navigation information, the environment perception information, the pilot vehicle information and the formation other following vehicle information;
step S5, after the following vehicle obtains the planning result of the vehicle, the planning result is converted into the control quantity which can be executed by the vehicle in the horizontal and vertical control programs and is issued to the vehicle control unit, and the control of the vehicle is completed;
step S6, the following vehicle packages the information of the vehicle and sends the information to the pilot vehicle;
s7, the pilot vehicle analyzes the received following vehicle information and adjusts the self action;
the above steps S2-S7 are repeated to carry out formation driving.
Further, in step S2, the pilot vehicle adjusts its own driving state according to the received sensing device information, combined navigation information, and driver intervention command; and packaging the self vehicle information and sending the self vehicle information to the following vehicle in a radio station broadcasting mode.
Further, the perception device information comprises lane lines, a front vehicle distance, a speed and acceleration information;
the integrated navigation information comprises vehicle position information and vehicle speed information; the vehicle position information includes longitude and latitude information; the vehicle speed information comprises vehicle speed, acceleration and course information;
the self vehicle information of the pilot vehicle is stored in a data packet in a packaging mode, and the data format is divided into a packet header, equipment information, the current frame data volume, vehicle information, verification information and a packet tail.
Further, the equipment information comprises a station serial number and wave rate information;
the vehicle information in the data packet comprises data type, vehicle position information, vehicle speed information, vehicle CAN bus information, vehicle type information, license plate number information and time information;
wherein the data type is used as a starting judgment basis for the complete data of one vehicle; the vehicle position information is vehicle longitude and latitude; the vehicle speed information comprises speed magnitude and direction and acceleration magnitude and direction; the vehicle CAN bus information is used for analyzing the vehicle driving behaviors including information such as steering and braking; the vehicle type information is used for distinguishing whether the vehicle is a special avoidance vehicle; the license plate number information comprises a license plate number and a communication equipment serial number which are used as the identification of the vehicle; the time information is the time information of data receiving and sending and is used for judging the timeliness of the vehicle information in the vehicle linked list.
Further, the following vehicle analyzes the piloting vehicle information sent by the piloting vehicle, and the analyzing process includes:
firstly, analyzing a data source IP and a port, and judging whether the data is station data; if the judgment is yes, verifying the packet head and the packet tail to analyze the piloting vehicle information; and judging whether the vehicle is an effective piloting vehicle or not by taking the data updating time or the data updating frequency as a basis, and storing the analyzed piloting vehicle information into a piloting vehicle information list or updating the piloting vehicle information.
Further, the route map information in step S3 is previously set as the predetermined travel route and the predetermined road section speed limit information;
the positioning navigation information comprises vehicle position and course information and is obtained by a GPS and an inertial navigation system;
the environment perception information comprises the distance of a front vehicle, speed information and lane line information of the vehicle, and is obtained by a millimeter wave radar and a camera.
Further, the step S4 includes the following vehicle obtaining the pilot vehicle information, the formation other vehicle information and the vehicle network information according to the communication module; and acquiring information of the sensing equipment through the sensing module, sending the information to the control module, and processing the information by the control module to complete path planning.
Further, the control module comprehensively analyzes the received information to obtain a planning result; and converting the planning result into a vehicle executable control quantity in transverse control and longitudinal control programs and issuing the vehicle executable control quantity to the vehicle control unit, controlling steering control, accelerator control and braking control of the vehicle by the vehicle control unit to obtain the action quantity of a steering wheel, accelerator opening and a brake pedal, and executing the action to finish the control of the following vehicle.
Further, the pilot vehicle obtains the following vehicle information, the following vehicle information is combined with the vehicle information of the pilot vehicle, the information is displayed in a driver monitoring interface, the pilot vehicle timely and correspondingly adjusts the speed, the acceleration and the inter-vehicle distance of the pilot vehicle according to the state of the following vehicle in formation, and the formation speed and the inter-vehicle distance are controlled within a proper range.
The invention has the following beneficial effects:
the intelligent vehicle formation driving method provided by the invention is beneficial to improving the guiding-following capability of the automatic driving vehicle in different environments. The information such as GPS, inertial navigation, radar and the like is fused to complete the accurate positioning of the relative positions of the vehicle and the road without high-precision positioning equipment and a high-precision map. When the formation runs, the following vehicles can be effectively ensured to run along the running path of the pilot vehicle, and the relative distance and speed of the running vehicles are ensured; when encountering an emergency, a pilot vehicle driver can immediately find the danger and make corresponding response to the danger, so that accidents are avoided, and the safety and the stability of the formation vehicles are greatly improved.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
Drawings
The drawings are only for purposes of illustrating particular embodiments and are not to be construed as limiting the invention, wherein like reference numerals are used to designate like parts throughout.
FIG. 1 is a schematic diagram of a formation run according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a formation driving process according to an embodiment of the present invention;
FIG. 3 is a schematic data flow diagram of a pilot vehicle according to an embodiment of the present invention;
FIG. 4 is a diagram illustrating data protocol packing according to an embodiment of the present invention
FIG. 5 is a diagram illustrating a data protocol analysis according to an embodiment of the present invention;
FIG. 6 is a block diagram of an autopilot platform system according to an embodiment of the present invention;
FIG. 7 is a schematic structural diagram of a communication module of a following vehicle according to an embodiment of the present invention;
FIG. 8 is a diagram of a sensing module according to an embodiment of the present invention;
FIG. 9 is a block diagram of a control module according to an embodiment of the present invention;
FIG. 10 is a schematic following vehicle data flow diagram in accordance with an embodiment of the present invention;
fig. 11 is a schematic structural diagram of a communication module of a piloted vehicle according to an embodiment of the invention.
Detailed Description
The preferred embodiments of the present invention will now be described in detail with reference to the accompanying drawings, which form a part hereof, and which together with the embodiments of the invention serve to explain the principles of the invention.
As shown in fig. 1, the intelligent vehicle formation driving method is realized by adopting a piloting following mode, and a Leader vehicle is used as a formation piloting vehicle and carries corresponding sensors and equipment, so that the intelligent vehicle formation driving method is an artificial driving mode; the following vehicle is an automatic driving vehicle, and can sense the vehicle environment, position and navigate and control the motion behavior according to the expected driving state of the formation, so as to realize automatic driving and following.
The meaning of the parameters in FIG. 1 is defined as follows:
vehicle following error distance SError: distance errors caused by following of rear vehicles due to the accuracy of vehicle systems (sensor sensing, positioning systems, vehicle control and the like) in the vehicle formation driving process;
expected driving distance S of vehicleDe: the expected following distance between two vehicles in the formation driving process is comprehensively considered by considering factors such as expected driving efficiency of the vehicles, formation driving speed, formation driving economy, control characteristics of the vehicles and the like, and comprises a vehicle delay distance and an expected vehicle stopping distance;
vehicle response distance SDelay: considering the response distance of the rear vehicle caused by the speed change of the front vehicle caused by the factors of the vehicle communication period, the sensor data receiving and processing period, the response period and delay of the vehicle controller, the road adhesion coefficient and the like;
expected parking distance S of vehicleSafe: i.e. in a well-controlled conditionThe lower rear vehicle is a stopping distance from the front vehicle.
The vehicle formation driving limiting conditions of the embodiment are as follows:
1) following vehicles are not allowed to leave the convoy;
2) other vehicles are not allowed to join the formation, e.g. the merging of other vehicles can only take place in front of the pilot vehicle;
3) the vehicle is not allowed to change positions during driving, such as overtaking.
In the embodiment, the following vehicles can automatically adjust the transverse and longitudinal motion states of the following vehicles according to the information of the pilot vehicle, so that the front and rear vehicles finally reach consistent running speed and stable transverse and longitudinal distance. The method mainly comprises two stages: in the first stage, sensing equipment and other equipment detect surrounding environment information, and vehicle information and the surrounding environment information are transmitted to a following vehicle through communication equipment; and in the second stage, after the following vehicle obtains the relevant information of the pilot vehicle, the autonomous planned path runs along with the pilot vehicle.
As shown in fig. 2, the symbols in the figure have the following meanings:
1, representing an internet communication service registration request when a vehicle formation prepares to run, namely, the vehicle networking technology needs to add and record vehicle information from a server and issue the vehicle information, and the information is completed by the internet communication technology;
2, indicating the preparation state information of the following vehicle, namely whether the preparation work completion condition (including system modules such as sensing, positioning and navigation) of the vehicle before driving is in the formation automatic driving state or not, wherein the information is completed by means of a network communication technology;
3, representing the expected state and the running rule information of the following vehicle, wherein the information is finished by means of the internet communication technology;
4, the main information required by the automatic driving of the vehicle comprises a route map, positioning navigation and environment perception, wherein the route map is information such as a preset running route, a road section speed limit and the like and needs to be set in advance; the positioning navigation provides information such as vehicle position, course and the like, and the information can be completed by a GPS and inertial navigation system combination method; the environment perception mainly provides information of the distance and the speed of a vehicle in front, and needs to detect a lane line where the vehicle is located, and the information is finished by a millimeter wave radar and a camera;
5, expected state information of vehicle formation running is preset and transmitted to an automatic driving vehicle planning controller for planning control;
6, outputting the information (such as the expected front wheel deflection angle, the expected speed, the acceleration and the like) of the expected transverse and longitudinal states of the vehicle by the vehicle planning controller, and finishing the information through UDP communication by a planning control module;
7 is the actual control quantity (such as steering wheel angle, throttle valve value, brake pressure value, etc.) which CAN be executed by the vehicle bottom actuator, and CAN be completed by the vehicle CAN communication;
8, representing the feedback information of the bottom state of the vehicle, and carrying out closed-loop planning and control by the planning controller according to the expected state and the current state of the vehicle, wherein the closed-loop planning and control can be completed by a vehicle serial port and UDP communication;
9, the real-time change of the vehicle position and the surrounding environment caused by the change of the vehicle position in the running process of the vehicle needs to be updated in real time according to the running position, and the real-time update of the information can be automatically completed in the vehicle environment sensing and positioning navigation module;
10, sending data for the real-time vehicle state, wherein the data is transmitted to an internet communication server through a vehicle-mounted internet communication device;
11, judging whether the vehicle state is normal according to the driving rule, and transmitting the data to the internet communication server through the vehicle-mounted internet communication device.
The intelligent vehicle formation driving method comprises the following steps:
step S1, judging the type of the vehicle in the formation and registering the vehicle information;
specifically, whether the vehicle is a piloting vehicle or a following vehicle is judged, wherein the piloting vehicle is in a manual driving mode, and the following vehicle is in an automatic driving mode. And performing network registration on the corresponding vehicle information, and adding all the vehicle information into the online server.
And step S2, the pilot vehicle acquires the information of the self vehicle and the information of the following vehicle, packages the information and sends the information to the following vehicle.
As shown in fig. 3, the pilot vehicle continuously receives the sensing device information, the combined navigation information and the driver intervention instruction, and adjusts the driving state of the pilot vehicle; and packaging the self vehicle information and sending the self vehicle information to the following vehicle in a radio station broadcasting mode.
The sensing equipment information comprises lane lines, front vehicle distance, speed and acceleration information.
The combined navigation information comprises vehicle position information and vehicle speed information; the vehicle position information includes longitude and latitude information; the vehicle speed information includes vehicle speed, acceleration, and heading information.
As shown in fig. 4, the vehicle information is stored in the data packet by each vehicle, and the single-frame data format is divided into a header, device information, a current frame data amount, vehicle information, check information, and a trailer. The equipment information comprises information such as a station serial number, a baud rate and the like. The vehicle information comprises data type, vehicle position information, vehicle speed information, vehicle CAN bus information, vehicle type information, license plate number information and time information. Wherein the data type is used as a starting judgment basis for the complete data of one vehicle; the vehicle position information is vehicle longitude and latitude; the vehicle speed information comprises speed magnitude and direction and acceleration magnitude and direction; the vehicle CAN bus information is used for analyzing the vehicle driving behaviors including information such as steering and braking; the vehicle type information is used for distinguishing whether the vehicle is a special avoidance vehicle; the license plate number information comprises a license plate number and a communication equipment serial number which are used as the identification of the vehicle; the time information is the time information of data receiving and sending and is used for judging the timeliness of the vehicle information in the vehicle linked list.
And step S3, the following vehicle analyzes the information sent by the pilot vehicle.
As shown in fig. 5, after receiving the radio station data, the following vehicle performs data protocol analysis, where the analysis process specifically includes:
firstly, analyzing a data source IP and a port, and judging whether the data is station data; if the judgment is yes, the packet head and the packet tail are checked to analyze the piloting vehicle information (vehicle position information, vehicle speed information, vehicle type information, CAN bus information, license plate number information and time information); and judging whether the vehicle is an effective piloting vehicle or not by taking the data updating time or the data updating frequency as a basis, and storing the analyzed piloting vehicle information into a piloting vehicle information list or updating the piloting vehicle information.
And analyzing the information of other following vehicles in the formation by adopting the same analysis mode.
And step S4, the following vehicles autonomously plan paths according to the route map information, the positioning navigation information, the environment perception information, the pilot vehicle information and the formation other following vehicle information.
The route map information is information such as a preset driving route, a road section speed limit and the like and needs to be set in advance; the positioning navigation information comprises information such as vehicle position, course and the like, and the information is obtained by combining a GPS (global positioning system) and an inertial navigation system; the environment perception information comprises the distance of a front vehicle, speed information and a lane line where the vehicle is located, and the information is finished by means of a millimeter wave radar and a camera.
As shown in fig. 6, the following vehicle obtains the pilot vehicle information, formation other vehicle information, and vehicle network information according to the communication module; and obtaining the perception device information through the perception module. And the control module processes the information and then issues a control instruction to complete path planning.
As shown in fig. 7, the process of the communication module obtaining the vehicle information: the communication module acquires 8 items of piloting vehicle information including speed and the like through communication software, and simultaneously acquires the vehicle information including vehicle speed, acceleration, front wheel deflection angle, course, longitude, latitude, ID number and distance from the vehicle to the front; and packaging the information and sending the information to the communication equipment and the control module.
As shown in fig. 8, the process of acquiring sensing device information includes: the millimeter wave radar acquires environmental data through a millimeter wave singlechip program, performs data processing in the upper computer, and sends the processed data to the perception information comprehensive processor; the camera also sends the measured related information to the perception information comprehensive processor; the perception information comprehensive processor simultaneously receives formation network information, comprehensively processes the received three items of information, sends the processed information to the control module, and displays the comprehensive processing result through the perception display interface.
As shown in fig. 9, the process of completing the path planning by the control module is as follows: and the control module comprehensively analyzes and obtains a planning result according to the received formation network information, the perception information and the vehicle state information.
The following requirements are met by the following vehicle autonomous planning path
1) And controlling the distance between the two vehicles. The distance between the vehicles is not too large, so that the driving efficiency, the driving speed and the like of the vehicle formation are reduced; it is not suitable for the occurrence of accidents such as rear-end collision due to untimely parking of the vehicle under special conditions.
2) And controlling the formation distance. In the formation driving process, due to control errors, the formation length is allowed to be adjusted within a certain range, certain speed and distance adjustment is carried out on the basis of meeting the formation stability, and the conditions of too small and too large intervals and the like are avoided.
n·Smin≤∑Si≤n·Smax
3) And controlling the speed error range. Namely, in the driving process of the formation of the vehicles, the speed control error between the rear vehicle and the front vehicle is controlled within a certain range, namely, the vehicles are not subjected to large-amplitude speed mutation in the process of adjusting the expected distance between the vehicles, so that the robustness of the formation system is poor.
4) And controlling an acceleration range. That is, the vehicle should not have a large speed increase during acceleration, which causes the interference of the expected speed of the vehicle behind and the instability of formation driving. And in the normal running process, when the vehicle is stopped in a non-emergency condition, the vehicle is not easy to generate excessive deceleration.
And step S5, after the following vehicle obtains the planning result of the vehicle, converting the planning result into the control quantity which can be executed by the vehicle in the horizontal and vertical control programs and transmitting the control quantity to the vehicle control unit to finish the control of the vehicle.
As shown in fig. 9, the planning result is converted into a vehicle executable control amount in the transverse control and longitudinal control program and is issued to the vehicle control unit, the vehicle control unit controls the steering control, the accelerator control and the braking control of the vehicle, and the movement amount of the steering wheel, the accelerator opening and the brake pedal is obtained, and the vehicle control is completed by executing the movement.
And step S6, the following vehicle packages and sends the own vehicle information to the pilot vehicle.
As shown in fig. 10, the following vehicle obtains own vehicle information from the combined navigation device and perception device, including: longitude, latitude, heading, speed, acceleration, front wheel slip angle, ID number; and packaging the information in a certain mode and sending the information to a radio station so as to transmit the information to a piloting vehicle.
And step S7, the pilot vehicle analyzes the received following vehicle information and adjusts the self action.
As shown in fig. 11, the pilot vehicle obtains the following vehicle information, and displays the information in the driver monitoring interface in combination with the vehicle information of the pilot vehicle, and the pilot vehicle receives the information of the following vehicle, knows the state of the following vehicle, and timely adjusts the speed, the acceleration and the inter-vehicle distance of the pilot vehicle, so as to control the formation speed and the inter-vehicle distance within a proper range.
And repeating the steps S2-S7 to complete formation driving.
In summary, the embodiment of the invention provides an intelligent vehicle formation driving method, which is beneficial to improving the guiding-following capability of an automatic driving vehicle in different environments. The information such as GPS, inertial navigation, radar and the like is fused to complete the accurate positioning of the relative positions of the vehicle and the road without high-precision positioning equipment and a high-precision map. When the formation runs, the following vehicles can be effectively ensured to run along the running path of the pilot vehicle, and the relative distance and speed of the running vehicles are ensured; when encountering an emergency, a pilot vehicle driver can immediately find the danger and make corresponding response to the danger, so that accidents are avoided, and the safety and the stability of vehicle formation are greatly improved.
Those skilled in the art will appreciate that all or part of the flow of the method implementing the above embodiments may be implemented by a computer program, which is stored in a computer readable storage medium, to instruct related hardware. The computer readable storage medium is a magnetic disk, an optical disk, a read-only memory or a random access memory.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are included in the scope of the present invention.
Claims (9)
1. An intelligent vehicle formation driving method is characterized by comprising the following steps:
step S1, judging the type of the vehicle in the formation and registering the vehicle information;
specifically, whether the vehicle is a piloting vehicle or a following vehicle is judged, wherein the piloting vehicle is in a manual driving mode, and the following vehicle is in an automatic driving mode; when the vehicle formation is ready to run, network registration is carried out on corresponding vehicle information, all the vehicle information is added into the internet server, and the vehicle information is distributed;
s2, the pilot vehicle acquires the information of the vehicle and the information of the following vehicles and sends the information to each following vehicle; in the step S2, the pilot vehicle adjusts its own driving state according to the received sensing device information, combined navigation information, and driver intervention instruction;
step S3, the following vehicles analyze the pilot vehicle information sent by the pilot vehicle and the information of other following vehicles in formation;
s4, the following vehicles autonomously plan paths according to the route map information, the positioning navigation information, the environment perception information, the pilot vehicle information and the formation other following vehicle information;
the requirements to be met by the autonomous planning path include: the method comprises the following steps of (1) controlling the distance of a travelling crane, controlling the formation distance, controlling the speed error range and controlling the acceleration range;
step S5, after the following vehicle obtains the planning result of the vehicle, the planning result is converted into the control quantity which can be executed by the vehicle in the horizontal and vertical control programs and is issued to the vehicle control unit, and the control of the vehicle is completed;
step S6, the following vehicle packages the information of the vehicle and sends the information to the pilot vehicle;
s7, the pilot vehicle analyzes the received following vehicle information and adjusts the self action;
repeating the steps S2-S7 to carry out formation driving;
wherein following vehicles are not allowed to leave the convoy; no other vehicles are allowed to join the formation.
2. The formation travel method according to claim 1, characterized in that: in step S2, the pilot vehicle packages the vehicle information and sends the packaged vehicle information to the following vehicle in a broadcasting manner.
3. The formation travel method according to claim 2, characterized in that:
the perception equipment information comprises lane lines, the distance of a front vehicle, speed and acceleration information;
the integrated navigation information comprises vehicle position information and vehicle speed information; the vehicle position information includes longitude and latitude information; the vehicle speed information comprises vehicle speed, acceleration and course information;
the self vehicle information of the pilot vehicle is stored in a data packet in a packaging mode, and the data format is divided into a packet header, equipment information, the current frame data volume, vehicle information, verification information and a packet tail.
4. The formation travel method according to claim 3, characterized in that: the equipment information comprises a radio station serial number and wave rate information;
the vehicle information in the data packet comprises data type, vehicle position information, vehicle speed information, vehicle CAN bus information, vehicle type information, license plate number information and time information;
wherein the data type is used as a starting judgment basis for the complete data of one vehicle; the vehicle position information is vehicle longitude and latitude; the vehicle speed information comprises speed magnitude and direction and acceleration magnitude and direction; the vehicle CAN bus information is used for analyzing the vehicle driving behaviors including steering and braking information; the vehicle type information is used for distinguishing whether the vehicle is a special avoidance vehicle; the license plate number information comprises a license plate number and a communication equipment serial number which are used as the identification of the vehicle; the time information is the time information of data receiving and sending and is used for judging the timeliness of the vehicle information in the vehicle linked list.
5. The formation travel method according to claim 3, characterized in that: the following vehicle analyzes the piloting vehicle information sent by the piloting vehicle, and the analyzing process comprises the following steps:
firstly, analyzing a data source IP and a port, and judging whether the data is station data; if the judgment is yes, verifying the packet head and the packet tail to analyze the piloting vehicle information; and judging whether the vehicle is an effective piloting vehicle or not by taking the data updating time or the data updating frequency as a basis, and storing the analyzed piloting vehicle information into a piloting vehicle information list or updating the piloting vehicle information.
6. The formation travel method according to claim 1, characterized in that: the route map information in the step S3 is previously set for a predetermined travel route and speed limit information of the road section;
the positioning navigation information comprises vehicle position and course information and is obtained by a GPS and an inertial navigation system;
the environment perception information comprises the distance of a front vehicle, speed information and lane line information of the vehicle, and is obtained by a millimeter wave radar and a camera.
7. The formation travel method according to claim 1, characterized in that: the step S4 includes that the following vehicle obtains pilot vehicle information, formation other vehicle information and vehicle network information according to the communication module; and acquiring information of the sensing equipment through the sensing module, sending the information to the control module, and processing the information by the control module to complete path planning.
8. The formation travel method according to claim 7, characterized in that: the control module comprehensively analyzes the received information to obtain a planning result; and converting the planning result into a vehicle executable control quantity in transverse control and longitudinal control programs and issuing the vehicle executable control quantity to the vehicle control unit, controlling steering control, accelerator control and braking control of the vehicle by the vehicle control unit to obtain the action quantity of a steering wheel, accelerator opening and a brake pedal, and executing the action to finish the control of the following vehicle.
9. The formation travel method according to claim 1 or 8, characterized in that: the pilot vehicle obtains the following vehicle information, the following vehicle information is combined with the pilot vehicle, the information is displayed in a driver monitoring interface, the pilot vehicle timely and correspondingly adjusts the speed, the acceleration and the workshop distance of the pilot vehicle according to the state of the following vehicle in formation, and the formation speed and the workshop distance are controlled within a proper range.
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Families Citing this family (59)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP3500940A4 (en) * | 2016-08-22 | 2020-03-18 | Peloton Technology, Inc. | Automated connected vehicle control system architecture |
| CN107145150B (en) * | 2017-06-16 | 2020-04-21 | 华为技术有限公司 | Automatic driving method for motor vehicle and terminal equipment |
| CN107357288B (en) * | 2017-06-23 | 2020-07-31 | 东南大学 | Device and method for double-vehicle cooperative motion of Mecanum wheel robot |
| EP3418843B1 (en) | 2017-06-23 | 2021-03-17 | Volkswagen Aktiengesellschaft | Concept of coordinating an emergency braking of a platoon of communicatively coupled vehicles |
| JP7091040B2 (en) * | 2017-09-07 | 2022-06-27 | 株式会社ダイフク | Transport system |
| US20180022348A1 (en) * | 2017-09-15 | 2018-01-25 | GM Global Technology Operations LLC | Methods and systems for determining lane health from an autonomous vehicle |
| US10481600B2 (en) * | 2017-09-15 | 2019-11-19 | GM Global Technology Operations LLC | Systems and methods for collaboration between autonomous vehicles |
| CN107885197A (en) * | 2017-09-19 | 2018-04-06 | 中车工业研究院有限公司 | The control method and device of automatic driving vehicle in intelligent mass transit system |
| CN109559499B (en) * | 2017-09-26 | 2021-06-01 | 郑州宇通客车股份有限公司 | Vehicle queue running management platform, control method and vehicle-mounted terminal |
| JP7031212B2 (en) * | 2017-10-12 | 2022-03-08 | トヨタ自動車株式会社 | Mobility support system and mobility support method |
| CN109724600A (en) * | 2017-10-30 | 2019-05-07 | 湖南中车时代电动汽车股份有限公司 | A kind of local path fault-tolerance approach for intelligent driving vehicle |
| CN107945502A (en) * | 2017-11-16 | 2018-04-20 | 东南大学 | A kind of fleet's emerging system and method based on intelligent transportation |
| CN110308716B (en) * | 2018-03-27 | 2022-02-25 | 上海汽车集团股份有限公司 | Cluster-based method and device for automatically driving vehicle and vehicle |
| JP7096060B2 (en) * | 2018-04-25 | 2022-07-05 | 日野自動車株式会社 | Formation system |
| CN108646737A (en) * | 2018-05-03 | 2018-10-12 | 韩静超 | A kind of novel intelligent highway transport vehicle control system and its control method |
| WO2019212239A1 (en) | 2018-05-04 | 2019-11-07 | Lg Electronics Inc. | A plurality of robot cleaner and a controlling method for the same |
| KR102067603B1 (en) * | 2018-05-04 | 2020-01-17 | 엘지전자 주식회사 | A plurality of robot cleaner and a controlling method for the same |
| CN108594830B (en) * | 2018-06-10 | 2020-06-30 | 同济大学 | Spatial domain-based networked intelligent vehicle formation driving control method |
| CN110580038B (en) * | 2018-06-11 | 2020-11-24 | 上海交通大学 | Automatic driving and following device and automatic driving motorcade system |
| EP3826891A1 (en) * | 2018-07-25 | 2021-06-02 | Bendix Commercial Vehicle Systems, LLC | Towing vehicle controller using trailer braking strategy and trailer braking control method |
| CN109164809B (en) * | 2018-09-20 | 2022-02-22 | 北京机械设备研究所 | Autonomous following control system and method for vehicle formation |
| CN109144076B (en) * | 2018-10-31 | 2020-05-22 | 吉林大学 | Multi-vehicle transverse and longitudinal coupling cooperative control system and control method |
| KR102463723B1 (en) * | 2018-11-07 | 2022-11-07 | 현대자동차주식회사 | Apparatus for controlling steering of platooning vehicle and method thereof |
| CN109270938B (en) * | 2018-11-20 | 2021-05-11 | 吉林大学 | Mining car matrix formation control system |
| CN109597414B (en) * | 2018-12-06 | 2022-03-18 | 英华达（上海）科技有限公司 | Driving system and method for average energy consumption of self-driving vehicle fleet |
| CN111627247B (en) * | 2019-02-28 | 2022-02-18 | 上海汽车集团股份有限公司 | Multi-vehicle formation control method and device |
| CN110262493A (en) * | 2019-06-25 | 2019-09-20 | 北京智行者科技有限公司 | The method and device of unmanned vehicle fleet evolution |
| US11429115B2 (en) * | 2019-06-27 | 2022-08-30 | Baidu Usa Llc | Vehicle-platoons implementation under autonomous driving system designed for single vehicle |
| CN112277942A (en) * | 2019-07-12 | 2021-01-29 | 北京图森智途科技有限公司 | Queue control method for automatically driving vehicle, vehicle-mounted device and system |
| CN110428603B (en) * | 2019-07-26 | 2021-04-23 | 北京主线科技有限公司 | Method and device for controlling following vehicle running in container truck formation |
| CN110992676B (en) * | 2019-10-15 | 2021-06-04 | 同济大学 | Road traffic capacity and internet automatic driving vehicle equivalent coefficient estimation method |
| CN110838228B (en) * | 2019-10-18 | 2021-07-02 | 东南大学 | Intelligent interactive driving system and device for commercial truck fleet |
| CN110838229A (en) * | 2019-10-22 | 2020-02-25 | 南京航空航天大学 | Vehicle queue formation method |
| CN110941003B (en) * | 2019-10-25 | 2022-02-25 | 北京汽车集团有限公司 | Vehicle identification method, device, storage medium and electronic equipment |
| CN110570648A (en) * | 2019-10-29 | 2019-12-13 | 北京百度网讯科技有限公司 | method, device and equipment for adjusting formation driving and computer readable storage medium |
| CN110691321B (en) * | 2019-10-29 | 2021-06-22 | 北京汽车集团有限公司 | Terminal control method, device and equipment |
| CN112835352B (en) * | 2019-11-25 | 2022-10-04 | 华为云计算技术有限公司 | Formation control method and device, vehicle, electronic device and storage medium |
| CN111290400B (en) * | 2020-03-18 | 2022-05-31 | 清华大学苏州汽车研究院（相城） | Separation control method for motorcade cooperative driving |
| CN111290399B (en) * | 2020-03-18 | 2022-05-27 | 清华大学苏州汽车研究院（相城） | Team cooperative driving team forming control method |
| CN113525405B (en) * | 2020-04-22 | 2022-09-13 | 北京图森智途科技有限公司 | Auxiliary control method for automatic driving vehicle, vehicle-mounted device and system |
| CN113734168B (en) * | 2020-05-15 | 2023-01-20 | 北京机械设备研究所 | Vehicle formation driving method |
| DE102020207283A1 (en) * | 2020-06-10 | 2021-12-16 | Volkswagen Aktiengesellschaft | Control center, vehicle, method, device and computer program for taking control of a vehicle to be controlled |
| CN111913389B (en) * | 2020-08-20 | 2021-02-26 | 襄阳达安汽车检测中心有限公司 | Vehicle formation longitudinal control method based on vehicle-vehicle communication |
| CN112034714A (en) * | 2020-09-08 | 2020-12-04 | 北京航空航天大学 | Grouping time-varying formation enclosure tracking control method and system |
| CN112261588B (en) * | 2020-10-19 | 2022-07-05 | 中国科学院合肥物质科学研究院 | Self-adaptive formation networking method, system and equipment for multiple unmanned vehicles guided by vehicles |
| CN112631287B (en) * | 2020-12-08 | 2022-07-01 | 重庆邮电大学 | Vehicle formation control system and method in Internet of vehicles environment |
| CN113734169A (en) * | 2020-12-16 | 2021-12-03 | 江铃汽车股份有限公司 | Car following control method and system based on vehicle-road cooperation |
| CN114690759A (en) * | 2020-12-31 | 2022-07-01 | 宝能汽车集团有限公司 | Automatic driving method and system, computer device and readable storage medium |
| CN112820097A (en) * | 2021-01-08 | 2021-05-18 | 重庆邮电大学 | Truck fleet longitudinal hierarchical control method based on 5G-V2X and unmanned aerial vehicle |
| CN112815959B (en) * | 2021-04-19 | 2021-09-07 | 禾多科技（北京）有限公司 | Vehicle lane level positioning system, method and device and electronic equipment |
| CN114061573B (en) * | 2021-11-16 | 2024-03-22 | 中国人民解放军陆军工程大学 | Ground unmanned vehicle formation positioning device and method |
| CN113848957B (en) * | 2021-11-17 | 2023-11-10 | 中国人民解放军陆军工程大学 | Ground unmanned vehicle formation control device and method |
| CN115214662A (en) * | 2021-12-09 | 2022-10-21 | 广州汽车集团股份有限公司 | Following vehicle speed control method and system based on vehicle formation driving |
| CN114475598A (en) * | 2022-02-28 | 2022-05-13 | 肇庆市前沿德至智能汽车测试评估有限公司 | High-speed queuing driving system and queuing method for unmanned vehicle |
| CN114506323B (en) * | 2022-04-20 | 2022-07-12 | 北京主线科技有限公司 | Formation vehicle control method, device, equipment and medium |
| CN114924678A (en) * | 2022-04-24 | 2022-08-19 | 北京主线科技有限公司 | Vehicle formation display method and device and electronic equipment |
| CN114550105B (en) * | 2022-04-25 | 2022-08-09 | 南通顺沃供应链管理有限公司 | Goods transportation method and system based on Internet of vehicles |
| CN115675493B (en) * | 2023-01-04 | 2023-08-11 | 北京易控智驾科技有限公司 | Unmanned method and device using manual driving track layer information |
| CN116719328B (en) * | 2023-08-10 | 2023-11-24 | 北京理工大学 | Multi-unmanned vehicle formation control and obstacle avoidance reconstruction method and system |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6985089B2 (en) * | 2003-10-24 | 2006-01-10 | Palo Alto Reserach Center Inc. | Vehicle-to-vehicle communication protocol |
| JP3818722B2 (en) * | 1997-03-21 | 2006-09-06 | 富士通テン株式会社 | Vehicle group formation control device |
| CN102906654A (en) * | 2010-05-31 | 2013-01-30 | 沃尔沃汽车公司 | Control system for travel in a platoon |
| CN104471624A (en) * | 2012-05-16 | 2015-03-25 | 大陆-特韦斯贸易合伙股份公司及两合公司 | Method and system for autonomous tracking of a following vehicle on the track of a leading vehicle |
| CN105067003A (en) * | 2015-08-14 | 2015-11-18 | 深圳市赛格导航科技股份有限公司 | System and method for vehicle following |
| CN106314423A (en) * | 2015-06-30 | 2017-01-11 | 丰田自动车株式会社 | Vehicle traveling control device |
-
2017
- 2017-02-16 CN CN201710083950.9A patent/CN106708057B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP3818722B2 (en) * | 1997-03-21 | 2006-09-06 | 富士通テン株式会社 | Vehicle group formation control device |
| US6985089B2 (en) * | 2003-10-24 | 2006-01-10 | Palo Alto Reserach Center Inc. | Vehicle-to-vehicle communication protocol |
| CN102906654A (en) * | 2010-05-31 | 2013-01-30 | 沃尔沃汽车公司 | Control system for travel in a platoon |
| CN104471624A (en) * | 2012-05-16 | 2015-03-25 | 大陆-特韦斯贸易合伙股份公司及两合公司 | Method and system for autonomous tracking of a following vehicle on the track of a leading vehicle |
| CN106314423A (en) * | 2015-06-30 | 2017-01-11 | 丰田自动车株式会社 | Vehicle traveling control device |
| CN105067003A (en) * | 2015-08-14 | 2015-11-18 | 深圳市赛格导航科技股份有限公司 | System and method for vehicle following |
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