Vehicle overall automatic driving method, device and system

Abstract

The invention discloses an overall automatic driving method, device and system for a vehicle, and relates to the technical field of intelligent traffic, and the method comprises the steps: constructing a traffic model according to the driving related information of the vehicle, and taking the starting point, destination, driving purpose, passenger / article and time demand of the vehicle as the input, the traffic model is utilized to generate an overall automatic driving scheme of the traffic tool, the overall automatic driving scheme of the traffic tool is sent to all the automatic driving traffic tools in the traffic model, and each automatic driving traffic tool performs automatic driving according to the overall automatic driving scheme of the traffic tool. Therefore, the problems that information acquisition is not comprehensive and decisions of the vehicles conflict with one another can be effectively avoided, and the driving safety and the driving efficiency of the vehicles are greatly improved.

Description

[0001] This application is a divisional application of the patent application named "A Method, Device and System for Autonomous Driving of a Vehicle Based on an Intelligent Transportation System". The filing date of the original application is June 5, 2021, and the application number is 202180001446.4. Technical Field

[0002] The present invention relates to the technical field of intelligent transportation, and particularly to a method, device and system for overall autonomous driving of a vehicle. Background Art

[0003] With the continuous development of technology, the emergence of autonomous driving technology has greatly promoted the development of transportation. Autonomous driving vehicles mainly rely on the collaborative cooperation of artificial intelligence, visual computing, radar, monitoring devices and the global positioning system to achieve automatic driving of vehicles. However, in areas with vision or sensing blind spots, autonomous driving vehicles are very likely to be unable to make appropriate and accurate decisions due to the inability to sense the surrounding conditions in a timely manner, resulting in problems such as incomplete information acquisition and conflicting decisions among vehicles. Summary of the Invention

[0004] The purpose of the present invention is to provide a method, device and system for overall autonomous driving of a vehicle, which can effectively avoid the problems of incomplete information acquisition and conflicting decisions among vehicles, and greatly improve the safety and efficiency of vehicle driving.

[0005] To achieve the above purpose, the present invention provides the following solutions:

[0006] A method for overall autonomous driving of a vehicle, comprising:

[0007] Obtaining relevant information on vehicle driving; the relevant information on vehicle driving includes: vehicle information, driving basic information and driving information;

[0008] Constructing a traffic model based on the relevant information on vehicle driving; the traffic model includes: road width, road texture, road curvature / angle, traffic flow, vehicle position / model / speed / acceleration / braking distance, driving purpose of the vehicle, destination, time requirement, urgency, passenger / cargo driving requirement, fuel quantity, power quantity, obstacle position / size, speed / direction / purpose / possible behavior of pedestrians / bicycles / electric vehicles / animals, weather conditions, special situations and other contents affecting traffic;

[0009] Taking the starting point, destination, driving purpose, passengers / items, and time requirements of the vehicle as inputs, and generating an overall autonomous driving plan for the vehicle by using the traffic model;

[0010] Send the overall autonomous driving plan of the vehicle to all autonomous driving vehicles in the traffic model, and each of the autonomous driving vehicles performs autonomous driving according to the overall autonomous driving plan of the vehicle.

[0011] An overall autonomous driving device for a vehicle, comprising:

[0012] A wireless transmission component, configured to receive the overall autonomous driving plan of the vehicle generated by using the above-mentioned overall autonomous driving method for a vehicle;

[0013] A control component, configured to control the vehicle to automatically drive according to the overall autonomous driving plan of the vehicle.

[0014] An intelligent transportation system, comprising:

[0015] A traffic information acquisition device, configured to acquire relevant information on the driving of the vehicle; the relevant information on the driving of the vehicle includes: information of the vehicle, driving basic information, and driving information;

[0016] A server, configured to construct a traffic model according to the relevant information on the driving of the vehicle; the traffic model includes: road width, road texture, road curvature / angle, traffic flow, vehicle position / model / speed / acceleration / braking distance, driving purpose of the vehicle, destination, time requirement, emergency level, passenger / cargo driving requirement, fuel quantity, power quantity, obstacle position / size, speed / direction / purpose / possible behavior of pedestrians / bicycles / electric vehicles / animals, weather condition, special situation, and other contents affecting traffic; taking the starting point, destination, driving purpose, passenger / object, and time requirement of the vehicle as inputs, generating an overall autonomous driving plan of the vehicle by using the traffic model; sending the overall autonomous driving plan of the vehicle to all autonomous driving vehicles in the traffic model, and each of the autonomous driving vehicles performs autonomous driving according to the overall autonomous driving plan of the vehicle.

[0017] According to the specific embodiments provided by the present invention, the following technical effects of the present invention are disclosed:

[0018] The present invention provides a method, apparatus and system for overall autonomous driving of a vehicle. A traffic model is constructed based on relevant information of the vehicle's driving. Using the starting point, destination, driving purpose, passengers / items, and time requirements of the vehicle as inputs, an overall autonomous driving plan for the vehicle is generated by the traffic model. The overall autonomous driving plan for the vehicle is sent to all autonomous driving vehicles in the traffic model, and each autonomous driving vehicle performs autonomous driving according to the overall autonomous driving plan for the vehicle, so that an overall autonomous driving plan for the coordinated operation of each vehicle can be generated, effectively avoiding the problems of incomplete information acquisition and conflicting decisions of each vehicle, and greatly improving the driving safety and driving efficiency of the vehicle. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0020] Figure 1 It is a schematic flowchart of a method for overall autonomous driving of a vehicle provided in Embodiment 1 of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0021] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0022] The purpose of the present invention is to provide a method, apparatus and system for overall autonomous driving of a vehicle, which can effectively avoid the problems of incomplete information acquisition and conflicting decisions of each vehicle, and greatly improve the driving safety and driving efficiency of the vehicle.

[0023] In order to make the above objects, features and advantages of the present invention more obvious and understandable, the present invention will be further described in detail below with reference to the drawings and specific embodiments.

[0024] Embodiment 1

[0025] As Figure 1 shown, a method for overall autonomous driving of a vehicle in this embodiment includes:

[0026] S1: Obtain relevant information on the travel of the transportation vehicle; the relevant information on the travel of the transportation vehicle includes: information on the transportation vehicle, basic travel information, and travel information.

[0027] In this embodiment, relevant information on the travel of the transportation vehicle is obtained through an intelligent transportation system. The intelligent transportation system (ITS) refers to an integrated management system that effectively integrates advanced information technology, data communication and transmission technology, electronic sensing technology, electronic control technology, and computer processing technology on a relatively complete infrastructure, and then establishes a real-time, accurate, and efficient comprehensive management system that plays a role in a large range and in all aspects. As the development direction of future transportation systems, the intelligent transportation system is of great significance in reducing the pressure on the transportation system, ensuring the safety of transportation vehicle travel, and improving the transportation efficiency of transportation vehicles. Therefore, there is an urgent need for a method that organically combines autonomous driving technology with the intelligent transportation system to better achieve the safety and efficiency of autonomous driving of transportation vehicles.

[0028] In this embodiment, the transportation vehicle is a vehicle, ship, aircraft, unmanned aerial vehicle, satellite, or rocket. Therefore, the overall autonomous driving method for transportation vehicles in this embodiment can be used for transportation vehicles such as vehicles, ships, aircraft, unmanned aerial vehicles, satellites, and rockets.

[0029] The relevant information on the travel of the transportation vehicle is an important basis for establishing a traffic model and also an important basis for analyzing and obtaining the overall autonomous driving plan for the transportation vehicle. Therefore, obtaining complete and comprehensive relevant information on the travel of the transportation vehicle is a guarantee for the correctness and safety of the overall autonomous driving plan for the transportation vehicle.

[0030] In this embodiment, the relevant information on the travel of the transportation vehicle includes: information on the transportation vehicle, basic travel information, and travel information.

[0031] The information on the transportation vehicle includes: transportation vehicle type, model, number, parameters such as the length / width / height / mass / maximum speed / braking distance / tire condition / power condition / battery level / fuel level of the transportation vehicle, the starting point / destination of the transportation vehicle, the travel purpose of the transportation vehicle (such as sightseeing / going to work / shopping / attending a meeting, etc.), the number of passengers, passenger information (such as crowd / age / height / weight / motion sickness resistance / vibration resistance, etc.), and traffic-related time requirements.

[0032] The information of the transportation vehicle may also include information specific to different types of transportation vehicles. For example, when the transportation vehicle is a ship, the information of the transportation vehicle also includes: ship name, year of completion, builder, ship type, cargo type, nationality, shipowner, displacement, full load displacement, draft, beam, length, speed, power, revolutions per minute, etc.; when the transportation vehicle is an aircraft, the information of the transportation vehicle also includes: flight envelope, maximum flight altitude, maximum range, takeoff distance, takeoff speed, runway requirements, pilot requirements, number of seats, seat pitch, etc.; when the transportation vehicle is a satellite or a rocket, the information of the transportation vehicle also includes: weight, size, use, orbit, residence time, etc.

[0033] The driving basic information is the basic information required for the transportation vehicle to drive. For a vehicle, it is road information; for a ship, it is water area information; for an aircraft, it is airspace information. When the transportation vehicle is a vehicle, the driving basic information includes: number of lanes, lane width, radius of curvature, slope, road material, entrances and exits, traffic lights, intersections, connecting roads, road environment, road surface conditions (including friction, load-bearing capacity, height limit, speed limit, etc.), height limit information, and other information related to the road itself; when the transportation vehicle is a ship, the driving basic information includes: water flow, water depth, reefs, wind and waves, ports, lighthouses, etc.; when the transportation vehicle is an aircraft, the driving basic information includes: flight path, wind speed, wind direction, cloud conditions, airports, runways, etc.

[0034] The driving basic information may also include: map information, geological information, environmental information, climate information, address information, etc.

[0035] The driving information is the information that may affect the driving of the transportation vehicle within the coverage of this intelligent transportation system. For a vehicle, it includes road condition information; for a ship, it includes water area condition information; for an aircraft, it includes airspace condition information. When the transportation vehicle is a vehicle, the driving information includes: traffic flow, information related to navigation such as the position / speed / acceleration / direction / route of other surrounding transportation vehicles, obstacle / pedestrian information, traffic signal information, road surface damage condition, traffic accidents, and other information related to road traffic conditions, traffic control, traffic signals, road condition rules, road condition requirements, road condition prediction, etc.; when the transportation vehicle is a ship, the driving information includes: flag signal, position / speed / acceleration / draft / direction / route of other surrounding ships, obstacle information, etc.; when the transportation vehicle is an aircraft, the driving information includes: air traffic control signal, position / speed / acceleration / flying altitude / direction / route of other surrounding aircraft, obstacle information, etc.

[0036] The driving information may also include: the convergence of different transportation system information, such as flight information, train information, activities (including competitions, performances, exhibitions, shows), government affairs, sports, study, work, entertainment (including movies, concert halls, games, amusement parks, dance halls), shopping, dining, medical treatment, tourism, festivals and other traffic-related information.

[0037] In this embodiment, obtaining the relevant information of the vehicle driving specifically includes: jointly obtaining the relevant information of the vehicle driving through multiple obtaining channels in the traffic information obtaining device on the way, the traffic information obtaining device carried by the vehicle, the remote traffic information obtaining device, the map system, the navigation system, the traffic management system, the climate system, the traffic information system. Of course, it may also include other obtaining channels, such as the travel management system, the weather forecast system, etc.

[0038] Among them, the traffic information obtaining device on the way includes: a variety of devices such as cameras, radars, induction sensors, infrared detection devices, pressure / optical / ultrasonic sensors on the road or pavement. Multiple devices can be set at appropriate positions on the way to obtain this information. The traffic information obtaining device carried by the vehicle includes: cameras / radars / speedometer / location devices carried on the vehicle, ship or aircraft. The remote traffic information obtaining device includes: satellites / remote radars, etc. Obtaining the relevant information of the vehicle driving through the traffic information obtaining device on the way, the traffic information obtaining device carried by the vehicle, and the remote traffic information obtaining device may be to receive the information actively sent by the above devices or the reply information of the above devices obtained after the intelligent transportation system actively inquiries.

[0039] The way for the intelligent transportation system to obtain the relevant information of the vehicle driving may also be to obtain the relevant information by monitoring the Internet of Things hardware / RF cards / ETC devices of the vehicle, or to obtain the relevant information of the road conditions by monitoring pedestrians / animals / vehicles / buildings / stations, etc. within the range that may affect the driving on the way. In addition, the intelligent transportation system can also obtain the map information of the relevant area through the map server. The map information may include the basic information required for the vehicle driving, such as road information / water area information / airspace information, and may also include the information that may affect the vehicle driving around, such as road condition information / water area condition information / airspace condition information, and may also include positioning / navigation information. Among them, the map information may be two-dimensional map information or three-dimensional map information. The intelligent transportation system can also obtain the relevant information of the vehicle driving in the relevant area from other system servers.

[0040] The advantage of obtaining information through multiple means is to make the information more comprehensive and avoid information loss caused by a single information source. For example, existing autonomous driving technologies usually rely on the monitoring devices of the vehicle itself to obtain information, which is easily blocked, resulting in some information being unavailable.

[0041] In this embodiment, since the obtained information comes from different sources, there may be a situation where the data structures / data standards / data formats / data descriptions, etc. of the obtained information are different. In this situation, in order to make the use of information smoother and more efficient, it is necessary to convert and / or integrate information from different sources. Specifically, the conversion and / or integration of information 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, translation of different languages, etc.

[0042] S2: Construct a traffic model based on the relevant information of the vehicle's travel; the traffic model includes: road width, road texture, road curvature / angle, traffic flow, vehicle position / model / speed / acceleration / braking distance, the travel purpose, destination, time requirement, urgency, passenger / cargo travel requirements, fuel quantity, power quantity of the vehicle, obstacle position / size, speed / direction / purpose / possible behavior of pedestrians / bicycles / electric vehicles / animals, weather conditions, special situations, and other contents affecting traffic.

[0043] In this embodiment, the intelligent transportation system establishes a traffic model. The traffic model includes: roads / sea lanes / air lanes, vehicles, obstacles, pedestrians, coverage area, coverage time, weather conditions, special situations, and other traffic-related factors. Specifically, it can include: road width, road texture, road curvature / angle, traffic flow, vehicle position / model / speed / acceleration / braking distance (also including the correlation between acceleration, braking and road conditions), the travel purpose, destination, time requirement, urgency, passenger / cargo travel requirements, fuel quantity, power quantity of the vehicle, obstacle position / size, reef position / size, cloud position / size, speed / direction / purpose / possible behavior of pedestrians / bicycles / electric vehicles / animals, etc., weather conditions (such as visibility / wind speed / ocean current / rain / snow / icing on the road surface, etc.), special situations (such as day-night differences / traffic tide rules / traffic control or restriction plans / vehicle weights / time priority of special tasks / limited-time arrival, and avoidance of other vehicles), and other contents affecting traffic (including various airplanes / ships / cars / objects / people outside the road).

[0044] The coverage of the traffic model can be set according to the actual situation, and the coverage can be a small section of road / channel / airway, a complete road / channel / airway, several roads / channel / airways, within a region, within a city, and a broader scope.

[0045] The richer and more real the information obtained, the more parameters the traffic model contains, and the closer the established traffic model is to the actual situation. The more perfect the overall automatic driving scheme of the vehicle obtained based on this traffic model is. Establishing a traffic model can include: first establishing it based on the relevant information obtained about the vehicle's driving, and then improving it by combining the map information and navigation information obtained from the map server and navigation server to obtain the traffic model.

[0046] In this embodiment, establishing a traffic model can be to create a new traffic model based on the information obtained, or to select an existing traffic model with a high similarity to the actual situation according to the information obtained, and modify the existing traffic model accordingly according to the actual situation to obtain a traffic model suitable for the actual situation, that is, select an existing traffic model with a high similarity to the actual situation according to the relevant information of the vehicle's driving; modify the existing traffic model according to the actual situation to obtain a traffic model suitable for the actual situation. Among them, the determination criterion of similarity can be set in advance, or obtained through big data analysis / artificial intelligence deep learning, or continuously optimized and improved during actual use.

[0047] S3: Using the starting point, destination, driving purpose, passengers / items, and time requirements of the vehicle as inputs, generate an overall automatic driving scheme for the vehicle using the traffic model.

[0048] After establishing the traffic model, within the model scope, based on true and complete information (including spatial information / temporal information / object information / other information (such as traffic control, traffic restrictions, or traffic lights, etc.)), calculate and analyze to obtain an overall automatic driving scheme for the vehicle.

[0049] After establishing the traffic model, the user inputs the starting point, destination, driving purpose, passengers / items, time requirements, etc. of the trip, substitute the starting point, destination, driving purpose, passengers / items, and time requirements of the vehicle into the traffic model, obtain the location information and relevant information about the vehicle's driving, plan the user's trip based on the above information, give an overall automatic driving scheme for the vehicle, and the user's vehicle travels according to this overall automatic driving scheme, and can safely and efficiently reach the designated destination.

[0050] This embodiment is to determine an overall autonomous driving solution for vehicles. Compared with the existing single autonomous driving solution for a single vehicle, calculating the overall autonomous driving solution as a whole has great advantages. First, for the overall autonomous driving solution for vehicles, each autonomous vehicle within the regional scope executes according to this overall autonomous driving solution. It is equivalent that the expected driving trajectories of these autonomous vehicles are known, and only the driving trajectory of the human-driven vehicle needs to be predicted. While for the single autonomous driving solution for a single vehicle, the driving trajectories of each vehicle need to be predicted. In addition, for the overall autonomous driving solution for vehicles, when calculating and analyzing the planning solution, it is considered from the whole of the vehicles, avoiding conflicts in the driving trajectories between the vehicles in the overall autonomous driving solution and making the overall safety and driving efficiency of the vehicles the highest. While for the single autonomous driving solution for a single vehicle, only the driving efficiency and safety of this vehicle are considered, and the single autonomous driving solutions between different vehicles may affect each other, reducing the overall driving efficiency and safety of the vehicles. Therefore, the overall autonomous driving method in this embodiment is superior to the existing single autonomous driving method in terms of both driving efficiency and safety. At the same time, for each autonomous vehicle, the overall autonomous driving method in this embodiment will also plan the optimal driving route according to the vehicle destination and real-time road conditions.

[0051] S4: Send the overall autonomous driving solution of the vehicle to all the autonomous vehicles in the traffic model, and each of the autonomous vehicles conducts autonomous driving according to the overall autonomous driving solution of the vehicle.

[0052] Send the overall autonomous driving solution of the vehicle to all the autonomous vehicles in the traffic model, and each autonomous vehicle executes the overall autonomous driving solution of the vehicle and automatically drives according to its own driving trajectory / real-time speed / real-time acceleration.

[0053] In this embodiment, after obtaining information and establishing a traffic model, there may be multiple overall autonomous driving solutions of the vehicle obtained through analysis and calculation. Different overall autonomous driving solutions of the vehicle may each have advantages. Therefore, in order to select the optimal overall autonomous driving solution of the vehicle, the overall autonomous driving method in this embodiment further includes: evaluating and comparing different overall autonomous driving solutions of the vehicle under the same traffic model, and preferentially providing the optimal overall autonomous driving solution of the vehicle.

[0054] Taking the starting point, destination, driving purpose, passengers / items, and time requirements of the transportation vehicle as inputs, a comprehensive autonomous driving plan for the transportation vehicle is generated using a traffic model. Specifically, it includes: taking the starting point, destination, driving purpose, passengers / items, and time requirements of the transportation vehicle as inputs, and generating multiple comprehensive autonomous driving plans using the traffic model; for each comprehensive autonomous driving plan, according to the level / score of each transportation vehicle in each evaluation objective among multiple evaluation objectives, the objective weight of each evaluation objective, and the vehicle weight of each transportation vehicle, calculate the comprehensive level / weight of the comprehensive autonomous driving plan; the evaluation objectives include: safety, driving efficiency, comfort, energy consumption, purposefulness, and real-time performance; the purposefulness includes evaluation items related to the driving purpose, destination, or time. Different driving purposes have different requirements for time, route selection, speed, and lanes. The vehicle weight is determined based on the vehicle type, number of passengers, vehicle value, and items carried by the transportation vehicle; select the comprehensive autonomous driving plan with the highest comprehensive level / weight as the comprehensive autonomous driving plan for the transportation vehicle.

[0055] Under the same traffic model, for the results of the evaluation of each transportation vehicle in the comprehensive autonomous driving plan according to objectives such as safety / driving efficiency / comfort / energy consumption, set the corresponding level / score, and set the objective weights of objectives such as safety / driving efficiency / comfort / energy consumption. Set the vehicle weights of each transportation vehicle according to aspects such as the vehicle type / number of passengers / vehicle value of each transportation vehicle, so as to be able to calculate the comprehensive level / score of this comprehensive autonomous driving plan based on the level / score of the vehicle objective evaluation and the objective weights in the comprehensive autonomous driving plan, as well as the vehicle weights of each transportation vehicle, in order to facilitate the comprehensive comparison and ranking of multiple comprehensive autonomous driving plans under the same traffic model.

[0056] The optimal solution is to comprehensively evaluate aspects such as the safety, driving efficiency, comfort, energy consumption, and purpose of the vehicle, and select the solution with the highest comprehensive score obtained by combining the target weights and vehicle weights. By setting different levels, scores, and weights for different targets, various optimal solutions can be achieved. The evaluation items can include: total time, total distance, total energy consumption, energy utilization efficiency, proportion of green energy, total pollution, etc. The evaluation items can also include items related to the driving purpose, destination, or time, such as: for different driving purposes, the time requirements are catching a plane > going to work > sightseeing; different driving purposes also have different requirements for route selection, speed, lanes, etc. For example, for the purpose of sightseeing, the preferred route for autonomous driving is a scenic route, driving at an appropriate speed on the lane close to the scenery; for rigid targets that must be achieved, such as ambulances / fire trucks / rescue aircraft need to reach the designated location within 30 minutes, their level can be set as the highest priority. Therefore, if this rigid target is not achieved, the comprehensive level / score of the overall autonomous driving solution will surely be lower than that of the overall autonomous driving solution when this rigid target is achieved. Rigid targets can also include: military affairs, police affairs, medical treatment, emergencies, safety, and other crucial targets. Classify / group vehicles / pedestrians / cargo according to factors such as vehicle type, passenger type, cargo type, destination, distance, route / route model, etc., and then set their weights through classification / grouping. The setting and optimization of levels / scores / weights can be based on professional / authoritative research results, or data obtained through big data analysis / information reorganization, which can be data obtained through artificial intelligence deep learning, or new data obtained through statistical analysis during the use of the original data, or a combination of the above methods. The setting and optimization of levels / scores / weights can be manually set, automatically set by artificial intelligence, or semi-manually and semi-automatically set.

[0057] Among them, the elements included in the safety objective may include: accident possibility / accident type / possible number of injured / possible number of deaths / possible economic losses / possible consequences / possible impacts, etc. The elements included in the travel efficiency objective may include: travel time / travel speed / travel mileage / trip completion rate / target achievement rate / timeliness evaluation, etc. The elements included in the comfort objective may include: travel speed / travel acceleration and deceleration / number of sharp turns / number of rapid accelerations / number of rapid decelerations / number of rapid ascents / number of rapid descents / bumpiness degree, etc. The elements included in the energy consumption objective may include: energy consumption of a single vehicle / total energy consumption / energy consumption per unit distance / energy consumption of a single task / energy consumption per capita / energy consumption per unit carrying capacity, etc. In this embodiment, the weights of the vehicles can be set according to aspects such as vehicle type, passenger group, and items carried by the vehicle. Vehicle types may include: vehicles, ships, airplanes, and drones. Vehicles can also be divided into: passenger cars / trucks / large vehicles / medium-sized vehicles / small vehicles / special-purpose vehicles / luxury cars, etc. Ships can also be divided into: river ships / sea ships / sailboats / steamships / cruise ships / freighters / large ships / medium-sized ships / small ships / special-purpose ships, etc. Airplanes can also be divided into: helicopters / jet airplanes / passenger airplanes / freight airplanes / large airplanes / medium-sized airplanes / small airplanes / training airplanes, etc. Drones can also be divided into: rotor drones / flying wing drones / special-purpose drones, etc. The passenger group may include: children, the elderly, pregnant women, patients, etc. Items carried by the vehicle may include: dangerous goods, fragile goods, volatile goods, etc.

[0058] In addition, the setting of levels / score values and weights can be adjusted according to different actual situations. For example, the weight of a special type of vehicle (such as a police car on a mission) is usually higher than that of a private car, but the weight of a private car carrying a critically ill patient may be higher than that of a general special type of vehicle. Another example: Under normal weather conditions, the takeoff interval of an airplane and the distance from the previous aircraft by 3 minutes do not affect the level / score value in terms of safety, but under bad weather conditions, the takeoff interval of an airplane and the distance from the previous aircraft by 3 minutes may lead to a decrease in the level / score value in terms of safety.

[0059] The overall autonomous driving solution is obtained through intelligent analysis of the traffic model. The process of obtaining the overall autonomous driving solution through intelligent analysis of the traffic model is a complex one, involving a large amount of computational work. However, autonomous driving is also a behavior with high real-time requirements. Therefore, it is required that the analysis of the overall autonomous driving solution be completed within a limited short time. This requires the overall autonomous driving method of this embodiment to balance between real-time performance and the optimal solution of the scheme. In the evaluation and comparison of the above overall autonomous driving solution, the evaluation of real-time performance is added. At this time, for a certain overall autonomous driving solution, not only the evaluations in terms of safety, driving efficiency, comfort, energy consumption, etc. need to be considered, but also the evaluation in terms of real-time performance needs to be considered. Because too low real-time performance will inevitably affect the driving efficiency of autonomous driving and may also likely affect safety, thus reducing the comprehensive evaluation of the scheme.

[0060] In this embodiment, the methods to reduce the computational work of analyzing the overall autonomous driving solution and thus improve real-time performance may include: selecting an appropriate coverage range to establish a traffic model according to the actual situation of the driving-related information of the vehicle. By appropriately reducing the size of the coverage range of the traffic model, the complexity of the traffic model can be reduced, the number of vehicles and the number of obstacles in the traffic model can be decreased, which can significantly reduce the computational work and thus greatly improve the real-time performance of the scheme.

[0061] The methods to improve real-time performance may also include: under the same or similar traffic models, storing / recording the levels / score values / weights set according to the evaluation results in terms of safety, driving efficiency, comfort, etc. of the vehicle, so that relevant settings can be directly used or referred to under the same / similar conditions. It is also possible to perform centralized processing on similar or partially similar vehicles, calculate them as a whole package, reduce the computational work, and improve real-time performance.

[0062] The methods to improve real-time performance may also include: setting that the vehicles / obstacles in the traffic model have a finite number of states to improve real-time performance, that is, limiting the vehicles / obstacles in the traffic model to a finite number of states. For example, the vehicle states may include: accelerating, decelerating, stopping, turning left, turning right, ascending, descending, changing lanes, overtaking, avoiding, etc. By limiting the finite states of each element in the traffic model, the computational work can be reduced and real-time performance can be improved.

[0063] In this embodiment, a large traffic model can also be divided into multiple local models, and each local model can be established by different hosts / servers / computing platforms respectively, and then the local models are superimposed into an overall model. By dividing the overall model into local models, the computing workload of a single host / server / computing platform can be effectively reduced, and the real-time response speed can be improved. The 5G and edge computing technologies can also be used to transmit data to the nearest idle computing platform through 5G to improve the real-time performance of data processing. It can also be to utilize the computing power of the vehicle itself to allocate the establishment of the traffic model and the intelligent analysis of the overall autonomous driving solution to the intelligent transportation system and multiple vehicles that agree to share their own computing power for processing, and then combine the results of these processes to obtain.

[0064] In this embodiment, the driving-related information of each vehicle in the target area is comprehensively obtained through the traffic information acquisition device on the way, the traffic information acquisition device carried by the vehicle, the remote traffic information acquisition device or other monitoring devices, so as to establish a traffic model and give an overall autonomous driving solution to the vehicle, thus effectively avoiding problems such as incomplete information acquisition and conflicting decisions of each vehicle, and greatly improving the driving safety and driving efficiency of the vehicle.

[0065] In order to further improve the safety / efficiency / comfort of the overall autonomous driving solution and reduce the computing workload and improve the real-time performance, the overall autonomous driving method of this embodiment may further include: obtaining the relevant information of the human-driven vehicle related to driving for predicting the expected driving behavior of the human-driven vehicle. Among them, the relevant information of the human-driven vehicle may include: vehicle condition, map / navigation system, driving plan, operation information, driver, driving style, driving level, driving preference, special habit, destination, route planning and other information. For example: if a human-driven car often brakes suddenly, the overall autonomous driving solution needs to maintain a greater safe driving distance for this car. The relevant information of the human-driven vehicle can be obtained by collecting and storing through a self-built database, or obtained from the database of the traffic management department or other relevant organizations, or obtained by analyzing the relevant information continuously obtained during the use of this method. The expected driving behavior of the human-driven vehicle refers to the driving behavior that the human-driven vehicle may take and the expected probability of the driving behavior.

[0066] In this embodiment, the overall autonomous driving solution for the vehicle is sent to a manually-driven vehicle to guide the driver to drive the manually-driven vehicle. Specifically, the overall autonomous driving solution for the vehicle is transmitted to the manually-driven vehicle or related devices (such as navigation devices, assisted driving devices, smartphones, etc.) to prompt the driver about the driving conditions of the autonomous vehicle, guide the driver to drive the manually-driven vehicle, or provide assisted driving. The driver of the manually-driven vehicle can learn in advance the expected driving trajectories of the surrounding autonomous vehicles and can also receive guidance to lead the driver to take correct driving actions such as decelerating, accelerating, and steering in such situations, which can greatly reduce the probability of accidents, improve driving efficiency, and enhance safety.

[0067] In this embodiment, if the autonomous vehicle does not reach the autonomous driving level of a fully autonomous vehicle but only the assisted driving level, the overall autonomous driving solution for the vehicle can be transmitted to the vehicle at the assisted driving level, so that the assisted driving system of the vehicle can remind / suggest / alarm / actively control the vehicle to drive according to the vehicle trajectory of the overall autonomous driving solution for the vehicle.

[0068] In this embodiment, the vehicle performs autonomous driving in at least one of the following ways: mutually providing information, jointly negotiating to formulate the overall autonomous driving solution for the vehicle, and completely driving according to the overall autonomous driving solution for the vehicle. That is, the vehicle can adopt different ways to utilize the overall autonomous driving method according to its actual situation. The ways for the vehicle to utilize the overall autonomous driving method can include at least one of mutually providing information, jointly negotiating to formulate the overall autonomous driving solution, and completely driving according to the overall autonomous driving solution. The way of mutually providing information means that the vehicle can only exchange information with the intelligent transportation system, such as information obtained by its own sensors, the driving route, etc., and receive the overall autonomous driving solution sent by the intelligent transportation system, and learn from it the autonomous driving solutions of other surrounding vehicles for use in assisted driving or to prompt the driver to pay attention. The way of jointly negotiating to formulate the overall autonomous driving solution means that the vehicle puts forward some requirements for its own autonomous driving, and the intelligent transportation system needs to meet the requirements of the vehicle when formulating the overall autonomous driving solution. Only after reaching an agreement through negotiation can the vehicle adopt the overall autonomous driving solution for autonomous driving. The way of completely driving according to the overall autonomous driving solution means that the vehicle completely follows the overall autonomous driving solution formulated by the intelligent transportation system.

[0069] The overall autonomous driving method of this embodiment can also adopt a distributed computing method, which distributes the establishment of a traffic model and the intelligent analysis of the overall autonomous driving plan to the intelligent transportation system and multiple vehicles that agree to share their own computing capabilities for processing, and then combines the results of these processes. Since the existing vehicle hardware configurations are generally not low and have strong computing capabilities, not inferior to a computer, through distributed computing, the computing capabilities of a large number of vehicles can be fully utilized, which can greatly improve the real-time performance of establishing a traffic model and intelligently analyzing the overall autonomous driving plan, and at the same time reduce the hardware requirements for the intelligent transportation system.

[0070] Among them, for distributing the establishment of a traffic model and the intelligent analysis of the overall autonomous driving plan to the intelligent transportation system and multiple vehicles that agree to share their own computing capabilities for distributed computing processing, it can be to allocate the computing related to the vehicle itself. For example, the intelligent transportation system sends an instruction to the vehicle to overtake or follow, and the vehicle calculates a specific driving plan suitable for the instruction based on the information related to the instruction, and then feeds back the specific driving plan suitable for the instruction to the intelligent transportation system. The information related to the instruction obtained by the vehicle can be obtained from the intelligent transportation system or through the monitoring device carried by the vehicle. The information related to the instruction can be the information of the vehicle, the basic driving information, or the surrounding driving information.

[0071] The overall autonomous driving method of this embodiment can also include: the intelligent transportation system sends a basic autonomous driving instruction to the vehicle, and the vehicle independently analyzes a driving plan suitable for the vehicle according to the basic autonomous driving instruction. The basic autonomous driving instruction sent to the vehicle can be: speed limit, lane limit, following, overtaking, turning, automatic cruise, etc. The vehicle can independently analyze a driving plan suitable for the vehicle according to the basic autonomous driving instruction and drive according to the driving plan. At the same time, the driving plan can be transmitted to the intelligent transportation system. By transmitting the basic autonomous driving instruction and having the vehicle drive according to the basic autonomous driving instruction independently, the software and hardware functions of the vehicle itself can be effectively utilized, and at the same time, the computing amount of the intelligent transportation system analysis can be reduced. And because the vehicle will transmit the driving plan that it independently analyzes as suitable for the vehicle according to the basic autonomous driving instruction to the intelligent transportation system, the intelligent transportation system also fully understands the specific driving conditions of the vehicle. Therefore, when analyzing the overall autonomous driving plan or the basic autonomous driving instruction, it still has an advantage in efficiency compared to the single-vehicle autonomous driving plan.

[0072] In practice, the intelligent transportation system may not be the only one. There may be multiple different intelligent transportation systems that can provide an overall autonomous driving solution. Therefore, the intelligent transportation system can also perform data interaction with other intelligent transportation systems and / or jointly negotiate to formulate an overall autonomous driving solution to achieve the overall driving plan between different transportation systems. By obtaining as much information as possible, a more efficient overall autonomous driving solution can be formulated.

[0073] In this embodiment, after generating the overall autonomous driving solution for the vehicle using the traffic model, it further includes: the intelligent transportation system manages at least one of traffic lights, bridges, railings, guiding lines / lights, peak lanes, passage / block, traffic signs, including managing traffic signals, intersections, lanes, waterways, air traffic control, etc., to further improve the overall traffic efficiency. For example: according to the overall autonomous driving solution, if there are more vehicles in the north-south direction and fewer vehicles in the east-west direction at an intersection, the intelligent transportation system can adjust the traffic light time, making the green light time longer in the north-south direction and shorter in the east-west direction, thus improving the overall traffic efficiency of this intersection.

[0074] The overall autonomous driving method of this embodiment can also be connected to other systems to provide various services based on the user's driving purpose, such as reserved parking, ticket booking, emergency notification, etc., to further enhance the user experience and traffic efficiency. For example: through the overall autonomous driving method of this embodiment, it is possible to know the exact time when the user drives the vehicle to the cinema, help the user reserve a parking space in the parking system, and at the same time help the user book tickets in the ticket booking system.

[0075] The overall autonomous driving method of this embodiment can also arrange for vehicles to drive jointly or perform mobile charging through the overall autonomous driving solution. For example: when a ship enters or exits a port, through the overall autonomous driving solution, arrange for a tugboat to jointly drive automatically with the ship to more efficiently achieve the entry and exit of the ship. Another example is that when an electric vehicle needs to be charged, arrange for a mobile charging vehicle to meet with the electric vehicle that needs to be charged, and then drive and charge at the same speed while driving through the overall autonomous driving solution, so that the electric vehicle does not need to stop for charging.

[0076] The overall autonomous driving method of this embodiment further includes: when the traffic model changes, for example: when a vehicle driven manually does not drive according to the instructions / suddenly brakes / suddenly accelerates, or a vehicle suddenly has an accident / failure, or new vehicles / pedestrians / obstacles are added, or the road environment / climate environment changes, etc., update the traffic model according to the information obtained in real time, perform intelligent analysis again, obtain a new overall autonomous driving solution, and transmit it to the autonomous driving vehicle for execution.

[0077] The overall autonomous driving method of this embodiment can also be applied to driving in non-preferred areas, such as grasslands, deserts, wastelands, reef areas, etc. Through the on-vehicle monitoring devices and remote monitoring equipment of the vehicle, information on the ground / water / airspace, vehicle information, and information on other vehicles / obstacles / pedestrians or animals in the area are obtained, a traffic model with a certain coverage is established, and an overall autonomous driving plan is obtained through intelligent analysis. Compared with the preferred area, the non-preferred area is less suitable for driving, without fixed roads / sea lanes / air lanes. The vehicle no longer travels along the roads / sea lanes / air lanes, and the possible range of vehicle travel expands. At the same time, since the vehicle density in the non-preferred area is much smaller than that in the preferred area, the number of vehicles in the plan is reduced. The overall autonomous driving method of this embodiment can be correspondingly optimized according to the characteristics of the non-preferred area to improve the driving efficiency and safety in the non-preferred area.

[0078] Based on the relevant information of vehicle driving, this embodiment establishes a traffic model, intelligently analyzes an overall autonomous driving plan based on the traffic model, and transmits it to each vehicle to enable autonomous driving, effectively avoiding problems such as incomplete information acquisition and conflicting decisions of each vehicle, greatly improving the driving safety and efficiency of the vehicle, and facilitating the addition of the autonomous driving function to manned vehicles at low cost.

[0079] Embodiment 2

[0080] This embodiment provides an overall autonomous driving device for a vehicle, including:

[0081] A wireless transmission component for receiving the overall autonomous driving plan for the vehicle generated by using the overall autonomous driving method of Embodiment 1;

[0082] A control component for controlling the vehicle to automatically drive according to the overall autonomous driving plan for the vehicle.

[0083] Specifically, the wireless transmission component is used to wirelessly send the traffic information data of the on-vehicle monitoring device of the vehicle and receive the overall autonomous driving plan for the vehicle; the control component is used to control the vehicle to automatically drive according to the overall autonomous driving plan for the vehicle.

[0084] In this embodiment, it may be that the control component is connected to the control system of the vehicle. The wireless transmission component transmits the received overall automatic driving scheme of the vehicle to the control component, and the control component transmits the overall automatic driving scheme of the vehicle to the control system of the vehicle. The control system of the vehicle controls the vehicle to travel according to the overall automatic driving scheme of the vehicle. It may also be that the control component includes one or more control devices for controlling the vehicle to travel according to the overall automatic driving scheme of the vehicle. The wireless transmission component transmits the received overall automatic driving scheme of the vehicle to the control component. After receiving the scheme, the control component controls the vehicle to travel according to the overall automatic driving scheme of the vehicle by each control device. In this embodiment, different vehicles require different control components. For example, vehicles / ships / aircraft with a high degree of intelligence may have a control system that can fully control the vehicle to travel according to the overall automatic driving scheme of the vehicle or only need a control device to add some control functions to the control system of the vehicle itself. Vehicles / ships / aircraft with a low degree of intelligence may have a low degree of automation and require a large number of control devices to be transformed to adapt to unmanned automatic driving control, such as automatic control of multiple components such as steering gears / accelerators / brakes / transmissions / lights / vehicle condition monitoring. The automatic control devices for different components are different, and the control devices for different levels of automatic driving are also different. For example, the control devices required for unmanned driving have the highest requirements and the most complete functions, while the requirements and functions of the control devices required for assisted driving are lower than those required for unmanned driving.

[0085] Through the automatic driving device of this embodiment, the automatic driving function can be conveniently added to a manually driven vehicle. Since the acquisition and analysis of the information for automatic driving to obtain the scheme do not need to be completed by the vehicle itself, the vehicle only needs to receive the automatic driving scheme and execute according to the automatic driving scheme to achieve the automatic driving function. Therefore, through an automatic driving device of this embodiment, the automatic driving function can be added to a manually driven vehicle at low cost without adding complex hardware devices, as long as it can receive and execute according to the automatic driving scheme.

[0086] Embodiment 3

[0087] This embodiment provides an intelligent transportation system, including:

[0088] A traffic information acquisition device for acquiring relevant information on the travel of a vehicle; the relevant information on the travel of the vehicle includes: information of the vehicle, basic travel information, and travel information;

[0089] A server for constructing a traffic model based on relevant information of vehicle travel; the traffic model includes: road width, road texture, road curvature / angle, traffic flow, vehicle position / model / speed / acceleration / braking distance, travel purpose, destination, time requirement, urgency, travel requirements of passengers / cargo, fuel quantity, power quantity, obstacle position / size, speed / direction / purpose / possible behavior of pedestrians / bicycles / electric vehicles / animals, weather conditions, special situations, and other content affecting traffic; taking the starting point, destination, travel purpose, passengers / items, and time requirements of the vehicle as inputs, generating an overall autonomous driving plan for the vehicle using the traffic model; and sending the overall autonomous driving plan for the vehicle to all autonomous driving vehicles in the traffic model, and each of the autonomous driving vehicles performs autonomous driving according to the overall autonomous driving plan for the vehicle.

[0090] Specifically, the intelligent transportation system includes: a traffic information acquisition device, a signal transceiver, and a server.

[0091] The traffic information acquisition device is used to acquire relevant information of vehicle travel, and may include: devices such as cameras, radars, induction sensors, infrared detection devices, pressure / optical / ultrasonic sensors on roads or road surfaces. The intelligent transportation system may also include remote monitoring devices such as satellites and remote radars.

[0092] The signal transceiver is used to send and receive signals. It can transmit the information acquired by the traffic information acquisition device to the server, and can also receive information sent by the vehicle, such as the information acquired by the monitoring device carried by the vehicle, and transmit it to the server. It can also transmit information from the server to the vehicle, such as the overall autonomous driving plan for the vehicle, etc. The signal transceiver can send and receive signals through wireless means, or through wired means, or through a combination of wired and wireless means.

[0093] The server receives relevant information of vehicle travel; establishes a traffic model, intelligently analyzes an overall autonomous driving plan for the vehicle, and transmits the plan to the vehicle through the signal transceiver. The vehicle performs autonomous driving according to the plan.

[0094] The server can also obtain information from other channels such as remote monitoring devices, and can also connect to the Internet to obtain information through databases of traffic management departments or other relevant organizations. The server can be either the server of the intelligent transportation system itself, or a cloud server, or an MEC server, and uses edge computing and 5G high-speed networks to achieve large-scale real-time computing.

[0095] In this embodiment, the intelligent transportation system may include a large number of traffic information acquisition devices and signal transceivers for acquiring a large amount of relevant information of vehicle travel.

[0096] The technical features of the above embodiments can be combined arbitrarily. For the sake of concise description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope recorded in this specification.

[0097] Specific examples are used in this article to elaborate on the principles and implementation manners of the present invention. The description of the above embodiments is only used to help understand the method and its core idea of the present invention; at the same time, for those of ordinary skill in the art, according to the idea of the present invention, there will be changes in the specific implementation manners and application scopes. In summary, the content of this specification should not be construed as a limitation to the present invention.

Claims

1. An overall automatic driving method for a vehicle, characterized in that, Including: Obtaining relevant information on the travel of a vehicle; The relevant information on the travel of the vehicle includes: information on the vehicle, basic travel information, and travel information; Constructing a traffic model based on the relevant information on the travel of the vehicle; the traffic model includes: road width, road curvature / angle, traffic flow, vehicle position / speed / acceleration, travel purpose, destination, time requirement, urgency, travel requirements of passengers / cargo, obstacle position / size, weather conditions, special circumstances, and other elements affecting traffic; Using the starting point, destination, travel purpose, passengers / articles, and time requirements of the vehicle as inputs, and generating an overall autonomous driving plan for the vehicle by means of the traffic model; Sending the overall autonomous driving plan for the vehicle to all autonomous driving vehicles in the traffic model, and each of the autonomous driving vehicles performing autonomous driving in accordance with the overall autonomous driving plan for the vehicle.

2. The overall autonomous driving method for a vehicle according to claim 1, characterized in that, The vehicle is a vehicle, ship, aircraft, drone, satellite, or rocket; The information on the vehicle includes: vehicle type, model, length / width / height / mass / power status / electricity level / fuel level of the vehicle, starting point / destination of the vehicle, travel purpose of the vehicle, traffic-related time requirements; when the vehicle is a ship, the information on the vehicle further includes: ship type, cargo type, beam width, ship length, speed, power; when the vehicle is an aircraft, the information on the vehicle further includes: maximum flight altitude; when the vehicle is a satellite or rocket, the information on the vehicle further includes: weight, size, use; The basic travel information is the basic information required for the travel of the vehicle; when the vehicle is a vehicle, the basic travel information includes: number of lanes, lane width, radius of curvature, slope, entrances and exits, traffic lights, road junctions, connecting roads, height limit information; when the vehicle is a ship, the basic travel information includes: water flow, water depth, reefs, wind and waves, ports; when the vehicle is an aircraft, the basic travel information includes: flight path, wind speed, wind direction, cloud conditions, airports; The travel information is information that may affect the travel of the vehicle; when the vehicle is a vehicle, the travel information includes: traffic flow, position / speed / direction / route of other surrounding vehicles, obstacle / pedestrian information, traffic signal information, traffic accidents, traffic control, traffic signals; when the vehicle is a ship, the travel information includes: position / speed / draft / direction / route of other ships, obstacle information; when the vehicle is an aircraft, the travel information includes: air traffic control signals, position / speed / flight altitude / direction / route of other surrounding aircraft, obstacle information.

3. A method for overall autonomous driving of a vehicle according to claim 1, characterized in that, Obtaining relevant information on the travel of the vehicle, specifically including: Jointly obtaining relevant information on the travel of the vehicle through multiple acquisition channels such as in-route traffic information acquisition devices, on-vehicle traffic information acquisition devices, remote traffic information acquisition devices, map systems, navigation systems, traffic management systems, climate systems, and traffic information systems.

4. A method for overall autonomous driving of a vehicle according to claim 1, characterized in that, The coverage range of the traffic model is a short section of road / channel / airway, a complete road / channel / airway, multiple roads / channels / airways, a regional scope or a city scope; According to the actual situation of the relevant information of the vehicle travel, select an appropriate coverage range to construct a traffic model to improve real-time performance.

5. A method for overall autonomous driving of a vehicle according to claim 1, characterized in that, Construct a traffic model according to the relevant information of the vehicle travel, specifically including: Select an existing traffic model with a high similarity to the actual situation according to the relevant information of the vehicle travel; modify the existing traffic model according to the actual situation to obtain a traffic model suitable for the actual situation.

6. The overall autonomous driving method of a vehicle according to claim 1, characterized in that, Using the starting point, destination, travel purpose, passengers / goods, and time requirements of the vehicle as inputs, generate an overall self-driving plan for the vehicle by using the traffic model, specifically including: Using the starting point, destination, travel purpose, passengers / goods, and time requirements of the vehicle as inputs, generate multiple overall self-driving plans by using the traffic model; For each of the overall self-driving plans, calculate the comprehensive level / weight of the overall self-driving plan according to the level / score of each evaluation target of each vehicle in the multiple evaluation targets, the target weight of each evaluation target, and the vehicle weight of each vehicle; the evaluation targets include: safety, travel efficiency, comfort, energy consumption, purposefulness, and real-time performance; the purposefulness includes evaluation items related to travel purpose, destination or time. Different travel purposes have different requirements for time, route selection, speed, and lanes. The vehicle weight is determined based on the vehicle type, number of passengers, vehicle value, and goods carried by the vehicle; Select the overall self-driving plan with the highest comprehensive level / weight as the overall self-driving plan for the vehicle.

7. A method for overall autonomous driving of a vehicle according to claim 1, characterized in that, Set the vehicles / obstacles in the traffic model to have a finite number of states to improve real-time performance; the states of the vehicle include: accelerating, decelerating, stopping, turning left, turning right, ascending, descending, changing lanes, overtaking, and avoiding.

8. A method for overall autonomous driving of a vehicle according to claim 1, characterized in that After generating the overall self-driving plan for the vehicle, it further includes: obtaining the relevant information of the human-driven vehicle related to travel, and predicting the expected travel behavior of the human-driven vehicle; sending the overall self-driving plan for the vehicle to the human-driven vehicle to guide the driver to drive the human-driven vehicle.

9. A method for overall autonomous driving of a vehicle according to claim 1, characterized in that, After generating the overall self-driving plan for the vehicle, it further includes: sending the overall self-driving plan for the vehicle to the non-self-driving vehicle to remind / advise the driver to drive along the vehicle trajectory of the overall self-driving plan for the vehicle.

10. A method for overall autonomous driving of a vehicle according to claim 1, characterized in that, The vehicle performs self-driving in at least one of the ways of mutually providing information, jointly negotiating to formulate an overall self-driving plan for the vehicle, and completely driving according to the overall self-driving plan for the vehicle.

11. A method for overall autonomous driving of a vehicle according to claim 1, characterized in that, The vehicle independently analyzes a driving plan suitable for the vehicle according to the basic self-driving instructions; the basic self-driving instructions include: speed limit, lane limit, following, overtaking, turning, and automatic cruise.

12. The overall autonomous driving method of a vehicle according to claim 1, wherein After generating an overall autonomous driving solution for a vehicle, it further includes: managing at least one of traffic lights, bridges, railings, guiding lines / lights, peak lanes, traffic flow / road closures, and traffic signs according to the overall autonomous driving solution for the vehicle.

13. An overall automatic driving device for a vehicle, characterized in that, It includes: A wireless transmission component for receiving the overall autonomous driving solution for a vehicle generated by using the overall autonomous driving method for a vehicle according to any one of claims 1-12. A control component for controlling the vehicle to automatically drive according to the overall autonomous driving solution for the vehicle.

14. An intelligent transportation system, characterized in that, It includes: A traffic information acquisition device for acquiring information related to the driving of the vehicle. The information related to the driving of the vehicle includes: information about the vehicle, basic driving information, and driving information. A server for constructing a traffic model based on the information related to the driving of the vehicle; the traffic model includes: road width, road curvature / angle, traffic flow, vehicle position / speed / braking distance, driving purpose, destination, time requirement, urgency, passenger / cargo driving requirements of the vehicle, obstacle position / size, weather conditions, special situations, and other content affecting traffic; using the starting point, destination, driving purpose, passengers / items, and time requirements of the vehicle as inputs, generating an overall autonomous driving solution for the vehicle by using the traffic model; sending the overall autonomous driving solution for the vehicle to all autonomous driving vehicles in the traffic model, and each of the autonomous driving vehicles performs autonomous driving according to the overall autonomous driving solution for the vehicle.

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