RU2774261C1 - Method for controlling the movement of vehicles with driver assistance systems in the environment "intelligent transport system - vehicle - driver" - Google Patents

Abstract

FIELD: automotive industry.

SUBSTANCE: invention relates to the automotive industry. In the method for controlling the movement of vehicles driven by a driver with driver assistance systems in the IVD environment, in the traffic control center of the road infrastructure of the ITS with the help of additional stationary fuel assemblies, they perform recognition, identification, determine the exact location, geometric dimensions, speeds and directions of movement of all vehicles, determine distances between the vehicle and/or obstacles, perform the formation, monitoring, updating and processing of databases. And also, taking into account the received data of the traffic control center DCC DI ITS, with the help of stationary information processing units of the PU of additional fuel assemblies, possible points of intersection and/or dangerous approaches with moving and fixed obstacles on the trajectory of each vehicle are predicted, and, if a forecast of possible intersection points is identified and/or close encounters with other vehicles, and/or obstacles, and/or DI objects, calculate additional maneuvers and/or trajectories and speeds of movement of each vehicle to prevent collisions and transmit the predicted information and calculation results to the electronic on-board devices of the UVTS, ​​in each of the ECUs of the vehicle surrounding the UHTS.

EFFECT: increase in efficiency and reliability of performance of TVS DCC DI tasks of traffic control in the ITV environment is achieved.

3 cl

Description

The invention relates to the automotive industry, in particular, to methods and devices for improving the systemic active safety of vehicles, including unmanned vehicles.

The method relates to the field of ensuring road safety by improving the efficiency and reliability of the traffic control of vehicles (TS), controlled by the driver (UVTS), with driver assistance systems in the "intelligent transport system - vehicle - driver" (ITV) environment. The method can be used to organize the safe movement of ground vehicles, including unmanned ones.

In the process of developing modern and promising vehicles on the roads, one of the ways to solve the most important problem - ensuring the safety of vehicles on the roads, is the use of driver assistance systems (active safety systems (ADAS) (ADAS - automatic data acquisition system)). Operating experience shows that the mass operation of vehicles with driver assistance systems has already made it possible to reduce accidents on the roads, reduce the time each vehicle travels along a given route, reduce fuel consumption by vehicles and reduce environmental pollution.

Modern driver assistance systems (active safety systems (ADAS)) potentially help the driver to prevent a large number of vehicle collisions in typical traffic situations. Expanding the functions of advanced driver assistance systems by solving additional problems of collision avoidance, for example, due to more accurate recognition of vehicles, the ability to cross their trajectories of movement and all possible obstacles in real operating conditions, monitoring the condition and destruction of tires, suspension, steering (RS) , detaching the wheels from the hubs and solving other problems will improve the efficiency of these systems. However, as the experience of their operation shows, for a number of reasons, these systems in the on-board version cannot in principle ensure the performance of all the necessary functions of the vehicle, achieve a radical increase in the efficiency and reliability of their operation, especially in the road and climatic conditions of the Russian Federation.

In order for the driver assistance system to accurately, reliably and efficiently fulfill the technical task assigned to it and its purpose, that is, the driver assistance function, the "ideal" on-board driver assistance system, like any other "ideal" on-board ADAS system, must ensure reliable recognition of all vehicles and obstacles on the roads, determine their size, dimensions, distances to them and between them, and using hardware, software and computing tools to evaluate the parameters of their movement (such as dimensions, speeds and accelerations, positioning of all vehicles, the possibility of crossing their trajectories traffic, etc.), process the received data taking into account information about the normal operation environment, including road, weather, climatic and other conditions, generate and transmit recommendations to the driver of the UVTS in accordance with the tasks it solves, and implement control signals and control commands.

To improve the efficiency, reliability and accuracy of computing operations by an “ideal” driver assistance system (or ADAS system) for the formation of recommendations for the driver and control signals and control commands that are guaranteed to ensure the safety of each vehicle and exclude the possibility of collisions with other vehicles and obstacles, demolitions, skids, rollovers and other traffic accidents under all traffic conditions and normal operating environment (SSE) parameters, it is necessary that the “ideal” driver assistance system (like any other ADAS system) additionally ensures the solution and implementation of at least the following main tasks and functions:

1. Main tasks:

- precise positioning of UVTS;

- recognition of road markings and determination of the exact location of the UVTS on the lane;

- recognition of road signs;

- recognition of surrounding vehicles and obstacles, including those moving and located in the front and rear hemispheres of the UHTS;

- stabilization of the UVTS distance to the front obstacle;

- stabilization of the UHTS trajectory on a given route according to the data of technical vision and navigation systems;

- automatic braking of UVTS in front of an obstacle;

- changing the lane of the UVTS, taking into account the position of all surrounding vehicles and obstacles, including for their urgent detour;

- stabilization of the speed of the UVTS on the ascents and descents;

- stabilization of longitudinal and transverse slides of UVTS;

- recognition of traffic policemen and their commands;

- detection of dangerous bumps and/or other dangerous road conditions;

- recognition of traffic lights and data of their countdown timers;

- the passage of unregulated intersections of equivalent roads in compliance with the current traffic rules;

- recognition of special signals, sirens and / or "beacons", etc. emergency vehicles that require the UVTS to perform a maneuver to skip them with a lane change or change in other traffic parameters;

- automatic parking UVTS with a choice of place;

- detection of dangerous misalignments and other malfunctions of wheels and hubs of UVTS;

- detection of dangerous wear of protectors and cords of UVTS tires;

- detection of dangerous wear of the suspension and steering (RU) of the vehicle;

- detection of dangerous pressure drops in UVTS tires.

2. The main functions of monitoring the parameters of the UVTS and the surrounding vehicles, their movement and the SSE, with the help of which the determination is made:

- technical speed of UVTS;

- longitudinal velocity of the center of mass of the UVTS;

- the speed of approach of the UVTS with the passing front and / or rear vehicles;

- drift speed of the front wheels of the UVTS;

- speed of skidding of rear wheels of UVTS;

- the danger of occurrence of the speed of overturning of the HVTS;

- slip speed of the driving wheels of the UVTS;

- longitudinal and transverse accelerations of UVTS;

- longitudinal slips of UVTS wheels;

- angles of rotation of the steered wheels of the UVTS;

- coordinates of the location of the UVTS in the Cartesian coordinate system attached to it;

- the speed of the UVTS, limited by road signs in their coverage area;

- the speed of the UHTS, limited by the detection range of moving and fixed obstacles in the traffic lane;

- distances of the UVTS to the vehicle and obstacles in the front and rear hemispheres on the lane;

- top values of sliding friction coefficients (characteristics of adhesion of wheels to the road surface);

- air pressure in UVTS tires;

- overheating temperatures of tires and brakes UVTS;

- the recommended speed of movement of the UVTS with a flat tire;

- dangerous speed of rupture of the cord of UVTS tires;

- types, condition and quality of the road surface;

- climatic and weather conditions;

- parameters of the surrounding air; illumination, time of day;

- control of the state of adequacy, sleep or wakefulness of the driver;

- the technical condition of a driver-controlled vehicle (UVTS), its controls, the technical condition of driver assistance systems (ADAS systems), their components and sensors.

3. Other priority functions for ensuring safe traffic, which, in addition to the main ones, include, for example, such as:

- stabilization of the safe speed and distance of movement from the UVTS to the vehicle and obstacles in the front and rear hemispheres;

- prevention of collisions of UVTS with mobile and fixed vehicles and obstacles;

- stabilization of longitudinal slips of UVTS wheels; stabilization of the exchange rate stability of the UVTS;

- prevention of overturning of UVTS;

- automatic braking of the UVTS without blocking the wheels to a complete stop on real surfaces (dry and wet asphalt, snow, ice, gravel, sand, soil, paving stones) in front of moving and / or fixed obstacles in the front hemisphere on the lane, taking into account the parameters of its movement and Vehicle in the rear hemisphere, control of a safe distance to the nearest vehicle;

- emergency stop of UVTS in case of critical malfunctions (tire pressure drop, overheating of tires and brakes, weakening of wheels to hubs, unacceptable wear of tire cords, etc.) and accidents;

- control of the state of adequacy, sleep or wakefulness of the driver.

- optimization of the composition and creation of favorable conditions for the operation of sensors, hardware and actuators, technical and computing facilities (FA) in the "intelligent transport system - vehicle - driver" environment, which ensure their most efficient and reliable operation under all traffic conditions and under all parameters of the normal operation environment.

In the absence of a solution to even a part of the listed tasks and functions, the known on-board driver assistance systems of vehicles and even in the future cannot, in manual or automatic mode, reliably and reliably solve the tasks assigned to them to radically increase the reliability and efficiency of the entire transport system.

Known methods for ensuring road safety by equipping vehicles with driver assistance systems (ADAS systems), for example, such as: active cruise control, traffic assistant in traffic jams; emergency and auxiliary braking systems; blind spot monitoring, lane change assistant; recognition of road signs, markings and pedestrians; lane control; assistant when leaving the parking lot in reverse and many others.

For example, a driver assistance system for avoiding collisions with obstacles is known (see PRC published application No. CN106915347A, applicant TIANJIN HUAFANG TECH CO LTD, publ. 07/04/2017), which includes a radar distance determination module, a machine vision module , interacting with the radar distance module, brake control module and steering wheel control module. A front obstacle avoidance is performed when the vision system does not detect obstacles in adjacent lanes. If obstacles are detected in neighboring lanes, then the vehicle is braked according to the data of the radar module for determining the distance in the front hemisphere.

The main disadvantages of the driver assistance system according to the application of the PRC No. CN106915347A are:

1. Insufficient efficiency and reliability of the system as a whole.

2. Insufficient efficiency and reliability of the driver assistance system in real operating conditions at different speeds of the UVTS, when the roadway and markings on it are dirty, if there is water, snow, sand, mud, ice on it, during rain or snowfall, when smoke, dust and gas content in the air, at high, low and ultra-low ambient temperatures, with pollution and damage to the windshields of UVTS, with insufficient lighting, sun glare, with poor quality of road markings and in the presence of other adverse factors.

3. Insufficient efficiency and reliability of the operation of technical and computing facilities and sensors of on-board driver assistance systems resulting from the presence of such unfavorable conditions for their operation as the impact of negative climatic and weather conditions, vibrations, shock loads, etc.

4. Insufficient efficiency and reliability of providing assistance to the driver by each on-board ADAS system, resulting from the lack of a solution in it of all the necessary and sufficient set of tasks for managing and implementing the functions of ensuring road safety due to the inability to provide and place in the memory of an electronic on-board unit (ECU) absolutely all of their varieties.

5. The lack of the possibility of a reliable and effective solution of such problems as, for example:

- recognition of traffic policemen and their commands;

- detection of pits, dangerous irregularities and other volume defects of the road surface, especially in the presence of snow, water, ice on the road surface;

- the passage of unregulated intersections of equivalent roads in compliance with the current traffic rules; recognition of "beacons" and other signals of emergency vehicles that require a maneuver to skip them with a change in lane or change in other traffic parameters;

- detection of dangerous misalignments of wheels and hubs of UVTS;

- detection of dangerous wear of UVTS tire cords;

- detection of dangerous wear of the suspension and steering, as well as other dangerous states of sensors, assemblies, systems and assemblies of the UVTS.

The disadvantages of the driver assistance system according to the application of the People's Republic of China No. CN106915347A are also: the lack of identification of the friction coefficients of the tires of the vehicle with the surface, which determines the upper limit of braking deceleration without blocking the wheels, as well as the absence of a deceleration limit determined by the distance to the rear obstacle on the lane.

A vehicle control device is known (see US Published Application No. US 20190210597 A1, applicants DENSO CORPORATION, publ. 07/11/2019), designed to prevent collisions with objects in the front hemisphere, which consists of a control unit and collision prevention, an mechanisms, a block for setting the states of actuators, including the brake system and steering. Obstacle avoidance is provided at the initiative of the driver, without taking into account the automatic detection of obstacles in adjacent lanes, both simultaneously with automatic braking and without it.

In addition to the above main disadvantages of the technical solution according to the application of the People's Republic of China No. CN106915347A, with the exception of the function of assessing the state of the actuators in this technical solution, the disadvantages of this device are also: the absence of restrictions on the amount of braking deceleration necessary to prevent collisions with a rear passing vehicle and / or an obstacle , insufficient reliability of data on the coefficients of sliding friction of the wheels, determined from the readings of the ambient temperature sensor or from the weather map.

A device is known for assessing the coefficient of adhesion to the road surface and a method for its implementation (see the patent of the Republic of Korea No. KR20180123366, the applicant Korea Automotive Technology Institute, publ. determining the maximum deceleration of a wheeled vehicle. The device for estimating the coefficient of friction using anticipatory braking may include: a braking coefficient adjustment unit configured to adjust the braking force distribution coefficient of the front and rear wheels; a detector for determining the amount of slip and the coefficient of friction in the contact of the tire with the road surface during warning braking in accordance with the coefficient of distribution of braking forces of the front and rear wheels; with the road surface.

In addition to the above main disadvantages of the technical solution according to the application of the People's Republic of China No. CN106915347A, with the exception of the implementation in this technical solution of the function of identifying the top values of the sliding friction coefficients of wheels by trial test braking to determine the maximum deceleration of a wheeled vehicle, different from the previously indicated disadvantage of the device according to the patent of the Republic of Korea No. KR1020180123366 is a limited ability to identify the parameters of tire grip with the surface conditions of warning braking. In conditions of movement on surfaces with a variable friction coefficient, this method is inapplicable. Under driving conditions, braking time intervals, including auxiliary ones, take up to 10% of the total time, which does not allow us to consider the identification data as adequate.

An automobile automatic control device for avoiding collisions with obstacles is known (see the previously mentioned PRC published application No. CN 106915347 A, applicants TIANJIN HUAFANG TECH CO LTD, publ. 07/04/2017), which includes a radar distance determination module, a vision module, a control module brakes and steering wheel control module. A front obstacle avoidance is performed when the vision module does not detect obstacles in adjacent lanes. If obstacles in adjacent lanes are detected, then braking is performed according to the data of the radar module for determining the distance in the front hemisphere.

In addition to the above main disadvantages of the technical solution according to the application of the People's Republic of China No. CN106915347A, the disadvantage of the device is also the lack of identification of the coefficients of adhesion of tires to the surface, which determines the upper limit of braking deceleration without blocking the wheels, as well as the absence of a deceleration limit determined by the distance to the rear obstacle on the lane.

Also known is a system for warning and avoiding collisions of a vehicle (see US patent No. US 8527172 B2, applicants Nikolai K. Moshchuk [US], Shih-Ken Chen [US], Chad T. Zagorski [US], Aamrapali Chatterjee [US], publ. 03.09.2013), which uses combined automatic heading and brake control and contains means for determining threshold values that identify the time before a collision with an obstacle and based on the analysis of the movement parameters of the object, including the coefficients of adhesion of tires to the surface, and obstacles, either a warning is selected, either braking or avoiding an obstacle.

In addition to the above main disadvantages of the technical solution according to the application of the People's Republic of China No. CN106915347A, the disadvantage of the system according to US patent No. US8527172B2 is also the lack of movement parameters of the rear passing obstacle when braking on the lane and the absence of a limit on the amount of braking deceleration necessary to prevent collision with the rear passing obstacle.

A known method for controlling an automatic vehicle (ATS) (see US patent No. US 9378424 B2, applicant RICOH COMPANY, LTD, publ. 06/28/2016) is characterized by the fact that a mathematically processed image of the roadway with scanning elements, mathematically transform it, obtain a real image of the roadway, mathematically transform the real image of the roadway and obtain images of the areas of location of the scanning elements and foreign elements of the image and sequentially remove images of foreign elements, compare the remaining image of the roadway with the scanning elements, the results generate control actions for UHTS.

In addition to the above main disadvantages of the technical solution according to the PRC application No. CN106915347A, the disadvantage of the control method according to US patent No. US 9378424 is also the low variability of images obtained from the long-term memory of the computer, respectively, the high required memory and computing capabilities of the computer processor.

There is also a known method of controlling an automatic vehicle (see US patent No. US 9489583 B2, applicant DENSO CORPORATION, publ. 11/08/2016) characterized in that a mathematically processed image of the roadway with scanning elements is extracted from the long-term computer memory of the UHTS driver assistance system, mathematically converting it in accordance with the observation point (position of the UVTS on the roadway) into an image in perspective, obtaining a real image of the roadway, mathematically transforming the real image of the roadway and obtaining images of the areas of location of the scanning elements and extraneous image elements and successively removing these images of foreign elements, the remaining image of the roadway with scan elements is compared with the mathematically transformed real image of the roadway, and based on the results, control actions are generated for the UVTS.

In addition to the above main disadvantages of the technical solution according to the PRC application No. CN106915347A, the disadvantage of the control method according to US patent No. US 9378424 is also the difficult task of obtaining a mathematically processed image due to the sequential removal of individual image elements performed by the ADAS system on board the vehicle.

The closest in technical essence is the system of adaptive cruise control of the vehicle with stabilization of course stability and a method for its implementation, which contains the largest number of similar actions and devices used in the method of operation, such as a road information and navigation module, a millimeter-wave radar module, a road grip coefficient estimation module, a minimum safety distance determination module, a vehicle maximum curve speed calculation module, an ESC real-time estimation module of the vehicle's center of mass side slip angle and yaw rate, and an adaptive speed control module (see PRC Publication No. CN109733398, applicants NANJING UNIVERSITY OF AERONAUTICS AND ASTRONAUTICS, published 05/10/2019). The proposed system stabilizes the speed and distance, taking into account the restrictions for the control of directional stability, based on the use of information about the future trajectory of movement entering the navigation system of the vehicle and data on the coefficients of adhesion of the wheels to the surface, which, for the above reason, is taken by us as a prototype .

In addition to the above main disadvantages of the technical solution according to the US patent No. US 9378424 B2, the disadvantage of the system according to the PRC application No. CN109733398 is also the lack of consideration for the condition of the tires and their wear, as well as the level of vibration accelerations and slippage of the drive wheels when choosing a safe speed for stabilizing the movement.

The methods of operation of the on-board driver assistance systems installed on vehicles, in a generalized form, consist in the analysis of traffic data from sensors by such systems, the identification of risks and the timely warning of drivers or, in the absence of actions by drivers to eliminate risks, such as collisions, in re-warning the driver using visual, audio and tactile elements, as well as in the implementation of small actions on the controls in order to warn drivers and force them to take the necessary actions. In the event of critical situations, in order to eliminate or reduce the level of consequences, on-board systems take on the functions of influencing the vehicle traffic controls.

The most important common shortcomings of on-board driver assistance systems and vehicle ADAS systems are the low efficiency and reliability of their operation due to the lack of the necessary set of data on board and the impossibility of solving each of the entire necessary and sufficient set of tasks and performing functions to ensure them, without the solution of which it is impossible to achieve the highest possible accuracy of the control signals and control commands generated by each of the on-board driver assistance systems.

Among such a necessary and sufficient complex, as noted above, at least the following tasks can be attributed:

- current positioning of UVTS;

- recognition of road markings and determination of the exact location of the UVTS on the lane;

- recognition of road signs;

- recognition of surrounding vehicles and obstacles, including moving and located in the front and rear hemispheres;

- stabilization of the UVTS distance to the front obstacle;

- stabilization and correction of the UHTS trajectory on a given route according to the data of technical vision and navigation systems;

- automatic braking of UVTS in front of an obstacle; changing the lane of the UVTS, taking into account the position of all moving and stationary surrounding vehicles and obstacles, including for their urgent detour;

- stabilization of the speed of the UVTS on the ascents and descents;

- stabilization of longitudinal and transverse slides of UVTS;

- recognition of traffic policemen and their commands;

- detection of dangerous volumetric defects and/or other dangerous conditions of the road surface (for example, puddles of water, snow, frost, etc.;

- recognition of traffic lights and data from their countdown timers and other non-regulated traffic rules states and traffic lights;

- the passage of unregulated intersections of equivalent roads in compliance with the current traffic rules;

- recognition of special signals such as symbols, sirens and/or beacons, etc. emergency vehicles that require a maneuver to skip them with a change in lane or change in other traffic parameters;

- When solving a complex of the listed tasks, it is also necessary to ensure monitoring of the following parameters of the technical condition of the UVTS:

detection of dangerous misalignments and other dangerous conditions of wheels and hubs of UVTS;

- detection of dangerous wear of cords and other dangerous conditions of UVTS tires;

- detection of dangerous wear and other dangerous conditions of the suspension and steering (RU) of the UVTS; detection of pressure drops in tires dangerous for UVTS and other dangerous conditions with a change in their shape.

When solving a complex of the listed tasks, it is also necessary to ensure monitoring of the following parameters of movement and safety of the air transport vehicle:

- technical speed of UVTS; longitudinal velocity of the center of mass of the UVTS;

- the speed of approach of the UVTS with the passing front and / or rear vehicles and other obstacles;

- drift speed of the front wheels of the UVTS;

- speed of skidding of rear wheels of UVTS;

- the danger of occurrence of the speed of overturning of the HVTS;

- slip speed of the driving wheels of the UVTS;

- longitudinal and transverse accelerations of UVTS;

- longitudinal slips of UVTS wheels;

- angles of rotation of the steered wheels of the UVTS;

- coordinates of the exact location of the UVTS in the associated Cartesian coordinate system;

- the speed of the UVTS, limited by road signs in their coverage area;

- the speed of the UHTS, limited by the detection range of moving and fixed obstacles in the traffic lane;

- distances to the vehicle and other obstacles in the front and rear hemispheres of the UVTS on the lane;

- top values of coefficients of sliding friction (characteristic of adhesion of UVTS wheels with the road surface); air pressure in UVTS tires; overheating temperatures of tires and brakes UVTS;

- recommended speeds of movement of the UVTS with a flat tire and / or with a docking device;

- dangerous speed of rupture of the cord of UVTS tires;

- types, condition and quality of the road surface;

- climatic and weather conditions;

- parameters of the weather condition of the surrounding air; illumination, season, time of day;

- control of the state of adequacy, sleep or wakefulness of the driver;

- the technical condition of the vehicle, its controls, the technical condition of driver assistance systems (ADAS systems), their components and sensors.

At the same time, each driver assistance system (ADAS system), in addition to solving the main tasks and the functions implemented in it, must ensure the implementation of at least the following additional functions (if they are not implemented in the system):

stabilization of the safe speed and distance of movement from the UVTS to the surrounding vehicles and obstacles in the front and rear hemispheres;

- prevention of collisions of UVTS with mobile and fixed vehicles and obstacles;

- stabilization of longitudinal slips of UVTS wheels; stabilization of the exchange rate stability of the UVTS; prevention of overturning of UVTS;

- automatic braking of UVTS without blocking the wheels to a complete stop on real surfaces (dry and wet asphalt, snow, ice, gravel, sand, soil, paving stones) in front of a movable and / or fixed obstacle in the front hemisphere on the lane, taking into account changes in the distance to the vehicle means in the rear hemisphere;

- emergency stop of UVTS in case of critical malfunctions (tire pressure drop, overheating of tires and brakes, weakening of wheels to hubs, unacceptable wear of tire cords, etc.) and accidents;

- control of the state of adequacy, sleep or wakefulness of the driver;

- optimization of the composition and creation of favorable conditions for the operation of sensors, hardware and actuators, technical and computing facilities (FA) in the "intelligent transport system - vehicle - driver" environment, which ensure their most efficient and reliable operation under all traffic conditions and under all parameters of the normal operation environment.

The solution of the listed tasks in each separate on-board driver assistance system (ADAS system) of the UVTS and the implementation of the listed additional functions in it in full is theoretically and technically not feasible. Moreover, the creation of such an “ideal” on-board driver assistance system cannot make it more reliable and efficient due to the following features of ADAS systems operation:

1. Excessive complication of the software and hardware of such an “ideal” system intended for use on vehicles can even lead to a decrease in the reliability of its operation and service life, to an increase in cost and to a qualitative change in maintenance requirements, and to the requirement for constant updating for elimination of identified software hazards when used.

2. The efficiency and reliability of the operation of modern sensors and on-board driver assistance systems (ADAS systems) are insufficient for a comprehensive provision of road safety, especially in the conditions of Russian operation of vehicles, resulting from low winter temperatures, low population, large expanses and length of the road network, diversity weather and climatic conditions from arctic in the north to subtropical in the south and specific mountainous, from specific requirements caused by the shape of roads (hilly, serpentines, long ascents and descents), high mountains and seasonality of transport communication (winter roads and summer roads in the arctic zone).

For example, there are limitations of vision systems in terms of efficiency and reliability of their operation at vehicle speeds up to 50 km/h on Ford, Mazda, FIAT, VW, Volvo, Mitsubishi, Subaru vehicles, and identified during testing of vision system sensors (cameras, radars, lidars, stereo cameras) conducted by Thatcham Research Center (Great Britain, document No. 13-0168, 2016), it was found that stereo cameras were the most effective, but only in a narrow speed range of the UVTS. Further in the process tests, the operation of stereo cameras was reliable and ensured that ADAS systems excluded collisions with obstacles (vehicles) only at speeds of air traffic control up to 50 km/h, radars worked effectively at air traffic speeds only up to 30 km/h, lidars - up to 20 km/h and integrated systems consisting of radars and lidars - at speeds of air traffic control only up to 35 km / h.

Under operating conditions, on-board driver assistance systems (ADAS systems) are characterized by a large number of false positives. The magnitude of false positives of sensors and these on-board systems as a whole is influenced not only by their insufficiently high technical parameters, but also, for example, by factors such as time of day, road, climatic and other conditions. Thus, external conditions in the form of pollution or damage to protective and windshields, poor lighting in tunnels, insufficient lighting of traffic lanes at night, blinding by the headlights of oncoming cars, adverse weather and climatic conditions (hoarfrost , snowfall, icing, heavy fog, smoke, rain), poor condition of road markings, sun glare, coloring of the surrounding infrastructure (buildings, trees, etc.), making it difficult to identify and recognize road signs against their background, and other conditions. The operability and reliability of sensors and electronic components of on-board systems is also limited by unfavorable temperature conditions of the external environment - above plus 40-50°C and below minus 20-40°C, which are typical for some regions of the Russian Federation, for example, such as the Crimea, the Arctic or Caucasus. The characteristics of sensors and on-board systems are also adversely affected by vibration and shock loads acting on them when driving in vehicles.

Thus, the sensors of modern on-board driver assistance systems (ADAS systems) of current vehicles and the on-board driver assistance systems themselves are not perfect and have very limited operational ranges for the effectiveness of controlled and implemented parameters when the vehicle is moving, for example, speed, which reduce their efficiency and reliability. .

The listed disadvantages of on-board driver assistance systems (ADAS systems) should also include:

- the need for duplication of systems for the reliable performance of all the functions necessary and sufficient to provide effective and reliable assistance to the driver and, accordingly, to ensure the safety of the traffic of the air transport vehicle, which must be performed by the onboard system of each air transport vehicle;

- the need for the on-board driver assistance system (ADAS system) of the UVTS to perform an excessively large number of functions that are simultaneously duplicated in all other vehicles;

- insufficient efficiency in the execution of the processes of generating and transmitting control signals and control commands to the control drives of the UVTS, due to the need to analyze a large amount of data;

- insufficient accuracy of the recognition function and the lack of information on the exact positioning of the surrounding vehicles, on the weather condition of the normal operation environment, and other functions;

- lack of sufficient information on a large number of expected and performed maneuvers by each of the vehicles on the road relative to other road users with a rapid change in road conditions;

- lack of operational and accurate data on the road surface and their accounting, for example, according to such indicators as: type, material, condition and quality of the road surface, its parameters, the presence of rutting, holes, potholes, cracks and other volumetric defects, the presence of snow, hoarfrost, ice, ice, water, dirt road condition, such as rutting of the pavement of an unpaved road;

- lack of operational and accurate data and taking into account climatic conditions on the route, such as, for example, air temperature and pressure, wind speed and direction, clear, cloudy or rainy weather, the presence of precipitation, fog, dust, smoke and air pollution with gaseous harmful substances and solid particles;

- lack of data on the time of year and day and their accounting when driving in traffic (summer, winter, day, night, etc.);

- insufficient quality of solving the problems of recognizing surrounding vehicles, moving and stationary obstacles, road markings, road signs, curbs (curbs), traffic lights and signals of traffic controllers using vision sensors (cameras, radars, thermal imagers, ultrasonic sensors, lidars, etc. .), which is associated with insufficient reliability and efficiency of on-board systems and their sensors, a decrease in the reliability and efficiency of their operation during operation due to their pollution, deterioration of lighting conditions, at high and ultra-low ambient temperatures, during precipitation, fog, dust and gas contamination air, smoke, snow cover on roads and adjacent territories, as well as with other circumstances, which leads to a decrease in the effectiveness of the technology for recognizing road images and the quality of solving problems of traffic control of the UVTS;

- the complexity of the hardware-software execution of on-board driver assistance systems and other ADAS systems, associated with the need to solve duplicate tasks of the same type in the systems of all vehicles for analyzing the traffic situation and generating control signals and control commands. A further increase in the complexity of electronic control systems, which should include the "ideal" driver assistance systems (ADAS systems), can lead to a decrease in the efficiency and reliability of their work; an overestimated array of data entering the "ideal" computing units of the on-board driver assistance systems and ADAS systems from on-board sensors for measuring the motion parameters of each UVTS, such as longitudinal and lateral accelerations, wheel speeds, steering position, the state of control units of control drives, as well as data on surrounding objects coming from sensors of vision systems (radar, lidar, video cameras, stereo cameras, parking sensors, etc.), navigation, communications, etc., from sensors and devices for measuring climatic and weather conditions and from other sensors and external systems (navigation, monitoring), which are received and processed in the computing units of on-board systems;

- the need to use in the "ideal" driver assistance systems or ADAS systems the most complex mathematical apparatus, control algorithms, software to perform the entire complex of data processing when solving problems and control functions;

- the possibility of false alarms and failures in the operation of even “ideal” driver assistance systems or ADAS systems, their sensors, which occur in different weather and climatic conditions and depend on the illumination of objects, sun glare, time of day and other factors, as well as depending on deficiencies in software products, malfunctions and failures in the operation of on-board systems and their sensors;

- theoretically known and developed in practice "ideal" on-board driver assistance systems and ADAS systems, their components and sensors have constantly changing resistance to newly emerging software viruses, have a limited service life and limited ranges of reliable and efficient operation when performing individual control functions during movement of vehicles in all operating modes and speeds of the UVTS, during acceleration, braking, when driving on gravel, sandy and dirt roads, climatic and weather conditions, when driving on a wet and snowy road surface, when icy, as well as in shock and vibration road loads.

These shortcomings in the methods of operation of known and “ideal” driver assistance systems and on-board ADAS systems can be radically eliminated in the “intelligent transport system - vehicle - driver” environment by upgrading them using stationary fuel assemblies TsUD DI in real time in areas actions of DI by implementing with their help most of the main and auxiliary functions, for example, such as recognition, identification, determination of the geometric dimensions, speeds and directions of movement of all vehicles, recognition, identification, determination of the geometric dimensions, speeds and directions of movement of moving and the exact location of stationary obstacles; determination of distances between vehicles and/or obstacles; formation, monitoring, updating and processing of databases according to specified algorithms for the normal operation environment (SSE) in the areas of DI coverage, such as, for example, maps of the area, type, quality and condition of the road surface, road markings, road signs, traffic lights and modes of their work, according to the climatic conditions of the SSE; Obtaining additional data from the satellite navigation system and/or, for example, from additional stationary fuel assemblies, and/or on-board ECUs of the vehicle using communication systems, for example, more accurate positioning of the vehicle, obstacles and RDI objects, air pollution with gaseous harmful substances, for example , nitrogen oxides, ozone, formaldehyde, carbon monoxide, particulate matter; processing additional data according to specified algorithms; forecasting possible points of intersection and/or dangerous approaches with moving and fixed obstacles on the trajectory of each vehicle, and in case of forecasting possible points of intersection and/or dangerous approaches with other vehicles and/or obstacles and/or CI objects, calculation of additional maneuvers, and / or the trajectory and speed of movement of each vehicle for collision avoidance and the transmission of predictive information and calculation results to the vehicle ECU.

The location and inclusion in the work, if necessary, of DI objects allows you to adequately assess the real effectiveness of their work in the ITS-TS-driver environment.

After receiving the predicted information and calculation results in each of the ECUs of the vehicle based on the results of processing the data received from the MCC, as well as, if necessary, additional data obtained, for example, from a satellite navigation system and / or, for example, from stationary fuel assemblies, on-board ECUs of other Vehicles generate control signals according to predetermined algorithms and transmit them to the graphic information output device and / or to indicators of calculated and / or dangerous states of the corresponding UVTS to inform the driver of the corresponding UVTS, which, based on the information received, performs further actions to control the movement of the UVTS, for example, by influencing the traction control systems / controls of the internal combustion engine of the UVTS, brakes, steering gears and / or controls of other systems, components and assemblies of the UVTS, and in the event of critical conditions and / or insufficiency or in the absence of driver actions to eliminate critical conditions, the ECU UVTS form and transmit control commands control of the motion control drives of each vehicle from the environment of the UVTS under the control of the corresponding driver of the vehicle. The implementation of the proposed method for controlling the movement of vehicles (V) with driver assistance systems in the "intelligent transport system-vehicle-driver" environment will help improve road safety of vehicles, radically reduce accidents, reduce the time of movement (being on the road) of each vehicle, reduction of fuel consumption and environmental pollution by vehicle emissions.

The technical problem to be solved by the present invention is to improve the efficiency and reliability of traffic control, including driver-controlled vehicles (UVTS), automated vehicles with a driver assistance system and unmanned vehicles by performing most of the main and auxiliary functions of driver assistance systems. with the help of computing and technical means of the transport infrastructure of the intelligent transport system in the "intelligent transport system - vehicle - driver" environment.

The technical problem posed is solved by the fact that, according to the method proposed as an invention for controlling the movement of vehicles (TC), controlled by the driver (UVTS), with driver assistance systems in the environment "intelligent transport system-vehicle-driver" (ITV), technical and computing means (TVS) of the ITV environment, including electronic on-board devices (ECU) of vehicles (TS) and ECU TVS of the traffic control center (TCC) of the road infrastructure (DI) of the intelligent transport system (ITS), in accordance with which signals are recorded and processed from sensors and systems of TVS TS and TVS TsUD DI, as well as signals from the satellite navigation system, transmit them to information processing units (PUs), which determine the values of the parameters and physical variables of each vehicle and the environment surrounding the UVTS (normal operation environment of the SSE), compare them with the calculated and / or with the boundary values characterizing the calculated and / or critical state to each vehicle, transmit the results of comparison and calculations to the control units (CU), which generate control signals and transmit them to the output devices of graphic information and / or indicators of calculated and / or dangerous states to inform the respective drivers, who determine and form further actions to control of the EVTS, and in the event of critical conditions and / or in case of insufficiency or absence of actions of a specific EVTS driver to eliminate critical conditions, control signals are generated and transmitted to the actuating drives for controlling the movement of a specific OVTS and other vehicles surrounding the OVTS, then, in the control center in real time, in addition to the previously indicated regular actions, a set of additional actions are performed in the area of responsibility of the control center, including such actions in which:

- carry out recognition, identification, determine the exact location, geometric dimensions, speeds and directions of movement of all vehicles in the area of responsibility of the control center;

- carry out recognition, identification, determine the exact location, geometric dimensions, absolute, relative speeds and directions of movement of moving and fixed obstacles, for example, such as people, motorcyclists, electric scooters, cyclists, animals, road curbs, foreign objects, cobblestones, volumetric defects pavement, pits;

- determine the distances between vehicles and/or obstacles;

- perform the formation, monitoring, updating and real-time processing of databases according to specified algorithms, in accordance with the state of the normal operation environment (SSE) in the areas of DI, such as, for example, according to maps of the area, by type, quality and condition road surface, according to road markings, road signs, traffic lights and their modes of operation, according to the climatic conditions of the SSE, for example, such as wind speed, temperature, air pressure and humidity, the presence and types of precipitation, dust and smoke in the air, fog, the presence on the road canvas in real time of fine moisture (hoarfrost, dew, drizzle), water, snow, ice, dirt;

- receive additional data from the satellite navigation system and / or, for example, from additional stationary fuel assemblies, on-board ECUs surrounding the vehicle using communication systems, such as, for example, more accurate positioning of the vehicle, obstacles and DI objects, air pollution with gaseous harmful substances , for example, such as nitrogen oxides, ozone, formaldehyde, carbon monoxide, particulate matter, and process them according to specified algorithms in real time;

- predicting, taking into account the data obtained by the MCC DI ITS, using stationary PU of additional fuel assemblies, possible points of intersection and / or dangerous approaches with moving and fixed obstacles on the trajectory of each vehicle, and in case of identifying a forecast of possible points of intersection and / or dangerous approaches with other vehicles and/or obstacles, and/or with CI objects, calculate additional maneuvers, and/or trajectories and speeds of movement of each vehicle to avoid collisions and transmit the predicted information and calculation results to the ECU of the UVTS and other vehicles surrounding the UVTS;

- at the same time, in each of the ECUs, control signals are generated based on the results of processing the data received from the MCC, as well as, if necessary, additional data received, for example, from a satellite navigation system and / or, for example, from stationary fuel assemblies, and / or on-board ECUs of the vehicle surrounding the UVTS, on the basis of which the final control signals are generated according to the specified algorithms and transmitted to the graphic information output device and / or to the indicators of the calculated and / or dangerous states of the UVTS to inform the driver, who, based on the information received, performs further actions to control the movement of the UVTS, for example, by influencing the systems / controls of the traction, brakes, steering gears and / or controls of other systems, components and assemblies of the UVTS, such as the power plant, propulsion unit, chassis, and in the event of critical conditions and / or insufficiency or in the absence of driver actions to eliminate critical conditions standing, the ECU of the UVTS form and transmit, bypassing the driver, control commands to the motion control drives of each UVTS and other vehicles surrounding the UVTS.

At the same time, the set technical problem is also solved by the fact that in the proposed method for controlling the movement of vehicles (V) with driver assistance systems in the environment "intelligent transport system - vehicle - driver" additional fuel assemblies of the traffic control center and / or on-board electronic control unit of the vehicle additionally monitor the execution of control commands by the motion control drives of each vehicle, evaluate the accuracy of their execution and, if necessary, recalculate the control commands and retransmit additional adjusted control commands through the PU of each vehicle to the ECU of each vehicle and/or to the motion control drives of each vehicle.

Also, the technical problem posed is also solved by the fact that in the method of controlling the movement of vehicles (TC) with driver assistance systems in the environment "intelligent transport system - vehicle - driver", with additional scanning and mathematical processing, flat and stereo images are obtained by using a road scanning device. blades with two linear photosensitive devices installed permanently in the DI and/or in the vehicle on a gyro-stabilized platform.

The claimed method for controlling the movement of vehicles with driver assistance systems in the "intelligent transport system-vehicle-driver" (ITV) environment is carried out as follows and at the same time it is disclosed how the following advantages are achieved, which arise only from comparison with similar operation when controlling the UVTS (Vehicles controlled by the driver) and the use of only on-board sensors and TVS systems of the controlled vehicle.

Technical and computing means (TVS) of the ITV DI environment can be diverse, and therefore their full, detailed and comprehensive description is very difficult and is not included in the scope of the proposal.

Technical and computing means (TVS) of the ITV environment, including electronic on-board devices (ECU) of vehicles (TS) and ECU TVS of the traffic control center (TCC) of the road infrastructure (CI) of the intelligent transport system (ITS), in accordance with the proposed method, register and processing signals from sensors and systems TVS TS and TVS TsUD DI, as well as signals from the satellite navigation system, transmit them to information processing units (PUU). CU determine the values of the parameters and physical variables of each vehicle and the environment surrounding the UVTS (normal operation environment of the SSE), compare them with the calculated and / or with the boundary values characterizing the calculated and / or critical state of each vehicle, transfer the results of comparison and calculations to the control units (CU), which generate control signals and transmit them to the output devices of graphic information and / or indicators of calculated and / or dangerous states to inform the relevant drivers, who determine and form further actions to control their UVTS, and in the event of critical conditions and / or in case of insufficiency or absence of actions of a specific driver of the UVTS to exclude critical conditions, control signals are generated and transmitted to the actuating drives for controlling the movement of a specific UVTS and other vehicles surrounding it.

Then, in accordance with the proposed method, during its implementation, additional stationary fuel assemblies of the traffic control center DI ITS additionally perform a set of actions in real time, including, for example, such actions as:

1. Recognition, identification, determination of the exact location, geometric dimensions, speeds and directions of movement of all vehicles in the area of responsibility of the control center.

2. Recognition, identification, determination of the exact location, geometric dimensions, absolute, relative speeds and directions of movement of moving and fixed obstacles, for example, such as people, motorcyclists, electric scooters, cyclists, animals, road curbs, foreign objects, cobblestones, volumetric defects pavement, potholes.

3. Determination of distances between vehicles and/or obstacles.

4. Formation, monitoring, updating and real-time processing of databases according to specified algorithms in accordance with the state of the normal operation environment (SSE) in the areas of DI, such as, for example, according to maps of the area, according to the type, quality and condition of the road surface , according to road markings, road signs, traffic lights and their modes of operation, according to the climatic conditions of the SSE, for example, such as wind speed, temperature, air pressure and humidity, the presence and types of precipitation, dust and smoke in the air, fog, the presence on the roadway of real-time mode of fine moisture (hoarfrost, dew, drizzle), water, snow, ice, dirt.

5. Obtaining additional data from the satellite navigation system and / or, for example, from additional stationary fuel assemblies, on-board ECUs surrounding the vehicle using communication systems, for example, such as: more accurate positioning of the vehicle, obstacles and objects of radiation sources, air pollution with gaseous harmful substances, such as nitrogen oxides, ozone, formaldehyde, carbon monoxide, particulate matter, and process them according to specified algorithms in real time.

6. Forecasting (taking into account the data obtained by the MCC DI ITS using stationary PU of additional fuel assemblies) of possible intersection points and / or dangerous approaches with moving and fixed obstacles on the trajectory of each vehicle, and in case of identifying a forecast of possible intersection points and / or dangerous approaches with other vehicles and/or obstacles and/or CI objects, calculation of additional maneuvers and/or trajectories and speeds of movement of each vehicle to avoid collisions.

7. Transfer of predicted information and calculation results to the ECU of the UVTS and other vehicles surrounding the UVTS.

In accordance with the proposed method, in each of the ECUs of the vehicle, based on the results of processing the data received from the MCC, as well as, if necessary, additional data received, for example, from a satellite navigation system and / or, for example, from stationary fuel assemblies, on-board ECUs surrounding vehicles, form control signals according to specified algorithms and transmit them to the graphic information output device and / or to the indicators of the calculated and / or dangerous states of the UVTS to inform the driver, who, based on the information received, performs further actions to control the movement of the UVTS, for example, such as , by influencing the systems / controls of traction, brakes, steering mechanisms and / or controls of other systems, components and assemblies of the UVTS, such as a power plant, propulsion unit, chassis, and in the event of critical conditions and / or insufficiency or the absence of the driver's actions to exclude critical conditions, the vehicle ECU is formed and transmitted, bypassing parent, control commands to the motion control drives of the UVTS and each vehicle surrounding the UVTS.

When implementing the method, also with the help of additional stationary fuel assemblies of the traffic control center and / or the electronic control unit of the vehicle, they additionally monitor the execution of control commands for the motion control drives of each vehicle, evaluate the accuracy of their execution and, if necessary, recalculate the control commands and retransmit them through the CU each vehicle, additional corrected control commands to the ECU of each vehicle and/or to the motion control drives of each vehicle.

Finally, in the method for controlling the movement of vehicles, with additional scanning and mathematical processing, flat and stereo images are obtained by using a roadbed scanning device with two linear photosensitive devices installed permanently in a DI and/or in a vehicle on a gyro-stabilized platform.

As follows from the above sequence of actions of a generalized description of the method of controlling the movement of vehicles with driver assistance systems in the "intelligent transport system - vehicle - driver" environment, assistance to the driver of each UVTS is carried out by jointly coordinated work of stationary regular and additional technical and computing facilities of the center traffic control of the ITS road infrastructure and electronic on-board devices (on-board technical and computing facilities) of the UVTS, and the latter are only assigned the functions of: processing data received from the MCC, as well as, if necessary, additional data received, for example, from a satellite navigation system and / or , for example, from stationary fuel assemblies, on-board ECUs for UVTS; generation of control signals according to predetermined algorithms and their transmission to the output device of graphic information and/or to indicators of calculated and/or dangerous states of the UVTS to inform the driver. The latter, on the basis of the information received, performs further actions to control the movement of the UVTS, for example, by influencing the systems / controls of traction, brakes, steering gears and / or controls of other systems, components and assemblies of the UVTS, such as a power plant, propulsion , chassis. In accordance with the proposed method, upon the occurrence of critical conditions and / or insufficiency or in the absence of driver actions to eliminate critical conditions, the UVTS ECU generates and transmits, bypassing the driver, control commands to the motion control drives of the UVTS and each vehicle surrounding the UVTS, which makes it possible to reduce the calculated - computational load on the regular on-board computing facilities of the UVTS and each specified vehicle, as well as to increase the reliability of operation and traffic safety in general.

When working together according to specified algorithms, stationary standard and additional fuel assemblies of the traffic control center of the ITS road infrastructure, containing at least stationary blocks for recognition, identification, determination of the parameters of the SSE, detection and recognition of vehicles and obstacles using vision systems with additionally installed stationary sensors , communication and navigation units, information processing units and real-time control units additionally perform a set of actions in the area of responsibility of the control center, including such actions as:

- perform at least recognition, identification, determination in the area of responsibility of the traffic control center of the ITS road infrastructure of the geometric dimensions, speeds and directions of movement of all vehicles, moving and fixed obstacles, for example, such as people, motorcyclists, electric scooters, cyclists, animals , road curbs, foreign objects, cobblestones, other volume defects of the road surface, such as ruts, pits, etc.;

- determine the distances between vehicles and/or obstacles;

- perform the formation, monitoring, updating and processing of databases according to the specified algorithms for the SSE in the areas of CI, for example, by such methods and means as by maps of the area, by type, quality and condition of the road surface, by road markings, road signs, traffic lights and their operating modes, according to the climatic conditions of the SSE, for example, such as wind speed, temperature, air pressure and humidity, the presence and types of precipitation, dust and smoke in the air, fog, the presence of moisture, water, snow, ice, mud on the roadway; receive additional data from the satellite navigation system and / or, for example, from additional stationary fuel assemblies, on-board ECUs surrounding the vehicle using communication systems, for example, more accurate positioning of the vehicle, obstacles and objects of radioactivity, air pollution with gaseous harmful substances, for example, oxides nitrogen, ozone, formaldehyde, carbon monoxide, solid particles, and process them according to specified algorithms; taking into account the data obtained by the MCC DI ITS, using stationary PU of additional fuel assemblies, they predict zones dangerous for drivers and possible points of intersection and / or dangerous approaches with moving and fixed obstacles on the trajectory of each vehicle;

- in case of revealing a highly probable forecast of the appearance of dangerous zones, possible intersection points and / or dangerous approaches of the UVTS with other vehicles and / or obstacles, and / or DI objects, additional maneuvers and / or trajectories and speeds of movement of each vehicle are calculated to overcome the dangerous zones , collision avoidance and transmit predictive information and calculation results to the ECU of vehicles surrounding the HVTS;

- at the same time, in each of the ECUs of the vehicle, based on the results of processing the data received from the MCC, as well as, if necessary, using additional data received, for example, from a satellite navigation system and / or, for example, from stationary fuel assemblies, on-board ECUs of the vehicle surrounding the UHTS , form control signals according to specified algorithms and transmit them to the graphic information output device and / or to indicators of calculated and / or dangerous zones and vehicle states to inform each driver, who, based on the information received, performs further actions to control the movement of his UVTS, for example, by influencing the systems / controls of the engine thrust, brakes, steering gears and / or controls of other systems, components and assemblies of the UVTS, such as a power plant, propulsion unit, chassis, and in the event of critical conditions and / or insufficiency or the absence of the driver's actions to exclude critical conditions, the ECU of the vehicle is formed and transmitted, bypassing driver, control commands to the motion control drives of each vehicle from the surrounding UVTS. Such carrying out of emergency actions makes it possible to increase the efficiency of prevention and accelerate the overcoming of an extraordinary situation, since only standard and additional fuel assemblies of the MCC ITS can comprehensively solve the problem with it for the entire flow of vehicles in road traffic.

Permanently installed and protected from environmental influences, standard and additional fuel assemblies of the TsUD ITS, taking into account the receipt of additional signals from the satellite navigation system and additional information, from the system for monitoring the parameters of the SSE and from the ECU of the vehicle surrounding the UHTS, using stationary and protected from adverse environmental conditions environments of sensors of vision systems (for example, radars, video cameras, stereo cameras, lidars, thermal imagers, ultrasonic sensors, etc.), taking into account their own databases updated in real time on the environment of normal operation, with higher accuracy, recognize and identify mobile and stationary vehicles and other obstacles on the road, such as people, motorcyclists, electric scooters, cyclists, animals, trees, road curbs, foreign objects, cobblestones, volumetric defects in the road surface, such as rutting, cracks, pits and other volumetric obstacles , determine geometric dimensions, speeds and directions of movement, at least in front of and behind the moving vehicle, the surrounding UHTS, moving and fixed obstacles, the distance between the vehicle and / or obstacles.

Permanently installed and protected blocks for processing information of stationary fuel assemblies of the MCC of the ITS road infrastructure perform calculations according to the specified programs and transfer their results to the control unit of the MCC of the ITS road infrastructure. The MCC control unit in its area of responsibility of the ITS road infrastructure integrates (analyzes, summarizes and calculates) the information coming, for example, from the information processing unit of the MCC TVS, from the satellite navigation system, from the ECU of all vehicles surrounding the ITS, forms in real time based on the results of processing and calculations, control signals and control commands and transmits them to the ECU of the TVS of the corresponding vehicle, which mainly perform the functions of comparing real actions and monitoring their implementation, which makes it possible to radically reduce the computational load on the standard on-board computing facilities of the ECU of all vehicles and increase their speed.

At the same time, to implement the actions of the method, on-board fuel assemblies of the UVTS are used, which contain at least a device for outputting graphic information, indicators of calculated and / or dangerous states, control drives, electronic on-board devices, including blocks for communication, receiving and processing information. Based on the results of incoming control signals and control commands from the control unit of stationary fuel assemblies of the TsUD ITS, as well as information from satellite navigation systems and systems for monitoring the parameters of the SSE, as well as the unit for receiving and processing information, the ECU forms UHTS, taking into account its own and externally received data according to specified simplified control signals to the algorithms and transmits them to the graphic information output device and / or to the indicators of the calculated and / or dangerous states of the active safety system to inform the driver of the UVTS, who, based on the information received, performs and / or corrects his further actions or the on-board computer to control the movement of his UVTS, for example, by influencing the systems / controls of traction, brakes, steering mechanisms and / or controls of other systems, components and assemblies of the UVTS, such as a power plant, propulsion unit, chassis, and in the event of critical conditions and / or insufficiency or absence and actions of the driver to eliminate critical conditions, the ECU of the corresponding UVTS form and transmit, bypassing the driver, control commands to the motion control drives of the UVTS and each of the vehicles surrounding it.

Further, regular stationary and additional fuel assemblies of the MCC traffic control center and / or an electronic control unit of the UVTS additionally monitor the execution of control commands by the driver and / or drives of each UVTS, evaluate the accuracy of their execution and, if necessary, recalculate the control commands and retransmit additional corrected control commands to the ECU of each UHTS and / or to the control drives and each of the vehicles surrounding it.

The sequence of implementation of the proposed method can be carried out in the following stages of its implementation.

Stage 0 (preparatory). Identification of all vehicles is carried out by TVS of the traffic control center DI ITS, which can be carried out, for example, in the following sequence: before the start of movement, for each vehicle, an individual identification code is set or determined, which the additional TVS of the MCC use to identify it. In the TVS version, the MCC can, at the request of consumers, independently form the route of each vehicle separately.

Usually, full recognition, identification, determination of the geometric dimensions, speeds and directions of movement of all vehicles, their routes of movement, as well as all obstacles on the roads and on the routes of movement by each known separate on-board driver assistance system and the ADAS UVTS system, are not performed, for example, from for lack of data and / or insufficient computing power of the on-board system, which has a negative impact on the accuracy and adequacy of the assessment of the traffic situation, the control signals generated by it, the control commands transmitted to the control drives through the UVTS computer.

Therefore, in the proposed method, further, subsequent actions following the identification of the vehicle, namely the operations of monitoring, generating, updating and processing databases in real time in the SSE environment using permanently installed and protected from the environment, with sufficient computing performance of additional technical and computing means of the DCC are performed at subsequent stages.

Stage 1. Further monitoring and formation of databases, maps of the area and the organization of traffic on route maps of the vehicle from the TVS of the MCC is carried out by measuring and making changes to the databases in real time of operational data on the width, capacity of roads in both directions, on the type , the quality and condition of the road surface, road markings, road signs, traffic lights and their modes of operation, permitted speeds, emergency situations, planned or urgent construction and road works, the condition of road curbs, extraneous obstacles, for example, such like, about objects on the carriageway, about cobblestones, defects in the road surface, ruts, potholes, holes, cracks, about all vehicles, motorcycles, electric scooters, cyclists, people, animals in the transport network, other three-dimensional obstacles and objects.

At the same time, due to the fact that the reliability and quality of recognition of road markings, signs, traffic lights and their modes of operation, all vehicles, motorcyclists, electric scooters, cyclists, people, animals in the transport network, foreign objects, cobblestones, road surface defects, for example, potholes, pits, cracks, etc., performed by well-known on-board vision systems of driver assistance systems and ADAS systems of all vehicles, cannot be higher than 95-99% due to their technical and functional limitations and the possibility of efficient operation of sensors and control systems movement at all speeds of the vehicle under different environmental conditions (rain, snow, fog, smoke, high and ultra-low ambient temperatures, etc.) and other conditions that impede the operation of the system and its sensors, for example, arising from wear, pollution on-board systems sensors, pollution or changes in the reflectivity of the roadway (glare), road signs and markings, falling out precipitation, smoke, fog, gas contamination of the air environment with gaseous harmful substances and solid particles, due to the appearance of solar glare from surrounding objects, overlapping signs with overall vehicles, trailers, tree leaves, and also due to other reasons, which leads to the lack of achievement of the necessary the highest possible efficiency and reliability of operation using only on-board driver assistance systems and ADAS systems.

In view of the foregoing, the formation of reliable and reliable information on the other listed database items using only on-board driver assistance systems and ADAS systems for each self-driving vehicle is a complex of extremely complex tasks that are largely unresolved at the current level of technology development. In turn, even the partial absence of such information significantly reduces the accuracy of the calculations performed by the UVTS ECU, the quality and accuracy of the information provided to the driver.

At the same time, in the proposed method, centralized monitoring and formation of databases and maps of the area using standard and additional organizational, technical and computing tools and sensors of the central control room, for example, located at installation sites and tied to the types of road signs, traffic lights and their modes of operation , road markings, information about emergency situations, planned or urgent construction and road works, about road curbs, foreign objects, cobblestones, other defects in the road surface, that is, about rutting, potholes, pits, cracks, other three-dimensional obstacles and objects with practically 100% reliability is solved with the help of intelligent organizational and technical solutions implemented with the help of DI and stationary systems of technical vision, navigation, communication TVS TsUD.

It is important to note that the efficiency and reliability of the permanently installed sensors of vision systems are significantly higher compared to on-board sensors, and they can be located only in places of the greatest danger of obstacles (which significantly reduces the load on the onboard fuel assemblies and on the entire fuel assemblies of the MCC, since they act locally and can be turned on if necessary). Under unfavorable conditions (fog, rain, snowfall, dustiness, smoke in the surrounding air, etc.), the ability to recognize surrounding vehicles, objects at long distances using standard video cameras, lidars, and radars of on-board driver assistance systems UVTS drops sharply. When implementing the steps of the method using stationary fuel assemblies of the MCC, an effective solution to this problem is achieved due, for example, to such measures as reducing the distances between these permanently installed sensors and / or the ability to connect additional temporarily “sleeping” sensors, which can only be located in places of greatest danger the appearance of obstacles or adverse environmental conditions, such as, for example, the appearance of morning fog in hollows, the possibility of falling stones from cliffs, etc., the use of additional means of positioning and navigation of all vehicles on the roads, the use of radar technologies and other technologies in technical vision systems , as well as by storing data on the nearest time position and state of obstacles in the memory of the TVS MCC, especially in places of the greatest danger of their occurrence.

Stage 2. Updating and processing databases and maps of the area about the technical and weather condition of the road and the environment and the requirements of traffic rules when implementing the proposed method using additional stationary measuring instruments of the TVS TsUD and / or data received from the TVS TsUD, for example, about road signs, markings, traffic lights and their modes of operation, data from weather stations and related air weather monitoring services, wind speed, air temperature, pressure and humidity, presence and types of precipitation, dust, smoke and air pollution, fog , own data on the weather condition of the environment in real time and the presence of fine moisture, water, snow, ice, dirt on the roadway, fluctuations and changes in annual, seasonal, daily, weather and other conditions are performed in real time.

In the TVS databases, the MCCs store additional information about the nearest position and the state of the road situation by entering and storing, for example, the coordinates of new and changed road signs and obstacles, a calculated forecast of the dynamics of changes in the weather state of the environment in real time on the route of movement.

Usually, updating data on the weather state of the environment in normal operation mode (in comparison with the average statistical SSE) using the TVS of known on-board driver assistance systems and ADAS systems is expensive, very complex, and in terms of a number of indicators and in terms of their diagnostics and prediction impossible. The lack of accounting for such data, or the insufficient accuracy of the measured parameters, also has a negative impact on the operational efficiency and reliability of the on-board driver assistance systems and ADAS systems.

In turn, when implementing the proposed method, the centralized implementation of these monitoring technologies is close to the highest level of efficiency and reliability with the help of standard and additional technical and computing facilities of the DCC with sufficient computing performance, as well as the technologies used by them for processing, receiving and monitoring forecasts from weather stations and related services based on average data and reliable forecasts of real changes in the local weather conditions of the environment of normal operation.

Stage 3. When implementing the proposed method, obtaining additional information and data about the environment during normal operation is efficiently and reliably carried out using additional stationary technical and computing tools of the TsUD DI ITS, including computing blocks for identification, determining the SSE, detecting and recognizing vehicles and obstacles with systems technical vision and stationary sensors, communication and navigation systems, computing blocks for processing information with sufficient computing performance. The listed permanently installed blocks, systems, sensors of fuel assemblies of the MCC are, in accordance with this proposal, elements of the road infrastructure. They can be reliably protected from all climatic and weather influences, from vibration and shock loads typical for driver assistance systems and ADAS systems of vehicles, and can also be made in an anti-vandal design or removed from the carriageway and protected from the direct impact of vandals, for example, placed on lighting or fence posts and/or walls. Additional local and/or distributed sensors of vehicle identification systems, measurements of climatic and weather factors, TVS technical vision systems can be permanently installed along roads on the side and/or above the carriageway, and/or inside the roadway and can also be reliably protected from vandals, climatic and weather influences, from vibration and shock loads and be connected to work if necessary.

The main type of information implemented by the stationary technical and computing means of the MCC DI is data on the environment, the SSE and the positioning of the vehicle. With the help of stationary sensors of the vision systems of the MCC DI ITS, a variety of things are performed: digital, infrared, laser, ultrasonic, radar, etc. scanning of the terrain, vehicles and obstacles with the necessary effects, depending on the weather and other environmental conditions, coverage, multiplicity, frequency and accuracy, inaccessible to on-board driver assistance systems and ADAS systems.

When implementing the proposed method, the scanning of the dynamics of the road situation using the TVS TsUD can be performed continuously simultaneously over the entire transverse width of the roadway, for example, with linear photosensitive devices (LPD) or, which is more preferable, the LPP for near and far scanning is equipped with the appropriate necessary lens with a zoom , which allows you to create a stereo image from these scans. For their further operation, LFP in a stationary version can be oriented and fixed when they are installed along all axes and horizontally. The images obtained as a result of scanning, after appropriate transformation, are compared with images from databases and their significant changes that affect the traffic situation, for example, an increase in traffic intensity, are revealed. In addition, from the satellite navigation system and / or from the ECU of the surrounding vehicles, additional data is obtained using the communication system, such as about the navigation of the vehicle in the traffic flow, weather conditions and SSE parameters in real time and process them according to specified algorithms.

Also, with additional scanning, flat and/or stereo images are obtained by using a roadbed scanning device with two linear photosensitive devices installed permanently at a height h above the roadway and/or in a vehicle on a gyro-stabilized platform. A gyro-stabilized platform is a device in which, regardless of external influences on the vehicle, all disturbances in the position of the vehicle around and / or relative to three coordinate axes are parried by means known in modern technology, while the position of the two linear photosensitive devices of the scanning device does not change relative to the horizontal plane . The first near linear photosensitive device can be directed vertically down and is designed to obtain a real near scan of the roadbed and road conditions, and the second far linear photosensitive device can be directed at a given reference angle y to the horizontal and is intended to obtain a real far scan to confirm the dynamics of change road conditions and the condition of the roadbed. Both LFPs are always equally located relative to the horizontal plane.

LFP for near and far scans is supplied with the appropriate necessary lens, for example with a zoom lens, which allows you to create various flat, perspective and stereo images from these scans. Such interaction of two LFPs makes it possible to create, on the one hand, a full volumetric profile of the roadway with all its defects, and, on the other hand, the roadway in the future by means that are minimal in terms of price and operating costs and with the possibility of subsequent geometric or other simple mathematical transformation of digitized scans into flat, perspective and/or stereo images of the roadway.

The first near LFP is designed to obtain a high-resolution near scan and can be positioned so that the scanning plane is always vertical, i.e. perpendicular to the horizontal plane and mostly perpendicular to the roadway, and perpendicular to the vertical plane of the location of the center line of the roadway and serves to obtain current images of the vehicle. The second far LFP can be located at a given angle y to the horizontal in the direction of the axial line of the roadway and is designed to obtain a far scan with the greatest coverage of the roadway. In this case, the center line of the roadway can be of any shape - straight, arcuate, broken (this happens in the case of intersections or turns to side roads near the main, scanned roadway).

All real distances to the scanning elements on the near and far scans can be calculated based on geometric relationships or measured, for example, using a laser rangefinder method.

When implementing the actions of the method on the UHTS, the signals from the sensors of the TVS TsUD DI are transmitted sequentially to the computing blocks for identification, determining the SSE, detecting and recognizing the vehicle and obstacles, by isolating the changing images of the vehicle from the scan image and from the computing identification blocks, the data is transmitted to the computing blocks for processing information, in which complex processing of all data is carried out in accordance with their priority and with the algorithms embedded in the program. Scanning data processing consists in: obtaining with the help of sensors, for example, such as two LFPs, the current real flat or stereo image of the roadway with vehicles on it, moving and stationary obstacles, road infrastructure equipment; in the geometric and mathematical transformation of each current real image; in the analysis and calculation of the current angle of rotation of their steering wheel, the current control of the brake pedals, determining the presence of other vehicles, obstacles and building a view of the current state of the roadway.

Processing of scanned data is greatly simplified, since mono and stereo images consist of multiple signals received in sequence and their arrangement in a block corresponding to a single image frame, similar to line and vertical scanning in a television frame. With the help of simple transformations, each block of frames can be changed as necessary to obtain flat or perspective or stereo images, which are compared with images from databases in order to detect a change in the road situation in a dangerous direction.

When implementing the proposed method, complex data processing takes into account real-time updated information about existing road signs, markings, traffic lights and their modes of operation, which subsequently allows, when generating control signals, to inform the driver in a timely manner and with high accuracy about the necessary order of his actions in full in accordance with the rules of the road and other requirements and rules established by road signs, markings, traffic lights and traffic controllers.

In the process of complex processing, operational information is also taken into account, entered into maps of the area and databases with the help of TVS TsUD road infrastructure on construction and road works, emerging volumetric defects in the road surface (for example, ruts, pits, potholes, cracks, foreign objects on or in road surface), data received from the satellite navigation system and / or from the ECU of the surrounding vehicles can also be taken into account, for example, on positioning, driving conditions of vehicles, motorcyclists, electric scooters, cyclists in traffic, on the weather condition and parameters of the SSE, on the map and terrain, positioning and movement parameters of each vehicle, motorcyclist, electric scooter, cyclist on lanes, distances between them, their geometric dimensions, speeds and directions of movement, acceleration and deceleration, at least in relation to the front and rear moving vehicles, about all other moving and fixed obstacles.

Depending on the tasks and types of roads (motorway, highway, multi-lane, single-lane, secondary, unpaved, etc.), permanently installed and / or removable, protected from vandals, weather and video cameras, stereo cameras, radars, lidars, thermal imagers, ultrasonic sensors and many others. Efficient and reliable recognition and identification on the roads in real time of moving and stationary vehicles, people, motorcyclists, electric scooters, cyclists, animals, fallen trees, newly appeared foreign objects, cobblestones, curbs and other obstacles on the roadway, road surface damage, for example , rutting, cracks, pits and other volumetric defects can be carried out using additional local and / or distributed sensors of fuel assemblies of the TsUD, the complex of which is selected from the condition of the most efficient receipt and implementation of specific information in real time, for example, in conditions of the appearance of morning fog in hollows the most informative will be ultrasonic or radar sensors for detecting vehicles and obstacles, and in sunny weather, television means will be the most effective there.

Performing on board the UVTS the above operations to recognize, identify the vehicle, other obstacles, to obtain information and take into account changes in the normal operation environment using the TVS of known on-board driver assistance systems and ADAS systems in conditions of precipitation, smoke, fog, road pollution and sensors of technical systems vision, for example, frost, snow, dust, dirt, condensate from fog, dew, water from puddles, at different times of the day, at high and low ambient temperatures and under many other circumstances, is an extremely difficult task, in many ways not solved by the on-board ECU of the vehicle using the state of the art. The implementation of these operations in on-board driver assistance systems and ADAS systems leads, due to the need to install a large number of various sensors on board, to a significant complication of the design and software products of systems, a decrease in the reliability and efficiency of their operation, an increase in the cost of both systems and their software and TS in general.

The lack of performance of even a part of the listed functions, as well as the low quality of their performance and the lower reliability of the operation of on-board sensors and the vehicle ECU in comparison with stationary ones in all ranges of speeds of the air traffic control system and the parameters of the SSE, has a negative impact on the efficiency and reliability of the on-board driver assistance systems and ADAS systems. So, for example, those that were during testing of sensors of on-board driver assistance systems (multichannel vision systems, video cameras, radars, lidars, stereo cameras) limited in terms of efficiency and reliability of their operation at vehicle speeds up to 50 km/h on Ford, Mazda, FIAT, VW, Volvo, Mitsubishi, Subaru, carried out by Thatcham research center, UK (document No. 13-0168, 2016), it was found that in a narrow speed range the efficiency of stereo cameras turned out to be the highest, but insufficient for practical purposes. During the tests, the operation of the stereo cameras was reliable and ensured that the ADAS systems excluded collisions with obstacles (vehicles) only at vehicle speeds up to 50 km/h, radars worked effectively only at vehicle speeds up to 30 km/h, lidars - only up to 20 km/h. km/h, and integrated systems consisting of radars and lidars - only at vehicle speeds up to 35 km/h. Thus, even the sensors of new vision systems used in driver assistance systems and ADAS systems in modern vehicles are far from perfect and have very limited operating ranges for efficient and reliable operation.

The magnitude of false positives of on-board sensors and vehicle active safety systems as a whole is influenced not only by the technical parameters of sensors and systems, but also by the time of year, day, road, climatic and other conditions. A negative impact on the increase in the number of false positives of sensors and vision systems, as shown by the results of tests by FSUE "NAMI" at the Dmitrovsky auto test site, is exerted by external conditions in the form of pollution, scuffs or other damage to windshields and protective glasses, poor lighting at night (insufficient lighting traffic lanes, blinding headlights of oncoming cars), bad weather and climatic conditions (snowfall, icing, heavy fog, rain), road markings, sun glare from the roadway and surrounding objects, color schemes of the surrounding infrastructure (buildings, trees, etc.). ), the location of road signs, etc. The operability and reliability of the on-board sensors and electronic components of the BTS EMS is also limited by the temperature conditions of the external environment, for example, such as above +40-50°C and below -20-40°C.

As the results of our tests of 3 lane departure warning systems (LDW) on 3 vehicles (DAF, Mercedes-Benz Sprinter and Volkswagen Crafter) showed, all tested systems were not effective when the road marking lines were “snowy” at the level 15% or more.

In a generalized form, according to the test results, it was found that on-board driver assistance systems partially or completely do not work:

- at night (a number of SPDV systems),

- when crossing a partially worn broken line marking in good weather conditions, in "diffused fog" and "solid fog", with the "dipped headlights" turned on and, to a greater extent, with the "high beam headlights" turned on,

- when you turn on the "low beam headlights" and there is an oncoming "high beam headlights" at night,

- when crossing a solid wet marking line,

- when crossing a worn broken marking line even in good weather conditions,

- in the daytime summer season in clear weather with pollution of the solid line of 70% or more,

- when "activating the alarm" and at the same time crossing a solid marking line.

It follows from the foregoing that the efficiency and reliability of modern on-board driver assistance systems and AD AS systems and sensors used in vehicles are far from perfect, especially when they work in Russian operating conditions.

When implementing the proposed method, based on the data received from sensors and computing identification units, determining the SSE, detecting and recognizing surrounding vehicles and obstacles, permanently installed computing units for processing information of TVS TsUD, which have sufficient computing performance, also predict possible points of intersection and / or dangerous UHTS approaches to other vehicles, moving and fixed obstacles on the trajectory of each vehicle, and in the case of forecasting possible intersection points and / or dangerous approaches to other vehicles and / or obstacles, additional maneuvers and / or trajectories, speeds of movement and braking process are calculated of each vehicle to prevent a collision and with the help of communication systems transmit predictive information and calculation results to the electronic blocks for informing drivers and controlling the UVTS and surrounding vehicles.

Stage 4. When implementing the proposed method in each of the ECUs of the vehicle, based on the results of processing data received from the computing blocks for processing information of the TVS TsUD, as well as the results of processing additional data received from the satellite navigation system and / or standard TVS TsUD DI and from on-board ECUs other vehicles, generate control signals according to specified algorithms and transmit them to the graphic information output device and / or to indicators of calculated and / or dangerous states of the vehicle to inform the driver corresponding to the UVTS, who, based on the information received, performs further actions to control the movement of his vehicle, for example, by influencing the systems / controls of traction, brakes, steering mechanisms and / or controls of other systems, components and assemblies of the vehicle, such as a power plant, propulsion unit, chassis, and in the event of critical conditions and / or insufficiency or in the absence of actions of the specified driver to eliminate critical states, the ECU of the vehicle generates and transmits, bypassing the driver, control commands to the motion control drives of the specified UVTS and each vehicle surrounding it.

When implementing the actions of the method, a significant acceleration of the processes of determining traffic parameters, predicting the limiting speeds of dangerous conditions and regulating the safe speed of the vehicle can only be implemented in an integrated system consisting of stationary fuel assemblies of the TsUD DI and a complex of on-board ECUs of the vehicle. In such a system, the software devices of stationary fuel assemblies of the TsUD DI, which have sufficient computing power, operate with the possibility of implementing in each of them the software execution of the functions of the block for determining the motion parameters, the block for predicting the boundary speeds of dangerous states, the block of the vehicle speed controller, allow in this design to more accurately determine the movement parameters of all vehicles, predict the limiting speeds of dangerous states and regulate the safe speed of movement of each individual vehicle. When using in calculations the limiting speed of approach to a passing obstacle in the form of the sum of the speed of a passing obstacle and the difference between the current value of the distance and its limiting value, multiplied by a real coefficient specified in the tuning data, it is possible to perform an accurate assessment of the minimum safe distance between vehicles.

After receiving the control commands, the UHTS ECU is transmitted to the graphic information output device and/or to the indicators of calculated and/or dangerous states of the driver assistance systems of the corresponding vehicle to inform the driver.

When the driver performs actions in accordance with the requirements of the control signals, for example, guaranteed stabilization of the safe speed of the wheeled vehicle with an extended vector of speed limits, including the boundary speeds of approach to a passing vehicle both from the rear and from the side, and from the front, slipping of the driving wheels, demolition of the front and skidding of the rear wheels, rollover of the vehicle, pressure drop and rupture of tire cords, the presence of "rolling" in the wheel scheme and limiting speeds in the area of traffic signs, as well as vibration acceleration levels.

However, in the event of the onset of critical conditions and / or insufficiency or in the absence of driver actions to eliminate critical conditions, the ECU of each such UVTS and the vehicles surrounding it form and transmit, bypassing the driver, control commands to the motion control drives of the UVTS and the vehicles surrounding it, such as , systems / controls for traction, brakes, steering mechanisms and / or controls for other systems, components and assemblies of all relevant vehicles, for example, such as power plant, propulsion, chassis.

Stage 5. In the electronic control unit of each vehicle and / or additional fuel assemblies of the traffic control center, they additionally monitor the execution of commands to control the operation of the steering drive, brake and accelerator (traction) pedals, gear lever (automatic or manual - if available), each The vehicles evaluate the accuracy of their execution by the driver or the corresponding drive and, if necessary, in the stationary fuel assemblies of the MCC DI, the control commands are recalculated and additional adjusted control commands are retransmitted to the control drives of each vehicle.

Stage 6. During additional scanning and mathematical processing, flat and stereo images are obtained by using a roadbed scanning device with two linear photosensitive devices installed permanently with additional fuel assemblies of the traffic control center and / or in the ECU of the vehicle on a gyro-stabilized platform, which, to control the current state of road conditions, are compared with the images available in the memory and databases of the MCC DI.

Among the main advantages, ie. The technical results achieved when implementing the proposed method for controlling the movement of vehicles with driver assistance systems in the "intelligent transport system - vehicle - driver" environment in comparison with existing on-board driver assistance systems and AD AS systems should include:

1. Increasing the efficiency and reliability of the solution and implementation of TVS TsUD DI traffic control tasks by identifying vehicles, monitoring, creating, updating and processing databases and terrain maps in a normal operation environment, recognizing and identifying moving and stationary vehicles and other obstacles on the roads , data processing according to single centrally defined algorithms, prediction of possible intersection points and / or dangerous approaches of the vehicle between themselves, as well as with moving and fixed obstacles, calculation of additional maneuvers, and / or trajectories and speeds of movement of each vehicle to prevent collisions and / or dangerous approaches with other vehicles and with moving or fixed obstacles on the trajectory of each vehicle, and in the case of predicting possible points of intersection and / or dangerous approaches with other vehicles and / or obstacles, calculating additional maneuvers, and / or trajectories and speeds of movement of each vehicle for collision avoidance, etc. due to the centralized solution of these problems by means of computing DI with sufficient computing performance, located in favorable stationary conditions, providing the creation of more optimal conditions for their efficient operation, protection from the effects of vandals, temperature extremes, adverse climatic and weather conditions, from vibrations and shock loads, improving the conditions for their operation, maintenance and repair.

2. Improving the efficiency, reliability and service life of technical and computing means of the "intelligent transport system - vehicle - driver" environment with driver assistance systems by reducing the number and likelihood of failures by creating more favorable conditions for the fuel assemblies of the MCC DI for efficient and reliable operation , protection from both the previously mentioned negative impacts, that is, climatic and weather conditions, from vibrations and shock loads, and DOS attacks by hackers, that is, by improving the complex of conditions for their operation, maintenance and repair.

3. Increasing (in comparison with on-board driver assistance systems UVTS or ADAS system) the efficiency, reliability of ITS in providing assistance to drivers in the “intelligent transport system-vehicle-driver” (ITV) environment due to the implementation of functions and a comprehensive solution of the entire complex of necessary and sufficient tasks to provide guaranteed assistance to drivers of all vehicles under all traffic conditions and normal operation environment, the solution and implementation of which in full is not possible in any single on-board driver assistance system (ADAS system), or when these systems are used in various combinations due to limited space in the vehicle, carrying capacity, computing power and cost of on-board driver assistance systems or other AD AS systems.

4. Ensuring, when implementing the actions of the method, guaranteed efficient and reliable performance in the environment of "intelligent transport system - vehicle - driver" (ITV) of system designs and the performance of their functions of assisting drivers in real operating conditions at different speed modes of the flow of the vehicle, at different kind of unfavorable impacts, that is, pollution of the roadway, if there is water, snow, frost, sand, mud, ice on it, during rain, snowfall, when visibility and visibility of marking elements and road signs deteriorate due to sun glare, smoke and dustiness of the air, at high and low ambient temperatures, in case of pollution and / or damage to the protective or windshields of the vehicle and ITV equipment, in case of insufficient illumination, in poor condition of road markings and in the presence of other adverse factors.

5. Improving the efficiency and reliability of providing assistance to drivers during the implementation of actions due to the timely solution of additional tasks, such as: recognition of traffic policemen and their teams; detection of pits, ruts, speed bumps and other voluminous, dangerous pavement defects; passage of unregulated intersections of equivalent roads in compliance with the current traffic rules; recognition of "beacons" and other signals of emergency vehicles that require a maneuver to skip them with a change in lane or change in other traffic parameters;

6. Detection by means of DI ITS of dangerous malfunctions of the vehicle, for example, such as misalignment of wheels and hubs; detection of dangerous wear of tire cords; detection of dangerous wear of the suspension and steering.

7. Reduction in the implementation of actions of the method of accidents on the roads, the severity of accidents, that is, the number of dead and injured as a result of an accident, reducing the time of movement of each vehicle, reducing fuel consumption by vehicles and reducing environmental pollution due to stabilization and optimization of the trajectory and the process of movement of each TS, excluding unstable transients of acceleration, idling and braking.

8. Reduction in the implementation of actions of the method of minimizing the cost of operating costs for all types of vehicles in which, to the maximum extent and at the level of requirements for business class cars, the task of assisting the driver in optimizing his actions to control the EVTS by solving and implementing the most complex and costly tasks and functions for calculating the route of movement and coordinating the control of the UVTS on it with the help of technical and computing means of the road infrastructure of the intelligent transport system.

9. Reduction in the implementation of the actions of the method of the cost of monetary, material and other costs for traffic control of vehicles (TS) and for the operation of road infrastructure (TI) of an intelligent transport system (ITS) when used in traffic in the environment "intelligent transport system-vehicle - driver" (ITV) of all types of vehicles, as well as for the modernization, maintenance and repair of technical and computing tools used in the implementation of the proposed control method due to their stationary application.

To the complex of tasks to be solved and functions performed using the proposed method for controlling the movement of vehicles with driver assistance systems in the "intelligent transport system - vehicle - driver" environment, which ensures the most efficient and reliable operation of the environment under all traffic conditions and under all parameters of the normal operation environment, including the difficult operating conditions of the vehicle in the Russian Federation, at least, can be attributed to the guaranteed and accurate solution of the following tasks and the performance of the following functions:

- accurate current positioning of UVTS;

- recognition of road markings and precise determination of the location of the UVTS on the lane;

- recognition of road signs;

- recognition of surrounding vehicles and obstacles, including those moving in the front and rear hemispheres;

- stabilization of the UVTS distance to the front obstacle;

- stabilization of the UHTS trajectory on a given route according to the data of the TVS TsUD DI, taking into account the data of its technical vision and navigation systems;

- automatic braking of the UVTS in front of a sudden obstacle when it is impossible to bypass it;

- changing the lane of the UVTS, taking into account the position of all surrounding vehicles and obstacles, including for their urgent detour;

- stabilization of the speed of the UVTS on the ascents and descents;

- stabilization of longitudinal and transverse slides of UVTS;

- recognition of traffic policemen and their commands;

- detection of dangerous, defects, irregularities and / or other dangerous conditions of the road surface;

- recognition of traffic lights and data of their countdown timers;

- passage of unregulated intersections of equivalent roads in compliance with the current traffic rules;

- recognition of special signals, sirens and / or "beacons", etc. emergency vehicles that require UVTS to perform a lane change maneuver or change other traffic parameters in order to skip them;

- automatic parking with a choice of place;

- detection of dangerous misalignments and other malfunctions of wheels and hubs of UVTS;

- detection of dangerous wear of protectors and cords of UVTS tires;

- detection of dangerous wear of the suspension and steering (RU) UVTS;

- detection of dangerous pressure drops in UVTS tires.

When solving the whole complex of the listed tasks using the proposed method, high-precision monitoring and diagnostics are provided, for example, of the following parameters:

- technical speed of the UVTS, longitudinal velocity of the center of mass of the UVTS;

- the speed of approach of the UVTS with passing front and rear vehicles or other obstacles;

- drift speed of the front wheels of the UVTS;

- speed of skidding of rear wheels of UVTS;

- the danger of occurrence of the speed of overturning of the HVTS;

- slip speed of the driving wheels of the UVTS;

- longitudinal and transverse accelerations of UVTS;

- longitudinal slips of UVTS wheels;

- angles of rotation of the steered wheels of the UVTS;

- position coordinates of the UVTS in the associated Cartesian coordinate system;

- the speed of the UVTS, limited by road signs in their coverage area;

- the speed of the UHTS, limited by the detection range of moving and fixed obstacles in the traffic lane;

- UHTS distances to obstacles in the front and rear hemispheres on the lane;

- top values of coefficients of sliding friction (characteristic of adhesion of wheels to the surface of the road surface);

- air pressure in UVTS tires;

- overheating temperatures of tires and brakes UVTS;

- limiting the speed of movement of UVTS with a flat tire;

- speed dangerous for breaking the cord of UVTS tires;

- types, condition and quality of the road surface;

- climatic and weather conditions;

- parameters of the surrounding air;

- lighting, time of day;

- control of the state of adequacy, sleep or wakefulness of the driver of the UVTS;

- the technical condition of a driver-controlled vehicle (PVTS), its traffic controls, the technical condition of driver assistance systems (ADAS systems), their components and sensors.

The technical determination of the indicated malfunctions of the EVTS can be carried out with external video recording of the behavior of the EVTS or other visual signs, and can also be recorded according to data from the on-board diagnostic system for the state of the indicated elements of the OVTS.

At the same time, in accordance with the proposed method, in addition to solving the main tasks and the functions implemented in it, the implementation of, among other things, the following additional functions is provided:

- stabilization of the safe speed and distance of movement of the UVTS to the vehicle and obstacles in the front and rear hemispheres;

- prevention of collisions of UVTS with mobile and fixed vehicles and obstacles;

- stabilization of longitudinal slips of UVTS wheels;

- stabilization of the exchange rate stability of the UVTS;

- prevention of overturning of UVTS;

- automatic braking of UVTS without blocking the wheels to a complete stop on real surfaces (dry and wet asphalt, snow, ice, gravel, sand, soil, paving stones) in front of a movable and / or fixed obstacle in the front hemisphere on the lane, taking into account the distance to another vehicle means in the rear hemisphere;

- emergency stop of UVTS in case of critical malfunctions (tire pressure drop, overheating of tires and brakes, weakening of wheels to hubs, unacceptable wear of tire cords, etc.) and accidents;

- control along the trajectory of the vehicle movement of the state of adequacy, sleep or wakefulness of the driver of the UVTS;

- optimization of the composition and creation of favorable conditions for the operation of sensors, hardware and actuators, technical and computing facilities (TVS) of DI ITS in the "intelligent transport system - vehicle - driver" environment, which ensure their most efficient and reliable operation under all road conditions movement and under all parameters of the environment for normal operation of the UVTS.

The implementation of the main functions of the driver assistance systems of all vehicles in the transport network using stationary technical and computing facilities of the traffic control center of the vehicle of the intelligent transport system and the execution of the transmitted control commands in simpler and more accessible on-board driver assistance systems of the vehicle will radically improve the reliability of the operation of the entire advanced road intelligent system .

Among the main advantages, ie. The technical results achieved by implementing the proposed method should include a sharp increase in road safety and a reduction in the total costs associated with the operation of the entire transport system, in which technical and computing tools with sufficient computing performance are used permanently and centrally to control all on-board driver assistance systems. UVTS instead of using the most complex, expensive and having a limited resource of autonomous on-board driver assistance systems of the vehicle, which are not capable of solving all the tasks that ensure the safe operation of vehicles, especially in the road and climatic conditions of the Russian Federation.

This proposal can be widely used on UVTS operated on public roads and in specialized, including closed areas (exhibition complexes, warehouse, industrial and factory territories, logistics centers, car parks, garage complexes, etc.) all environmental conditions in normal operation.

Based on the foregoing, the following can be stated.

The stated technical problem is solved by technical means and can be used in the proposed form in the national economy, therefore, the proposal meets the criterion of the invention "industrial applicability".

The proposal differs from the known method of operation, therefore, meets the criterion of invention "novelty".

The proposal, when performing all known and new actions of the method, allows achieving new, previously unknown technical results, therefore, it meets the criterion of the invention "inventive step".

Claims (10)

1. A method for controlling the movement of vehicles (TS) driven by a driver (UVTS) with driver assistance systems in the "intelligent transport system - vehicle - driver" (ITV) environment, according to which the technical and computing means (TVS) of the ITV environment , including electronic on-board units (ECU) of vehicles (TS) and ECU TVS of the traffic control center (TCC) of the road infrastructure (TI) of the intelligent transport system (ITS), register and process signals from sensors and systems of TVS TS and TVS TsUD DI, and also signals from the satellite navigation system, transmit them to information processing units (PUU), which determine the values of the parameters and physical variables of each vehicle and the environment surrounding the UHTS of the normal operation environment (SSE), compare them with the calculated and / or with the boundary values characterizing calculated and/or critical state of each vehicle, transfer the results of comparison and calculations to the control units (CU), which form control signals and transmit them to the output devices of graphic information and / or to indicators of calculated and / or dangerous states to inform the appropriate drivers, who determine and form further actions to control the UVTS, and in the event of critical conditions and / or in case of insufficiency or absence of actions of a particular of the driver of the UVTS to exclude critical conditions, generate control signals and transmit them to the actuating drives for controlling the movement of a specific UVTS and other vehicles surrounding it, characterized in that in the traffic control center of the DI ITS with the help of additional stationary fuel assemblies in real time in addition to the previously indicated standard actions are performed in the area of responsibility of the control center a set of additional actions, including such actions in which: - carry out recognition, identification, determine the exact location, geometric dimensions, speeds and directions of movement of all vehicles in the area of responsibility of the control center; - carry out recognition, identification, determine the exact location, geometric dimensions of moving and fixed obstacles, such as people, motorcyclists, electric scooters, cyclists, animals, road curbs, foreign objects, cobblestones, volumetric defects of the road surface, pits, and also determine the absolute and relative speed and direction of moving obstacles; - determine the distances between vehicles and/or obstacles; - perform the formation, monitoring, updating and real-time processing of databases according to specified algorithms, in accordance with the state of the normal operation environment in the areas of DI coverage, such as by maps of the area, by type, quality and condition of the road surface, by road markings, road signs, traffic lights and their modes of operation, according to the climatic conditions of the SSE, such as wind speed, temperature, pressure and humidity, the presence and types of precipitation, dust and smoke in the air, fog, the presence of fine moisture on the roadway in real time (hoarfrost , dew, drizzle), water, snow, ice, mud; - receive additional data from the satellite navigation system and / or from additional stationary fuel assemblies, on-board ECUs surrounding the vehicle with the help of communication systems, such as: more accurate positioning of the vehicle, obstacles and RD objects, air pollution with gaseous harmful substances, such as: oxides nitrogen, ozone, formaldehyde, carbon monoxide, solid particles, and process them according to specified algorithms in real time; - predict (taking into account the data obtained by the MCC DI ITS using stationary PU of additional fuel assemblies) possible points of intersection and / or dangerous approaches with moving and fixed obstacles on the trajectory of each vehicle, and in case of identifying a forecast of possible points of intersection and / or dangerous approaches with other vehicles, and/or obstacles, and/or objects, the DI calculates additional maneuvers and/or trajectories and speeds of movement of each vehicle to prevent collisions and transmits the predicted information and calculation results to the ECU of the UVTS and other vehicles surrounding the UVTS; - at the same time, in each of the ECUs of the UHTS, control signals are generated based on the results of processing the data received from the MCC, as well as additional data received from the satellite navigation system, and / or from stationary fuel assemblies, and / or on-board ECUs of the vehicle surrounding the UHTS, on on the basis of which the final control signals are formed according to the given algorithms and transmitted to the graphic information output device and / or to the indicators of the calculated and / or dangerous states of the air traffic control system to inform the driver, who, based on the information received, performs further actions to control the movement of the air traffic control system, by influencing the systems / controls for traction, brakes, steering mechanisms and / or controls for other systems, components and assemblies of the UVTS, such as a power plant, propulsion unit, chassis, and in the event of critical conditions and / or insufficiency or in the absence of driver actions to eliminate critical states of the ECU of the UVTS are formed and transmitted, bypassing the driver i, control commands to the motion control drives of each UVTS and other vehicles surrounding the UVTS. 2. The method of controlling the movement of vehicles according to claim 1, characterized in that additional fuel assemblies of the traffic control center and / or on-board electronic control unit of the vehicle additionally monitor the execution of control commands for the motion control drives of each vehicle, evaluate the accuracy of their execution and, if necessary , the control commands are recalculated and additional corrected control commands are retransmitted via the PU of each vehicle to the ECU of each vehicle and/or to the motion control drives of each vehicle. 3. The method of controlling the movement of vehicles according to claim 1, characterized in that, with additional scanning and mathematical processing, flat and stereo images are obtained by using a roadbed scanning device with two linear photosensitive devices installed permanently in the DI and / or in the vehicle on a gyro-stabilized platform .