WO2021243710A1 - 一种基于智能交通***的自动驾驶方法、装置和智能交通*** - Google Patents

一种基于智能交通***的自动驾驶方法、装置和智能交通*** Download PDF

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Publication number
WO2021243710A1
WO2021243710A1 PCT/CN2020/094719 CN2020094719W WO2021243710A1 WO 2021243710 A1 WO2021243710 A1 WO 2021243710A1 CN 2020094719 W CN2020094719 W CN 2020094719W WO 2021243710 A1 WO2021243710 A1 WO 2021243710A1
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Prior art keywords
road
automatic driving
vehicle
information
vehicles
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PCT/CN2020/094719
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English (en)
French (fr)
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曹庆恒
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曹庆恒
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Application filed by 曹庆恒 filed Critical 曹庆恒
Priority to PCT/CN2020/094719 priority Critical patent/WO2021243710A1/zh
Priority to CN202080000912.2A priority patent/CN113330497A/zh
Priority to PCT/CN2021/098508 priority patent/WO2021244655A1/zh
Priority to CN202180001446.4A priority patent/CN113993761A/zh
Publication of WO2021243710A1 publication Critical patent/WO2021243710A1/zh

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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W60/00—Drive control systems specially adapted for autonomous road vehicles
    • B60W60/001—Planning or execution of driving tasks
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
    • B60W2050/0001—Details of the control system
    • B60W2050/0019—Control system elements or transfer functions
    • B60W2050/0028—Mathematical models, e.g. for simulation

Definitions

  • the present invention relates to the field of intelligent transportation technology, in particular to an automatic driving method, device and intelligent transportation system based on an intelligent transportation system.
  • Autonomous vehicles mainly rely on the collaboration of artificial intelligence, visual computing, radar, monitoring devices, and global positioning systems to realize the automatic driving of the vehicle.
  • the data returned by the sensor is used to determine the driving area of the vehicle.
  • the content of environmental perception can be divided into two parts, namely road information and road condition information.
  • the target information can provide autonomous vehicles with targets in various areas around the vehicle, so that the autonomous vehicles can respond correctly, such as overtaking. , Decelerate, follow and other behaviors to achieve automatic control, and the road information provides the vehicle with a drivable road for path planning, and brings the vehicle to the designated area.
  • autonomous vehicles may not be able to make appropriate and accurate decisions because they cannot sense the surrounding conditions in time.
  • Intelligent Transportation System refers to the effective integration and application of advanced information technology, data communication transmission technology, electronic sensing technology, electronic control technology, and computer processing technology on a relatively complete infrastructure
  • ITS Intelligent Transportation System
  • the intelligent transportation system is of great significance in reducing the pressure of the transportation system, ensuring the safety of vehicles, and improving the efficiency of vehicle transportation. Therefore, there is an urgent need for a method of organically combining autonomous driving technology and intelligent transportation to better realize the safety and efficiency of automatic driving of vehicles.
  • the main purpose of the present invention is to provide an automatic driving method and device based on an intelligent transportation system, and an intelligent transportation system.
  • the road monitoring device and the on-board monitoring device can obtain road information, road condition information and vehicle information, and establish a road traffic model. Analyzed the implementation of the overall automatic driving plan for road vehicles, effectively avoiding the problems of incomplete information acquisition and conflicting decisions of various vehicles, and greatly improving the safety of vehicle driving and the efficiency of vehicle driving.
  • the present invention provides an automatic driving method based on an intelligent transportation system, the method including:
  • Intelligent transportation system obtains road information and road condition information
  • the system obtains information of vehicles driving on the road
  • the system establishes a road traffic model, and intelligently analyzes the overall automatic driving scheme of road vehicles;
  • the system transmits the plan to the autonomous driving vehicle, and the autonomous driving vehicle executes automatic driving according to the plan.
  • the way for the intelligent transportation system to obtain road condition information includes at least one of a road monitoring device, a vehicle-mounted monitoring device, or a high-altitude monitoring device.
  • the road information includes at least one of the number of lanes, lane width, radius of curvature, gradient, road material, entrances and exits, traffic lights, crossings, connecting roads, road environment, and road surface conditions.
  • the method further includes obtaining relevant information of the manually-driven vehicle on the road for predicting the expected driving behavior of the manually-driven vehicle.
  • the method further includes transmitting the overall automatic driving scheme of the road vehicle to the manual driving vehicle for prompting the driver of the driving situation of the automatic driving vehicle or guiding the driver to drive the vehicle.
  • the automatic driving method further includes: under the same road traffic model, evaluating and comparing different overall automatic driving schemes of road vehicles, and giving priority to providing the optimal overall automatic driving scheme of road vehicles.
  • the method further includes performing intelligent analysis again when the road traffic model changes to obtain a new overall automatic driving scheme for road vehicles, and transmitting it to the automatic driving vehicle for execution.
  • the method further includes selecting a suitable coverage area to establish a road traffic model according to the actual situation of the road information and the road condition information.
  • the method further includes converting and/or integrating information obtained from different data sources/data structures/data standards/data formats/data descriptions.
  • the establishment of a road traffic model is to select an existing road traffic model that is highly similar to the actual situation, and directly apply or modify the existing road traffic model according to actual information to obtain a road traffic model suitable for the actual situation.
  • Road traffic model is to select an existing road traffic model that is highly similar to the actual situation, and directly apply or modify the existing road traffic model according to actual information to obtain a road traffic model suitable for the actual situation.
  • the present invention also provides an automatic driving device for a vehicle, which includes a control component and a wireless transmission component; the wireless transmission component is used to wirelessly send the monitoring data of the on-board monitoring device and receive the automatic driving scheme; the control component is used to follow the The autonomous driving scheme controls the driving of the vehicle.
  • the present invention also provides an intelligent transportation system, which includes a road monitoring device, a signal transceiver and a server,
  • the road monitoring device is used to obtain road information and road condition information
  • the signal transceiver is used to send and receive signals
  • the server obtains road information, road condition information, and vehicle information on the road; builds a road traffic model through the obtained information, and intelligently analyzes the overall automatic driving scheme of road vehicles; transmits the scheme to the automatic driving through the signal transceiver
  • the vehicle, the self-driving vehicle executes self-driving according to the plan.
  • the present invention is an automatic driving method and device based on an intelligent transportation system, and an intelligent transportation system.
  • the automatic driving method includes acquiring road information, road condition information and vehicle information, establishing a road traffic model, and intelligently analyzing the execution of an overall automatic driving scheme for road vehicles.
  • the automatic driving device includes a control component and a wireless transmission component.
  • Intelligent transportation system includes: road monitoring device, signal transceiver and server.
  • the intelligent transportation system-based automatic driving method, device, and intelligent transportation system of the present invention obtain comprehensive road information, road condition information, and vehicle information through road monitoring devices, on-board monitoring devices, or other monitoring devices, and provide information to vehicles on the road.
  • Develop an overall autonomous driving plan which effectively avoids problems such as incomplete information acquisition and conflicting decisions of various vehicles, greatly improving the safety of vehicle driving and the efficiency of vehicle driving, and it is convenient to add manual driving cars to automatic driving at low cost. Function.
  • Fig. 1 is a method flowchart of an automatic driving method based on an intelligent transportation system according to a first embodiment of the present invention.
  • Fig. 2 is a schematic diagram of an automatic driving device for a vehicle according to a second embodiment of the present invention.
  • Fig. 3 is a schematic diagram of an intelligent transportation system according to a third embodiment of the present invention.
  • Fig. 1 is a method flowchart of an automatic driving method based on an intelligent transportation system according to a first embodiment of the present invention.
  • the automatic driving method based on the intelligent transportation system of the present invention includes:
  • Step 1 Intelligent transportation system obtains road information and road condition information.
  • Road information and road condition information are an important basis for establishing road traffic models, as well as an important basis for analyzing automated driving schemes. Therefore, obtaining complete and comprehensive road information and road condition information is the guarantee of the correctness and safety of the autonomous driving scheme.
  • Road information includes: number of lanes, lane width, radius of curvature, slope, road material, entrances and exits, traffic lights, crossings, connecting roads, road environment, road surface conditions (including friction, load-bearing, height limit, speed limit, etc.), and the road itself Relevant information.
  • Road condition information includes: navigation-related information such as traffic flow, vehicle location, vehicle speed, vehicle acceleration, vehicle targets, obstacle/pedestrian information, traffic signal information, road damage, traffic accidents, and other information related to road traffic conditions.
  • Intelligent transportation systems can obtain road information and road condition information through road monitoring devices and vehicle-mounted monitoring devices, and can also obtain road information and road condition information through other monitoring devices such as high-altitude monitoring devices.
  • Road monitoring devices can include cameras, radars, induction sensors, infrared detection devices, road or road pressure/optical/ultrasonic sensors and other devices. Multiple monitoring devices can be set up at appropriate locations on the road to obtain this information.
  • existing vehicles whether they are self-driving vehicles or manually driven vehicles, usually also include some on-board monitoring devices, such as on-board cameras, on-board radars, and speedometers. It is also possible to obtain road information and road condition information through high-altitude monitoring devices such as satellites/aircrafts/unmanned aerial vehicles/high-altitude balloons.
  • Step 2 The system obtains the information of vehicles driving on the road.
  • Vehicle information is also an important basis for establishing road traffic models and analyzing automated driving schemes.
  • Vehicle information may include: vehicle type, model, license plate number, vehicle length/width/height/quality/braking distance/tire condition/power condition/electricity/fuel quantity and other parameters, vehicle destination, number of passengers, and so on.
  • Ways to obtain vehicle information can include: receiving vehicle information proactively sent by the vehicle, the information that the vehicle replies after the system inquires the vehicle, the information obtained through the monitoring of road monitoring devices or other devices, and the information obtained by inquiring after identifying the vehicle model or license plate number, etc. .
  • the acquired information comes from different sources, there may be differences in the data structure/data standard/data format/data description of the acquired information.
  • High efficiency requires conversion and/or integration of information from different sources and types.
  • the conversion and/or integration of information and data can be achieved through methods such as video recognition technology, audio recognition technology, vehicle/license plate recognition technology, three-dimensional/four-dimensional modeling technology, virtual reality technology, augmented reality technology, and translation of different languages.
  • Step 3 The system establishes a road traffic model, and intelligently analyzes the overall automatic driving scheme of road vehicles.
  • the system uses the obtained information to build a road traffic model.
  • the road traffic model can include: roads, vehicles, obstacles, pedestrians, coverage, coverage time, weather conditions, special circumstances and other factors related to road traffic. Specifically, it can include: road width, traffic volume, vehicle position/model/speed/acceleration/braking distance, obstacle position/size, pedestrian speed/direction/purpose/possible behavior, etc., visibility/rain/snow /Weather conditions such as road icing, special circumstances such as day and night differences/traffic tide rules/traffic control or restricted traffic plan/vehicle weights/time priority of special tasks/time-limited arrivals and avoidance of other vehicles/out-of-road coverage, etc., and impacts Other contents of road traffic include various vehicles/objects/people outside the road.
  • the coverage of the road traffic model can be set according to the actual situation.
  • the coverage can be a short section of road, a complete road, several roads, within a region, within a city, and a wider range.
  • the overall automatic driving scheme of road vehicles can be calculated and analyzed.
  • Building a road traffic model can be to create a new road traffic model based on the acquired information, or to select an existing road traffic model that is highly similar to the actual situation based on the acquired information, and directly apply or modify the existing road based on the actual information. Traffic model to obtain a road traffic model suitable for the actual situation.
  • the similarity criterion can be set in advance, can also be obtained based on big data analysis/artificial intelligence deep learning, or it can be continuously optimized and perfected in the actual use process.
  • the automatic driving to be realized is an overall automatic driving scheme for vehicles on the road.
  • the overall calculation and analysis of the automatic driving scheme has great advantages.
  • each automatic driving vehicle on the road is executed in accordance with the overall automatic driving scheme.
  • the expected driving trajectory of these automatic driving vehicles is known, and only manual driving is required.
  • the trajectory of the vehicle is predicted.
  • the automatic driving method of the present invention is superior to the existing automatic driving method in terms of efficiency and safety.
  • the automatic driving method of the present invention for each automatic driving vehicle, will also plan an optimal driving route for each automatic driving vehicle according to the destination of the vehicle and the real-time road conditions.
  • the automatic driving method of the present invention also includes: under the same road traffic model, evaluating and comparing different overall automatic driving schemes of road vehicles, and giving priority to providing the optimal overall automatic driving scheme of road vehicles.
  • the specific methods include: under the same road traffic model, set the corresponding level/score for each vehicle in the overall automatic driving scheme of road vehicles according to the results of the target evaluation of safety/driving efficiency/comfort/energy consumption, and Set target weights for safety/driving efficiency/comfort/energy consumption and other goals, and set the vehicle weights of each vehicle according to the vehicle type/number of passengers/vehicle value of each vehicle, so as to be able to drive automatically according to the overall road vehicle
  • the level/score and target weight of the vehicle target evaluation in the scheme, as well as the vehicle weight of each vehicle calculate the comprehensive level/score of the overall automatic driving scheme of the road vehicle, so as to facilitate multiple roads under the same road traffic model Comprehensive comparison and ranking of the overall automatic driving scheme of the vehicle.
  • the optimal solution is to comprehensively evaluate the vehicle safety/driving efficiency/comfort/energy consumption, and combine the target weights and vehicle weights to obtain the highest comprehensive score.
  • various optimal solutions can be achieved. For example: For rigid goals that must be reached, such as ambulances/firetruck that need to rush to a designated location within 30 minutes, the level can be set as the highest priority. Therefore, if the goal is not achieved, the overall level/point value of the plan must be low A plan to achieve this goal.
  • Rigid goals can also include military affairs, police affairs, medical care, emergency response, security and other vital goals.
  • the level/score/weight setting and optimization can be based on professional/authoritative research results, or based on data obtained from big data analysis/information reorganization, data obtained through artificial intelligence deep learning, or It is new data obtained through statistical analysis in the process of using the original data, or a combination of the above methods.
  • the level/score/weight setting and optimization can be manual setting, artificial intelligence automatic setting, or semi-manual and semi-automatic setting.
  • the elements included in the safety goal may include factors such as possibility of accident/type of accident/number of possible injuries/number of possible deaths/possible economic loss/possible consequences/possible influence.
  • the elements included in the driving efficiency target may include factors such as driving time/driving speed/driving mileage/stroke completion degree/target achievement rate/timeliness evaluation.
  • the elements included in the comfort goal may include factors such as driving speed/driving acceleration/deceleration/number of sharp turns/number of sudden stops/degree of turbulence.
  • the elements included in the energy consumption target may include factors such as vehicle fuel consumption (power consumption)/total fuel consumption (power consumption)/fuel consumption per unit of travel (power consumption).
  • the weight of the vehicle can be set according to the type of vehicle, the crowd of passengers, and the items carried by the vehicle.
  • Vehicle types can include: passenger car/truck/large car/medium car/small car/special purpose vehicle/luxury car, etc.
  • Passengers can include: children, the elderly, pregnant women, motion sickness patients, patients, etc.
  • the items carried by the vehicle may include: dangerous goods, fragile goods, easily volatile goods, etc.
  • braking reaction time includes signal acquisition time/model establishment time/analysis time/decision time/program transmission time/program execution time , Comprehensively obtain the safe braking distance, and then compare the distance between the current vehicle and the preceding vehicle with the safe braking distance to obtain the corresponding level/point value.
  • the setting of the level/score and the weight coefficient can be adjusted according to different actual conditions.
  • the weight of special types of vehicles such as police cars performing tasks is usually higher than that of private cars, but the weight of private cars carrying critical patients May be higher than general special type vehicles.
  • the overall automatic driving scheme of road vehicles is derived through intelligent analysis of road traffic models.
  • the input elements are based on the actual information of the road traffic model, which can include: road information such as the number of lanes/lane width/radius of curvature/gradient/road material/ Entrance and exit/traffic lights/crossings/connecting roads/road environment/road surface conditions/friction/load bearing/height limit/speed limit, etc./climate conditions/visibility conditions and other information, road condition information such as traffic flow/vehicle location/vehicle speed/vehicle acceleration/ Vehicle target/navigation-related information/obstacle information/pedestrian information/traffic signal information/road damage/traffic accidents and other information, vehicle information such as vehicle type/model/license plate number/length/width/height/quality of the vehicle /Brake distance/tire condition/power condition/electricity/fuel quantity/other vehicle parameters/vehicle destination/number of passengers and other information, as well as other information related to the overall automatic driving scheme
  • the output elements of the overall automatic driving scheme of road vehicles can include: the driving route of each vehicle/trajectory/speed/acceleration/turning timing/turning amplitude/horn control/light control/distance control with other vehicles or pedestrians or obstacles (Including lateral and longitudinal distance)/Brake control/Reminders to the personnel in the vehicle/Reminders and driving suggestions for manual driving vehicles/Assisted driving control for autonomous vehicles, etc.
  • the method of reducing the calculation amount of analyzing the overall automatic driving scheme of road vehicles to improve real-time performance may be: according to the actual situation of road information and road condition information, selecting a suitable coverage area to establish a road traffic model.
  • the method to improve real-time performance can also be: limit the vehicles/obstacles in the road traffic model to a limited number of states.
  • the state of the vehicle can include: acceleration, deceleration, parking, turning left, turning right, changing lanes, overtaking, avoiding, etc. .
  • the amount of calculation can be reduced and the real-time performance can be improved.
  • Step 4 The system transmits the plan to the self-driving vehicle, and the self-driving vehicle executes automatic driving according to the plan.
  • the optimal overall automatic driving scheme of road vehicles is transmitted to all the automatic driving vehicles in the road traffic model, and each automatic driving vehicle executes the scheme according to their own driving trajectory/real-time Speed/real-time acceleration automatically travels.
  • the automatic driving method based on the intelligent transportation system of the present invention obtains comprehensive road information, road condition information, and vehicle information through road monitoring devices, on-board monitoring devices or other monitoring devices, and provides an overall automatic driving scheme for vehicles on the road. This effectively avoids problems such as incomplete information acquisition and conflicting decisions of various vehicles, and greatly improves the safety of vehicle driving and the efficiency of vehicle driving.
  • the automatic driving method based on the intelligent transportation system may also include obtaining the information of the artificially driven vehicles on the road. Relevant information is used to predict the expected behavior of a manually driven vehicle.
  • the expected driving behavior of a manually driven vehicle refers to the driving behavior that the manually driven vehicle may take, and the expected probability of the driving behavior.
  • Information related to a manually driven vehicle may include: vehicle status, driver, driving style, driving level, driving preferences, special habits, destinations, route planning and other information.
  • Obtaining the relevant information of a manually driven vehicle can be through self-built database to collect and store relevant information, or after recognizing the license plate number and/or face recognition of the driver, the traffic management department or other related organizations based on the license plate number and/or driver information
  • the acquisition of the database can also be obtained through relevant information analysis and other methods continuously acquired during the use of this method.
  • the automatic driving method based on the intelligent transportation system of the present invention may further include transmitting the overall automatic driving scheme of the road vehicle to the manual driving vehicle for prompting the driver of the driving situation of the automatic driving vehicle or guiding the driver to drive the vehicle.
  • the driver of a manually driven vehicle can know the expected driving trajectory of the autonomous vehicle on the road in advance, and can also obtain the guidance of the intelligent transportation system-based automatic driving method of the present invention to guide the driver to adopt the correct deceleration, Driving behaviors such as acceleration, merging, and parking can greatly reduce the probability of accidents, improve driving efficiency, and improve safety.
  • the automatic driving method based on the intelligent transportation system of the present invention can transmit the overall automatic driving scheme of the road vehicle to the auxiliary driving level vehicle, so that the auxiliary driving system of the vehicle can remind/recommend/warn/actively control the vehicle according to the scheme The trajectory of the vehicle.
  • the method also includes when the road traffic model changes, for example: a manually driven vehicle does not drive/suddenly brake/accelerate as instructed, or a road vehicle has a sudden accident/failure, or a new vehicle/pedestrian/obstacle is added, or When the road environment/climate environment changes, the road traffic model is updated according to the information obtained in real time, and the intelligent analysis is performed again to obtain the new road vehicle overall automatic driving plan, and transmit it to the automatic driving vehicle for execution.
  • the road traffic model changes for example: a manually driven vehicle does not drive/suddenly brake/accelerate as instructed, or a road vehicle has a sudden accident/failure, or a new vehicle/pedestrian/obstacle is added, or
  • the road traffic model is updated according to the information obtained in real time, and the intelligent analysis is performed again to obtain the new road vehicle overall automatic driving plan, and transmit it to the automatic driving vehicle for execution.
  • the automatic driving method based on the intelligent transportation system of the present invention can also be applied to non-road areas, such as grasslands, deserts, wastelands and the like. Obtain terrain and ground information, vehicle information, and other vehicle/obstacle/pedestrian or animal information on the ground through on-board monitoring devices and high-altitude monitoring equipment, establish a model with a certain coverage area, and obtain an autonomous driving solution through intelligent analysis. Compared with roads, off-road areas, vehicles no longer drive along the road, and the possible range of vehicles traveling is expanded. At the same time, because the density of vehicles in off-road areas is much smaller than that of roads, the number of vehicles in the scheme is changed. few.
  • the automatic driving method based on the intelligent transportation system of the present invention can be optimized according to the characteristics of the non-road area, and the efficiency and safety of the non-road area can be improved.
  • Fig. 2 is a schematic diagram of an automatic driving device for a vehicle according to a second embodiment of the present invention.
  • the automatic driving device includes a control component 21 and a wireless transmission component 22; the wireless transmission component 22 is used to wirelessly send the monitoring data of the on-board monitoring device and receive the automatic driving plan; the control component 21 is used to control according to the automatic driving plan The vehicle is moving.
  • the control component 21 is connected to the control system of the vehicle, and can transmit the overall automatic driving plan of the road vehicle received by the wireless transmission component 22 to the control component 21.
  • the control component 21 transmits the overall automatic driving scheme of the road vehicle to the control system of the vehicle, and the control system of the vehicle controls the vehicle to drive according to the driving trajectory of the vehicle in the overall automatic driving scheme of the road vehicle. It may also be that the control component 21 includes one or more control devices for controlling the vehicle to drive in accordance with the overall automatic driving scheme of the road vehicle. After the control component 21 receives the overall automatic driving scheme of the road vehicle received by the wireless transmission component 22, Each control device controls the vehicle to drive in accordance with the vehicle travel trajectory of the overall automatic driving scheme of the road vehicle. In this embodiment, different vehicles require different control components.
  • a car with a high degree of intelligence may have its own control system that can completely control the vehicle to drive in accordance with the overall automatic driving scheme of the road vehicle or only need a control device to add some control functions to the vehicle's own control system.
  • a traditional car with a low degree of intelligence may be a vehicle Its own degree of automation is low, and a large number of control devices are needed to adapt to unmanned automatic driving control, such as steering wheel/throttle/brake/transmission/handbrake/light/horn/vehicle condition monitoring and other multi-component automatic control.
  • Different components have different automatic control devices, and different levels of automatic driving have different control devices.
  • the control devices required for unmanned driving require the highest and most complete functions, while the requirements and functions of the control devices required for assisted driving are lower than those of none.
  • the control device required for human driving may be a vehicle Its own degree of automation is low, and a large number of control devices are needed to adapt to unmanned automatic driving control, such as steering wheel/throttle/brake/transmission
  • the automatic driving device for vehicles of the present invention it is convenient to add automatic driving functions to manually driven vehicles. As the automatic driving information acquisition and analysis results do not need to be completed by the vehicle itself, the vehicle only needs to accept the automatic driving scheme and follow The automatic driving scheme can be executed to realize the automatic driving function. Therefore, the automatic driving device of the vehicle of the present invention can add the automatic driving function to the manual driving vehicle at low cost, without adding complex hardware equipment, and only needs to be able to receive and follow the automatic driving The program can be executed.
  • Fig. 3 is a schematic diagram of an intelligent transportation system according to a third embodiment of the present invention.
  • the intelligent transportation system includes: a road monitoring device 31, a signal transceiver 32, and a server 33.
  • the road monitoring device 31 is used to obtain road information and road condition information, and may include; may include a camera, a radar, an induction sensor, and so on.
  • Intelligent transportation systems can also include high-altitude monitoring devices such as satellites, airplanes, unmanned aerial vehicles, and high-altitude balloons.
  • the signal transceiver 32 is used to send and receive signals.
  • the information obtained by the road monitoring device 31 can be transmitted to the server 33, and it can also receive information sent by the vehicle, such as on-board monitoring information, and transmit it to the server 33. It can also transmit information for the server 33 to vehicles on the road, such as the overall automatic driving plan of road vehicles, etc. .
  • the server 33 obtains road information, road condition information and vehicle information on the road; builds a road traffic model based on the obtained information, and intelligently analyzes the overall automatic driving scheme of road vehicles; transmits the scheme to the self-driving vehicle through the signal transceiver 32,
  • the autonomous driving vehicle executes autonomous driving according to the plan.
  • the server 33 can also obtain information from other means such as high-altitude monitoring devices, and can also connect to the Internet to obtain information through a database of a traffic management department or other related organizations.
  • the server 33 may be a server of the intelligent transportation system itself, a cloud server, or an MEC server, which uses edge computing and a 5G high-speed network to implement large-scale real-time computing.
  • the intelligent transportation system of the present invention is composed of an automatic driving method based on the intelligent transportation system of the present invention, and the structural features correspond to each other. You can refer to the description of the aforementioned automatic driving method based on the intelligent transportation system, here No longer.
  • the present invention is an intelligent transportation system-based automatic driving method, device, and intelligent transportation system.
  • the automatic driving method includes acquiring road information, road condition information, and vehicle information, establishing a road traffic model, and intelligently analyzing the overall road vehicle Autonomous driving plan execution.
  • the automatic driving device includes a control component and a wireless transmission component.
  • Intelligent transportation system includes: road monitoring device, signal transceiver and server.
  • the intelligent transportation system-based automatic driving method, device, and intelligent transportation system of the present invention obtain comprehensive road information, road condition information, and vehicle information through road monitoring devices, on-board monitoring devices, or other monitoring devices, and provide information to vehicles on the road.
  • Develop an overall autonomous driving plan which effectively avoids problems such as incomplete information acquisition and conflicting decisions of various vehicles, greatly improving the safety of vehicle driving and the efficiency of vehicle driving, and it is convenient to add manual driving cars to automatic driving at low cost. Function.

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  • Engineering & Computer Science (AREA)
  • Automation & Control Theory (AREA)
  • Human Computer Interaction (AREA)
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  • Mechanical Engineering (AREA)
  • Traffic Control Systems (AREA)

Abstract

一种基于智能交通***的自动驾驶方法、装置和智能交通***，自动驾驶方法包括获取道路信息、路况信息及车辆信息，建立道路交通模型，智能分析出道路车辆整体自动驾驶方案执行。自动驾驶装置包括控制组件（21）和无线传输组件（22）。智能交通***包括：道路监测装置（31）、信号收发器（32）和服务器（33）。一种基于智能交通***的自动驾驶方法、装置和智能交通***，通过道路监测装置及车载监测装置或其他监测装置全面的获取道路信息、路况信息及车辆信息，对道路上的车辆给出整体自动驾驶方案，从而有效避免了信息获取不全面，各车辆决策相互冲突等问题，大大提高了车辆行驶的安全性以及车辆行驶的效率，并且可以方便低成本的将人工驾驶汽车加入自动驾驶的功能。

Description

一种基于智能交通***的自动驾驶方法、装置和智能交通*** 技术领域
本发明涉及智能交通技术领域，特别是涉及一种基于智能交通***的自动驾驶方法、装置和智能交通***。
背景技术
随着科技的不断发展，自动驾驶车辆已经出现，极大地促进了智能交通的发展。自动驾驶车辆主要是依靠人工智能、视觉计算、雷达、监测装置和全球定位***的协同合作来实现车辆的自动行驶的，通过传感器返回的数据确定车辆的可行驶区域。其中，环境感知的内容可以分为两大部分，分别为道路信息和路况信息，其中目标信息可以为自动驾驶车辆提供本车周围各个区域的目标，让自动驾驶车辆做出正确的反应，如超车、减速、跟随等行为，实现自动控制，而道路信息为车辆提供了可行驶道路以进行路径规划，将车辆带到指定区域位置。但是，在存在视野或感应盲区的地段，自动驾驶车辆很可能会因为无法及时感应到周边状况而无法做出合适、准确的决策。
智能交通***(Intelligent Transportation System，ITS),指的是在较完善的基础设施之上将先进的信息技术、数据通讯传输技术、电子传感技术、电子控制技术以及计算机处理技术等有效地集成运用于整个交通运输管理体系，从而建立起一种在大范围、全方位发挥作用的实时、准确、高效的综合管理***。智能交通***作 为未来交通***的发展方向，对减轻交通***压力、保证车辆行驶安全性、提高车辆运输效率等方面具有重要意义。因此亟待一种将自动驾驶技术与智能交通有机结合的方法，更好地实现车辆自动驾驶的安全性及高效性。
发明内容
本发明的主要目的是：提供一种基于智能交通***的自动驾驶方法、装置和智能交通***，通过道路监测装置及车载监测装置，获取道路信息、路况信息及车辆信息，建立道路交通模型，智能分析出道路车辆整体自动驾驶方案执行，有效避免了信息获取不全面，各车辆决策相互冲突等问题，大大提高了车辆行驶的安全性以及车辆行驶的效率。
为实现上述目的，本发明提供了一种基于智能交通***的自动驾驶方法，所述方法包括：
智能交通***获取道路信息和路况信息；
所述***获取道路上行驶的车辆信息；
所述***建立道路交通模型，智能分析出道路车辆整体自动驾驶方案；
所述***将所述方案传输至自动驾驶车辆，自动驾驶车辆按照所述方案执行自动驾驶。
如上所述的自动驾驶方法，所述智能交通***获取路况信息的途径包括：道路监测装置、车载监测装置或高空监测装置中的至少一种途径。
如上所述的自动驾驶方法，所述道路信息包括：车道数、车道宽度、曲率半径、坡度、道路材质、出入口、红绿灯、道口、连接道路、道路环境、路面情况中的至少一种信息。
如上所述的自动驾驶方法，所述方法还包括获取道路上的人工驾驶车辆的相关信息，用于预测人工驾驶车辆的行驶期望行为。
如上所述的自动驾驶方法，所述方法还包括将所述道路车辆整体自动驾驶方案传输至人工驾驶车辆，用于提示司机自动驾驶车辆的行驶情况或引导司机驾驶车辆。
如上所述的自动驾驶方法，所述自动驾驶方法还包括：在相同的道路交通模型下，对不同的道路车辆整体自动驾驶方案进行评估和比较，优先提供最优的道路车辆整体自动驾驶方案。
如上所述的自动驾驶方法，所述方法还包括当道路交通模型发生变化时，重新进行智能分析，得到新的道路车辆整体自动驾驶方案，并传输至自动驾驶车辆执行。
如上所述的自动驾驶方法，所述方法还包括根据道路信息及路况信息的实际情况，选择合适的覆盖范围建立道路交通模型。
如上所述的自动驾驶方法，所述方法还包括将获取的不同数据来源/数据结构/数据标准/数据格式/数据描述的信息进行转换和/或整合。
如上所述的自动驾驶方法，所述建立道路交通模型是通过选择与实际情况相似度高的已有道路交通模型，直接应用或根据实际信息相应修改所述已有道路交通模型以得到适合实际情况的道路交通模型。
本发明还提供一种车辆的自动驾驶装置，包括控制组件和无线传输组件；所述无线传输组件用于无线发送车载监测装置的监测数据和接收自动驾驶方案；所述控制组件用于按照所述自动驾驶方案控制车辆行驶。
本发明还提供一种智能交通***，所述***包括：道路监测装置、信号收发器和服务器，
所述道路监测装置用于获取道路信息和路况信息；
所述信号收发器用于收发信号；
所述服务器获取道路信息和路况信息及道路上行驶的车辆信息；通过获取的信息建立道路交通模型，智能分析出道路车辆整体自动驾驶方案；将所述方案通过所述信号收发器传输至自动驾驶车辆，自动驾驶车辆按照所述方案执行自动驾驶。
本发明的一种基于智能交通***的自动驾驶方法、装置和智能交通***，自动驾驶方法包括获取道路信息、路况信息及车辆信息，建立道路交通模型，智能分析出道路车辆整体自动驾驶方案执行。自动驾驶装置包括控制组件和无线传输组件。智能交通***包括：道路监测装置、信号收发器和服务器。本发明的一种基于智能交通***的自动驾驶方法、装置和智能交通***，通过道路监测装置及 车载监测装置或其他监测装置全面的获取道路信息、路况信息及车辆信息，对道路上的车辆给出整体自动驾驶方案，从而有效避免了信息获取不全面，各车辆决策相互冲突等问题，大大提高了车辆行驶的安全性以及车辆行驶的效率，并且可以方便低成本的将人工驾驶汽车加入自动驾驶的功能。
附图说明
图1为本发明第一实施例一种基于智能交通***的自动驾驶方法的方法流程图。
图2为本发明第二实施例一种车辆的自动驾驶装置的示意图。
图3为本发明第三实施例一种智能交通***的示意图。
具体实施方式
为进一步阐述本发明达成预定目的所采取的技术手段及功效，以下结合附图及实施例，对本发明的具体实施方式，详细说明如下。
本发明第一实施例参阅图1。图1是本发明第一实施例一种基于智能交通***的自动驾驶方法的方法流程图。如图所示，本发明的基于智能交通***的自动驾驶方法包括：
步骤1：智能交通***获取道路信息和路况信息。
道路信息和路况信息是建立道路交通模型的重要依据，也是分析得出自动驾驶方案的重要依据。因而，获取完整全面的道路信息和路况信息是自动驾驶方案正确性和安全性的保障。道路信息包括：车道数、车道宽度、曲率半径、坡度、道路材质、出入口、红绿灯、道口、连接道路、道路环境、路面情况(包括摩擦力、承重、限高、限速等)等与道路本身有关的信息。路况信息包括：车流量、车辆位置、车辆速度、车辆加速度、车辆目标等与导航有关的信息、障碍物/行人信息、交通信号灯信息、路面破损情况、交通意外等与道路交通状况有关的信息。
智能交通***可以通过道路监测装置和车载监测装置获取道路信息和路况信息，也可以通过其他监测装置如高空监测装置等获取道路信息和路况信息。道路监测装置可以包括摄像头、雷达、感应传感器、红外探测装置、道路或路面的压力/光学/超声波传感器等多种装置，可以在道路的合适位置设置多个监测装置用于获取这些信息。此外，现有的车辆，无论是自动驾驶车辆还是人工驾驶车辆，通常也都会包括一些车载监测装置，如车载摄像头、车载雷达、测速仪等等。还可以通过高空监测装置如卫星/飞机/无人机/高空气球等获取道路信息和路况信息。也可以通过监测车辆的物联网硬件/射频卡/ECT设备等获取相关信息。最后，还可以通过监测道路周边可能影响路况的范围如路边行人/动物/车辆/建筑物/车站等来获取道路状况的相关信息。通过多种方式获取信息的好处是使信息更加全面，避免了单一信息来源导致的缺失。例如：现有自动驾驶技术通常是依赖车辆自身的监控装置来获取路况信息，容易被遮挡导致一些信息获取不到。
步骤2：***获取道路上行驶的车辆信息。
车辆信息也是建立道路交通模型、分析得出自动驾驶方案的重要依据。车辆信息可以包括：车辆类型、型号、车牌号、车辆的长度/宽度/高度/质量/制动距离/轮胎情况/动力情况/电量/油量等参数、车辆目的地、乘坐人数等等。
获取车辆信息的途径可以包括：接收车辆主动发出的车辆信息、***向车辆询问后车辆回复的信息、通过道路监测装置或其他装置监测得出、通过识别出车辆型号或车牌号后查询得到等等。
在本发明中，由于获取的信息来自不同的来源，因而可能存在获取的信息的数据结构/数据标准/数据格式/数据描述等存在差异的状况，在此状况下，为了信息使用的流畅化及高效化，需要将不同来源、类型信息的进行转换和/或整合。可以通过视频识别技术、音频识别技术、车辆/车牌识别技术、三维/四维建模技术、虚拟现实技术、增强现实技术、不同语言的翻译等方法实现信息数据的转换和/或整合。
步骤3：***建立道路交通模型，智能分析出道路车辆整体自动驾驶方案。
***用获得的信息建立道路交通模型，道路交通模型可以包括：道路、车辆、障碍物、行人、覆盖范围、覆盖时间、天气状况、特殊情况及其他与道路交通相关的因素。具体可以包括：道路宽度、车流量、车辆位置/型号/速度/加速度/制动距离，障碍物位置/大小、行人的速度/方向/目的性/可能的行为等、能见度/下雨/下雪/路面结冰等天气情况、特殊情况如白天夜晚差异/交通潮汐规律/交通管 制或限行计划/车辆权重/特殊任务的时间优先/限时到达以及其他车辆的避让/道路外覆盖范围等、以及影响道路交通的其他内容包括道路外的各种车/物/人等。道路交通模型的覆盖范围可以根据实际情况设置，覆盖范围可以是一小段道路、一条完整的道路、几条道路、一个区域范围内、一个城市范围内以及更广阔的范围。***获取的信息越丰富、越真实，道路交通模型包含的参数越多，所建立的道路交通模型也就贴近实际，依据该模型所分析得出的道路车辆整体自动驾驶方案就越完善。建立模型之后，在模型范围内依据真实完整的信息包括：空间信息/时间信息/对象信息/其他信息如交通管制或限行或红绿灯等信息，通过计算分析得出道路车辆整体自动驾驶方案。
建立道路交通模型可以是通过获取的信息新建道路交通模型，也可以是根据获取的信息通过选择与实际情况相似度高的已有道路交通模型，直接应用或根据实际信息相应修改所述已有道路交通模型以得到适合实际情况的道路交通模型。相似度的判定标准可以是事先设定的，也可以根据大数据分析/人工智能深度学习得到的，还可以是在实际使用过程中不断优化与完善的。
在本发明中，要实现的自动驾驶是针对道路上车辆的整体自动驾驶方案。对比现有的只针对单辆车的自动驾驶，从整体上计算分析自动驾驶方案具有很大优势。首先，针对道路车辆整体的自动驾驶方案，道路上的每辆自动驾驶车辆都按照该整体自动驾驶方案执行，那么，相当于这些自动驾驶车辆的预期行驶轨迹是已知的，只需要对人工驾驶车辆的行驶轨迹进行预测。而单辆车的自动驾驶方案，需要对每辆车的行驶轨迹进行预测。此外，针对道路车辆整体 的自动驾驶方案，在计算分析规划方案时，是从道路车辆的整体来考虑的，避免方案中的车辆之间的行驶轨迹发生冲突，并且使道路车辆整体的安全性和效率最高。而单辆车的自动驾驶方案只考虑本车的行驶效率和安全性，不同车辆之间的自动驾驶方案就有可能相互影响，降低行驶效率及安全性。因而本发明的自动驾驶方法在效率及安全性上均优于现有的自动驾驶方法。同时，本发明的自动驾驶方法，对于各自动驾驶车辆，也会根据车辆目的地及实时路况，为各自动驾驶车辆规划最优的行驶路线。
在获取信息并建立道路交通模型后，通过分析计算得出的道路车辆整体自动驾驶方案可能有多个，不同的道路车辆整体自动驾驶方案可能各有优势。本发明的自动驾驶方法还包括：在相同的道路交通模型下，对不同的道路车辆整体自动驾驶方案进行评估和比较，优先提供最优的道路车辆整体自动驾驶方案。
具体方法包括：在相同的道路交通模型下，对道路车辆整体自动驾驶方案中各车辆根据安全性/行车效率/舒适性/能耗等目标评估的结果，设定对应的级别/分值，并且设定安全性/行车效率/舒适性/能耗等目标的目标权重，并根据各车辆的车辆类型/乘坐人数/车辆价值等方面设定各车辆的车辆权重，从而能够根据道路车辆整体自动驾驶方案中车辆目标评估的级别/分值和目标权重，以及各车辆的车辆权重，计算出该道路车辆整体自动驾驶方案的综合级别/分值，以便于在相同的道路交通模型下对多个道路车辆整体自动驾驶方案进行综合比较及排序。
最优方案是将车辆安全性/行车效率/舒适性/能耗等方面进行综合评估，并结合各目标权重和车辆权重所得到的综合分数最高的方 案。通过对不同的目标设定不同的级别/分值/权重，可以实现各种最优方案。例如：对于必须达到的刚性目标如救护车/救火车30分钟内需赶到指定地点，可以将其级别设为最优先级，因而如果该目标未能达成，则方案的综合级别/分值必定低于该目标达成的方案。刚性目标还可以包括：军务、警务、医疗、应急、安全和其他至关重要的目标。还可以将车辆/行人/货物，按照车辆类型、乘客类型、货物类型、目的地、距离、路线/路线模型等因素进行分类/分组，然后通过分类/分组来设置它们的权重。级别/分值/权重的设定和优化可以基于具有专业性/权威性的研究结果，也可以基于大数据分析/信息重整得到的数据，可以是通过人工智能深度学习得到的数据，还可以是在原有数据使用过程中通过统计分析得出的新的数据，或上述方法的组合。级别/分值/权重的设定和优化可以是人工设置，也可以是人工智能自动设置，还可以是半人工半自动设置。
在本发明中，安全性目标所包含的要素可以包括：事故可能性/事故类型/可能受伤人数/可能死亡人数/可能经济损失/可能后果/可能影响等因素。行车效率目标所包含的要素可以包括：行驶时间/行驶速度/行驶里程/行程完成度/目标达成率/及时性评价等因素。舒适性目标所包含的要素可以包括：行驶速度/行驶加减速/急转弯次数/急刹车次数/颠簸程度等因素。能耗目标所包含的要素可以包括：车辆油耗(电量消耗)/总油耗(电量消耗)/单位路程油耗(电量消耗)等因素。车辆权重可以根据车辆类型、乘车人群、车辆运载物品等方面进行设定。车辆类型可以包括：客车/货车/大型车/中型车/小型车/特殊用途车辆/豪华车等。乘车人群可以包括：儿童、老人、孕妇、晕车患者、病人等。车辆运载物品可以包括：危险品、易碎品、易挥发性物品等。
例如：考虑车辆制动及动力情况，制动又包括路面与轮胎、制动反应时间包括获取信号的时间/模型建立的时间/分析的时间/决策的时间/方案传输的时间/方案执行的时间，综合得出安全制动距离，再将当前车辆与前车的距离与安全制动距离比较，得出相应的级别/分值。
级别/分值和权重系数的设定，可以根据不同的实际情况进行调整，例如，特殊类型车辆如执行任务的警车的权重通常是高于私家车的，但载有危急病人的私家车的权重可能会高于一般特殊类型车辆。又比如：正常天气情况下，车辆与前车间距20米不影响安全性方面的级别/分值，但雨天车辆与前车间距20米可能会导致安全性方面的级别/分值降低。
道路车辆整体自动驾驶方案是通过对道路交通模型智能分析得出的，输入要素是基于建立道路交通模型的实际信息，可以包括：道路信息如车道数/车道宽度/曲率半径/坡度/道路材质/出入口/红绿灯/道口/连接道路/道路环境/路面情况/摩擦力/承重/限高/限速等/气候状况/能见度状况等信息、路况信息如车流量/车辆位置/车辆速度/车辆加速度/车辆目标/与导航有关的信息/障碍物信息/行人信息/交通信号灯信息/路面破损情况/交通意外情况等信息、车辆信息如车辆类型/型号/车牌号/车辆的长度/宽度/高度/质量/制动距离/轮胎情况/动力情况/电量/油量/车辆其他参数/车辆目的地/乘坐人数等信息，以及其他与道路车辆整体自动驾驶方案有关的信息。道路车辆整体自动驾驶方案的输出要素可以包括：各车辆的行驶路线/行驶轨迹/速度/加速度/转向的时机/转向幅度/喇叭控制/车灯控制/与其他车辆或行人或障碍物的距离控制(包括横向及纵向距离)/制 动控制/对车内人员的提示/对人工驾驶车辆的提示及行驶建议/对自动驾驶车辆的辅助驾驶控制等等。
通过道路交通模型智能分析出道路车辆整体自动驾驶方案是一个复杂的过程，包含大量的运算量，但是自动驾驶又是一个对实时性要求很高的行为，所以又要求分析道路车辆整体自动驾驶方案有限的短时间内完成，这就要求本发明的自动驾驶方法需要在实时性与方案最优解方面进行平衡。可以在上述道路车辆整体自动驾驶方案的评估与比较中，加入实时性的评价，对于某个道路车辆整体自动驾驶方案，既要考虑安全性/行车效率/舒适性等方面的评价，也要考虑实时性方面的评价，因为过低的实时性必然会对自动驾驶的行车效率产生影响，同时也很可能会对安全性产生影响，从而降低方案的综合评价。
在本发明中，降低分析道路车辆整体自动驾驶方案的运算量从而提高实时性的方法可以是：根据道路信息及路况信息的实际情况，选择合适的覆盖范围建立道路交通模型。通过适当缩小道路交通模型的大小，从而降低模型的路线长度，减少模型中的车辆数量，障碍物的数量，可以让运算量大幅下降，从而大大提高方案的实时性。还可以将在相同或相似的道路交通模型下，车辆根据安全性/行车效率/舒适性等方面评估的结果所设定对应的级别/分值/权重，进行存储/记录，以便在相同/相似的条件下能够直接使用或借鉴相关设定，也可以对于相似或部分相似的车辆进行集中处理，整体打包计算，降低运算量，提高实时性。
提高实时性的方法还可以是：将道路交通模型中的车辆/障碍物限定为有限个状态，例如车辆状态可以包括：加速、减速、停车、 左转、右转、换道、超车、避让等。通过限定道路交通模型中每个元素的有限状态，可以减少运算量，提高实时性。
步骤4：***将所述方案传输至自动驾驶车辆，自动驾驶车辆按照所述方案执行自动驾驶。
通过道路交通模型智能分析并评估出最优的道路车辆整体自动驾驶方案后，将该方案传输至道路交通模型中所有的自动驾驶车辆，各自动驾驶车辆执行该方案，按照各自的行驶轨迹/实时速度/实时加速度自动行驶。
本发明的一种基于智能交通***的自动驾驶方法，通过道路监测装置及车载监测装置或其他监测装置全面的获取道路信息、路况信息及车辆信息，对道路上的车辆给出整体自动驾驶方案，从而有效避免了信息获取不全面，各车辆决策相互冲突等问题，大大提高了车辆行驶的安全性以及车辆行驶的效率。
在本发明中，为了进一步提高道路车辆整体自动驾驶方案的安全性/效率/舒适性，并且降低运算量提升实时性，基于智能交通***的自动驾驶方法还可以包括获取道路上的人工驾驶车辆的相关信息，用于预测人工驾驶车辆的行驶期望行为。人工驾驶车辆的行驶期望行为是指人工驾驶车辆可能会采取的行驶行为，以及行驶行为的期望概率。人工驾驶车辆的相关信息可以包括：车辆状况、驾驶人、驾驶风格、驾驶水平、驾驶偏好、特殊习惯、目的地、线路规划等信息。例如：如果人工驾驶车辆经常急刹车，则道路车辆整体自动驾驶方案时需要为该车保持更多的安全驾驶距离，等等。获取人工驾驶车辆的相关信息可以是通过自建数据库收集存储相关信息， 或者识别车牌号和/或人脸识别驾驶者后，根据车牌号和/或驾驶者的信息由交通管理部门或其他相关组织的数据库的获取，还可以通过本方法的使用过程中不断获取的相关信息分析等方法得到。
本发明的一种基于智能交通***的自动驾驶方法，还可以包括将所述道路车辆整体自动驾驶方案传输至人工驾驶车辆，用于提示司机自动驾驶车辆的行驶情况或引导司机驾驶车辆。人工驾驶车辆的驾驶员可以提前获知道路上的自动驾驶车辆的预期行驶轨迹，还可以获得本发明的一种基于智能交通***的自动驾驶方法的引导，引导司机在该状况下采用正确的减速、加速、并线、停车等驾驶行为，可以大大降低事故发生的概率，提高行驶效率，提高安全性。
在本发明中，如果自动驾驶车辆还打不到主动驾驶车辆的自动驾驶级别，而只是辅助驾驶级别。本发明的一种基于智能交通***的自动驾驶方法可以将所述道路车辆整体自动驾驶方案传输至辅助驾驶级别的车辆，使车辆的辅助驾驶***可以提醒/建议/报警/主动控制车辆按照该方案的车辆轨迹行驶。
所述方法还包括当道路交通模型发生变化时，例如：人工驾驶车辆未按指示驾驶/急刹车/急加速，或道路车辆突然发生事故/故障，或加入新的车辆/行人/障碍物、或道路环境/气候环境发生变化等情况时，按照实时获取的信息更新道路交通模型，重新进行智能分析，得到新的道路车辆整体自动驾驶方案，并传输至自动驾驶车辆执行。
本发明的基于智能交通***的自动驾驶方法还可以适用于非道路区域，如草原、沙漠、荒地等。通过车载监测装置和高空监测设备等，获取地形地面信息、车辆信息及地面上其他车辆/障碍物/行 人或动物的信息，建立一定覆盖范围的模型，并通过智能分析得到自动驾驶方案。非道路的区域相比于道路来说，车辆不再沿道路行驶，车辆行驶可能的范围扩大了，同时，由于非道路区域的车辆密度远小于道路的车辆密度，从而使方案中的车辆数量变少。本发明的基于智能交通***的自动驾驶方法可以针对非道路区域的特点进行相应的优化，提高非道路区域的效率及安全性。
本发明第二实施例参阅图2。图2为本发明第二实施例一种车辆的自动驾驶装置的示意图。如图所示，自动驾驶装置包括控制组件21和无线传输组件22；无线传输组件22用于无线发送车载监测装置的监测数据和接收自动驾驶方案；控制组件21用于按照所述自动驾驶方案控制车辆行驶。控制组件21与车辆的控制***连接，可将无线传输组件22接收到的道路车辆整体自动驾驶方案传输至控制组件21。控制组件21将道路车辆整体自动驾驶方案传输至车辆的控制***，由车辆的控制***控制车辆按照道路车辆整体自动驾驶方案的本车的行驶轨迹行驶。也可以是控制组件21包括一个或多个用于控制车辆按照所述道路车辆整体自动驾驶方案行驶的控制装置，控制组件21收到无线传输组件22接收到的道路车辆整体自动驾驶方案后，由各控制装置控制车辆按照所述道路车辆整体自动驾驶方案的车辆行驶轨迹行驶。在本实施例中，不同车辆所需控制组件不同。例如：智能化程度高的汽车可能自身的控制***可以完全控制车辆按照道路车辆整体自动驾驶方案行驶或只需要控制装置为车辆自身的控制***增加部分控制功能，智能化程度低的传统汽车可能车辆自身的自动化程度低，需要大量控制装置使其改造为适应无人自动驾驶控制，如方向盘/油门/刹车/变速器/手刹/灯光/喇叭/车辆状况监控等多部件的自动控制。不同部件的自动控制装置不同，不 同级别的自动驾驶，其控制装置也不同，如无人驾驶所需控制装置要求最高功能最全，而辅助驾驶所需的控制装置的要求和功能均低于无人驾驶所需的控制装置。
通过本发明的车辆的自动驾驶装置，可以方便的为人工驾驶车辆添加自动驾驶功能，由于自动驾驶的信息获取和分析得出方案都无需有车辆自身完成，车辆只需要接受自动驾驶方案，并且按照自动驾驶方案执行即可实现自动驾驶功能，所以，通过本发明的车辆的自动驾驶装置可以低成本的为人工驾驶车辆添加自动驾驶功能，无需增加复杂的硬件设备，只需要能够接收并按照自动驾驶方案执行即可。
本发明第三实施例参阅图3。图3为本发明第三实施例一种智能交通***的示意图。如图所示，智能交通***包括：道路监测装置31、信号收发器32和服务器33。
道路监测装置31用于获取道路信息和路况信息，可以包括；可以包括摄像头、雷达、感应传感器等等。智能交通***还可以包括：卫星、飞机、无人机、高空气球等高空监测装置。
所述信号收发器32用于收发信号。可以将道路监测装置31获取的信息传输至服务器33，也可以接收车辆发出的信息如车载监测信息传输至服务器33，还可以为服务器33向道路上的车辆传输信息如道路车辆整体自动驾驶方案等。
服务器33获取道路信息和路况信息及道路上行驶的车辆信息；通过获取的信息建立道路交通模型，智能分析出道路车辆整体自动 驾驶方案；将所述方案通过信号收发器32传输至自动驾驶车辆，自动驾驶车辆按照所述方案执行自动驾驶。
服务器33还可以从高空监测装置等其他途径获取信息，也可以连接互联网通过交通管理部门或其他相关组织的数据库等获取信息。服务器33既可以是智能交通***自身的服务器，也可以是云服务器，也可以是MEC服务器，利用边缘计算及5G高速网络实现大运算量实时计算。
本发明的一种智能交通***是采用本发明的一种基于智能交通***的自动驾驶方法构成的，结构特征一一对应，可以参照前述一种基于智能交通***的自动驾驶方法的说明，在此不再赘述。
综上所述，本发明的一种基于智能交通***的自动驾驶方法、装置和智能交通***，自动驾驶方法包括获取道路信息、路况信息及车辆信息，建立道路交通模型，智能分析出道路车辆整体自动驾驶方案执行。自动驾驶装置包括控制组件和无线传输组件。智能交通***包括：道路监测装置、信号收发器和服务器。本发明的一种基于智能交通***的自动驾驶方法、装置和智能交通***，通过道路监测装置及车载监测装置或其他监测装置全面的获取道路信息、路况信息及车辆信息，对道路上的车辆给出整体自动驾驶方案，从而有效避免了信息获取不全面，各车辆决策相互冲突等问题，大大提高了车辆行驶的安全性以及车辆行驶的效率，并且可以方便低成本的将人工驾驶汽车加入自动驾驶的功能。
以上所述的具体实施方式，对本发明的目的、技术方案和有益效果进行了进一步详细说明，所应理解的是，以上所述仅为本发明 的具体实施方式而已，并不用于限定本发明的保护范围，凡在本发明的精神和原则之内，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。

Claims (12)

  1. 一种基于智能交通***的自动驾驶方法，其特征在于，所述方法包括：
    智能交通***获取道路信息和路况信息；
    所述***获取道路上行驶的车辆信息；
    所述***建立道路交通模型，智能分析出道路车辆整体自动驾驶方案；
    所述***将所述方案传输至自动驾驶车辆，自动驾驶车辆按照所述方案执行自动驾驶。
  2. 根据权利要求1所述的自动驾驶方法，其特征在于，所述智能交通***获取路况信息的途径包括：道路监测装置、车载监测装置或高空监测装置中的至少一种途径。
  3. 根据权利要求1所述的自动驾驶方法，其特征在于：所述道路信息包括：车道数、车道宽度、曲率半径、坡度、道路材质、出入口、红绿灯、道口、连接道路、道路环境、路面情况中的至少一种信息。
  4. 根据权利要求1所述的自动驾驶方法，其特征在于：所述方法还包括获取道路上的人工驾驶车辆的相关信息，用于预测人工驾驶车辆的行驶期望行为。
  5. 根据权利要求1所述的自动驾驶方法，其特征在于：所述方法还包括将所述道路车辆整体自动驾驶方案传输至人工驾驶车辆，用于提示司机自动驾驶车辆的行驶情况或引导司机驾驶车辆。
  6. 根据权利要求1所述的自动驾驶方法，其特征在于：所述自动驾驶方法还包括：在相同的道路交通模型下，对不同的道路车辆整体自动驾驶方案进行评估和比较，优先提供最优的道路车辆整体自动驾驶方案。
  7. 根据权利要求1-6中任一权利要求所述的自动驾驶方法，其特征在于：所述方法还包括当道路交通模型发生变化时，重新进行智能分析，得到新的道路车辆整体自动驾驶方案，并传输至自动驾驶车辆执行。
  8. 根据权利要求1-6中任一权利要求所述的自动驾驶方法，其特征在于：所述方法还包括根据道路信息及路况信息的实际情况，选择合适的覆盖范围建立道路交通模型。
  9. 根据权利要求1-6中任一权利要求所述的自动驾驶方法，其特征在于：所述方法还包括将获取的不同数据来源/数据结构/数据标准/数据格式/数据描述的信息进行转换和/或整合。
  10. 根据权利要求1-9中任一权利要求所述的自动驾驶方法，其特征在于：所述建立道路交通模型是通过选择与实际情况相似度高的已有道路交通模型，并根据实际信息相应修改所述已有道路交通模型以得到适合实际情况的道路交通模型。
  11. 一种车辆的自动驾驶装置，其特征在于，所述自动驾驶装置包括控制组件和无线传输组件；
    所述无线传输组件用于无线发送车载监测装置的监测数据和接收自动驾驶方案；
    所述控制组件用于按照所述自动驾驶方案控制车辆行驶。
  12. 一种智能交通***，其特征在于，所述***包括：道路监测装置、信号收发器和服务器，
    所述道路监测装置用于获取道路信息和路况信息；
    所述信号收发器用于收发信号；
    所述服务器获取道路信息和路况信息及道路上行驶的车辆信息；通过获取的信息建立道路交通模型，智能分析出道路车辆整体自动驾驶方案；将所述方案通过所述信号收发器传输至自动驾驶车辆，自动驾驶车辆按照所述方案执行自动驾驶。
PCT/CN2020/094719 2020-06-05 2020-06-05 一种基于智能交通***的自动驾驶方法、装置和智能交通*** WO2021243710A1 (zh)

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