CN117104218A

CN117104218A - Unmanned remote control collaborative decision-making system

Info

Publication number: CN117104218A
Application number: CN202311377695.0A
Authority: CN
Inventors: 赵枫; 吴晶晶
Original assignee: Jiangsu Huaiguang Intelligent Transportation Technology Co ltd
Current assignee: Jiangsu Huaiguang Intelligent Transportation Technology Co ltd
Priority date: 2023-10-24
Filing date: 2023-10-24
Publication date: 2023-11-24
Anticipated expiration: 2043-10-24
Also published as: CN117104218B

Abstract

The application discloses an unmanned remote control collaborative decision-making system, which relates to the technical field of automobile unmanned, and comprises a carrier end, a control cloud end and a plurality of site ends; the control cloud end is used for acquiring data fed back from the carrier end; the carrier end comprises an abnormal point detection module, an evaluation judging module and a braking subsystem which are sequentially executed; the abnormal point detection module is used for acquiring the front road surface information and judging whether abnormal points exist or not; the technical key points are as follows: when the automobile braking state evaluation value Pvce is calculated, the correlation factors between the automobile and the abnormal points are comprehensively considered, and when the automobile braking state evaluation value Pvce is compared with the evaluation threshold value, the external environmental factors are additionally considered, so that the accuracy of judging how to brake the automobile by the system is further improved, and the driving safety in the automobile braking process is greatly improved by combining the design of the station end and the steering braking unit.

Description

Unmanned remote control collaborative decision-making system

Technical Field

The application relates to the technical field of unmanned vehicles, in particular to an unmanned remote control collaborative decision-making system.

Background

Unmanned automobile refers to technology and system for enabling an automobile to run and navigate autonomously without a human driver by using an automation technology and artificial intelligence, wherein the technology and system senses the surrounding environment through laser radar, cameras, sensors, computers and other devices, and makes decisions and controls by using algorithms and models so as to realize autonomous driving and automatic running; the logistics automobiles in the factory can realize functions such as automatic driving and the like and can be driven remotely by switching one key because the logistics automobiles are provided with the 4G/5G communication hot equipment.

The technical scheme disclosed in the China patent application number 202110893527.1, named unmanned automobile control system and unmanned automobile is as follows: the control system of the unmanned automobile integrates an automatic driving system, a communication system and a man-machine interaction system, can realize L4-level automatic driving, sets the automatic driving system and the man-machine interaction system in different domains by using a central safety gateway, and realizes safety network communication and data isolation between the automatic driving system and the man-machine interaction system inside the control system by the central safety gateway; and secure data transmission between the control system and the external device can be realized through the central security gateway.

However, in view of the above-mentioned patent, in combination with the prior art, the safety of the driver is improved by using the unmanned vehicle to transport goods on the traffic road of the port, but the stability of the vehicle itself cannot be intuitively and accurately controlled, the conventional unmanned vehicle can determine whether the vehicle uses conventional braking or emergency braking when acquiring the deceleration request through the ESC, the conventional braking is the conventional braking with the deceleration less than 0.4g and the emergency braking with the deceleration not less than 0.4g, but the factors considered by the conventional determination method are single, for example: for the periphery of a port, the wet skid coefficient of the road is high, and the automobile cannot be stopped before encountering an obstacle only by conventional braking operation; in addition, if the automobile encounters an obstacle, the automobile cannot be stopped before encountering the obstacle by using the emergency brake, and at the moment, steering adjustment is needed, the automobile can be greatly reduced in stability in the braking running process due to the fact that the automobile is directly driven off the road surface, the automobile can be damaged, and the goods carried by the automobile can be damaged to a certain extent.

Disclosure of Invention

Aiming at the defects of the prior art, the application provides the unmanned remote control collaborative decision-making system, when the automobile braking state evaluation value Pvce is calculated, the related factors between the automobile and the abnormal point are comprehensively considered, and when the automobile braking state evaluation value Pvce is compared with the evaluation threshold value, the external environmental factors are additionally considered, so that the accuracy of judging how to brake the automobile by the system is further improved, the safety of running in the automobile braking process is greatly improved by combining the design of a station end and a steering braking unit, and the problems that the conventional braking or emergency braking of the automobile is judged to be inaccurate and the stability of the automobile is reduced due to the fact that the steering adjustment is selected when the automobile is not braked in the past are solved.

In order to achieve the above purpose, the application is realized by the following technical scheme:

the unmanned remote control collaborative decision-making system comprises a carrier end, a control cloud end and a plurality of site ends;

the control cloud end is used for acquiring data fed back from the carrier end;

the carrier end comprises an abnormal point detection module, an evaluation judging module and a braking subsystem which are sequentially executed;

the abnormal point detection module is used for acquiring the front road surface information, judging whether an abnormal point exists or not, if yes, sending a deceleration request through an ESC system carried by the automobile, collecting relevant data of the automobile, and if not, enabling the automobile to normally run;

the evaluation judging module builds a data analysis model, generates an automobile braking state evaluation value Pvce, compares the automobile braking state evaluation value Pvce with an evaluation threshold value, inputs a comparison result into a braking subsystem, and performs conventional or emergency braking selection;

the control cloud also judges whether a station end exists between the initial position of the automobile when the speed reduction request is executed and the position of the abnormal point, if so, a starting instruction is sent to the station end closest to the abnormal point, a control instruction is sent to a steering braking unit in the braking subsystem under the condition that the automobile runs to the station end closest to the abnormal point so as to control the automobile to steer into the corresponding station end, and if not, a control instruction is directly sent to the steering braking unit so as to control the automobile to steer into a roadside area.

Further, in the abnormal point detection module, the process of judging whether the abnormal point exists is as follows:

s101, acquiring a front road surface image in real time by a vehicle-mounted camera in the running process of an automobile;

s102, preprocessing a front road surface image, and extracting edge characteristics in the road surface image by adopting an edge detection algorithm;

s103, distinguishing edge features by adopting a segmentation image algorithm to obtain an abnormal region and a normal road surface;

and S104, constructing a rule engine, judging whether the abnormal region is in a protruding shape or a concave shape, if so, judging that the abnormal region is an abnormal point, and if not, judging that the abnormal region is a non-abnormal point.

Further, the data are applied to a data acquisition unit built in the abnormal point detection module when the related data of the automobile are acquired, wherein the related data comprise deceleration of the automobile when a deceleration request is executed, the distance between the abnormal point and the current automobile and the estimated occupied area and height of the abnormal point.

Further, in the evaluation determination module, the generation step of the vehicle brake state evaluation value Pvce is as follows:

s201, carrying out dimensionless processing on the deceleration Vr, the distance Hu between the abnormal point and the current automobile and the estimated occupied area Wv and the height Ko of the abnormal point when the automobile executes a deceleration request;

s202, calculating an abnormal point occupation coefficient Har according to the estimated occupation area Wv and the height Ko of the abnormal point, wherein the estimated occupation area Wv and the height Ko of the abnormal point are calculated according to the following formula:

；

s203, calculating an automobile braking state evaluation value Pvce according to the deceleration Vr when the automobile executes the deceleration request, the distance Hu between the abnormal point and the current automobile and the occupation coefficient Har of the abnormal point, and the following formula:

in the method, in the process of the application,、/>、/>respectively the preset proportional coefficients of the deceleration of the automobile when the automobile executes the deceleration request, the distance between the abnormal point and the current automobile and the occupation coefficient of the abnormal point, and +.>＞/>＞/>＞0，/>，/>The specific value of the constant correction coefficient can be set by user adjustment or generated by fitting an analysis function.

Further, the process of comparing the vehicle brake state evaluation value Pvce with the evaluation threshold value is as follows:

s301, when the vehicle is running in a special environment, evaluating a threshold value=a correction value xz+a preset threshold value;

s302, calculating a correction value as follows:

the method comprises the steps of carrying out dimensionless treatment on the collected slip coefficient Sxt of the road surface environment and the road surface gradient Po, and obtaining a correction value XZ through formula calculation, wherein the formula is as follows:

in the method, in the process of the application,、/>respectively the coefficient of slip of the road surface environment and the preset proportional coefficient of the road surface gradient, and +.>，/>；

S303, if the automobile brake state evaluation value Pvce is larger than the evaluation threshold value, indicating that an emergency brake request is needed;

if the vehicle braking state evaluation value Pvce is not greater than the evaluation threshold value, a conventional braking request is required.

Further, the braking subsystem comprises a conventional braking module, an emergency braking module and a position prediction module;

the conventional braking module is used for realizing braking torque control under ACC working conditions;

the emergency braking module is used for realizing braking torque control under AEB working conditions;

the position prediction module is used for comparing the acquired automobile deceleration distance Lr with the distance Hu between the abnormal point and the current automobile, wherein the automobile deceleration distance Lr is the distance from the deceleration request to the running of the automobile in the stationary time period;

if the automobile deceleration distance Lr is greater than the distance Hu between the abnormal point and the current automobile, starting a steering braking unit arranged in the emergency braking module; if the automobile deceleration distance Lr is not greater than the distance Hu between the abnormal point and the current automobile, continuing normal braking torque control until the automobile is stationary.

Further, any station end comprises a roller supporting module and a speed regulating module, the station ends are station end 1, station ends 2 and … and station end n respectively, n is the number of the corresponding station end, and n is a positive integer.

Further, the roller supporting module comprises a plurality of rubber rollers which are uniformly distributed and a driver for driving each rubber roller to synchronously rotate, the speed regulating module carries out braking control, and the specific process of the braking control is as follows:

s401, acquiring real-time vehicle speed Vt of an automobile;

s402, controlling a driver to drive the rotating speed of each rubber roller to be consistent with the real-time vehicle speed Vt of the vehicle, wherein the rotating direction of any rubber roller is opposite to the rotating direction of the vehicle wheel;

s403, stopping braking control after the automobile completely enters the corresponding station end.

The application provides an unmanned remote control collaborative decision-making system, which has the following beneficial effects:

the deceleration, the distance between the abnormal point and the current automobile and the occupation coefficient of the abnormal point are obtained when the automobile executes the deceleration request, wherein the built data analysis model not only analyzes and calculates the occupation coefficient of the abnormal point, but also generates an automobile braking state evaluation value Pvce, which not only considers the deceleration as a single factor, comprehensively considers the related factors between the automobile and the abnormal point, and improves the judgment accuracy of the conventional braking or emergency braking request;

by adding the correction value to the originally fixed preset threshold before comparing the automobile braking state evaluation value Pvce with the evaluation threshold, the evaluation threshold can automatically adjust the value according to actual conditions, influence caused by external environmental factors is considered when conventional braking or emergency braking is judged to be used, the accuracy of judging how to brake the automobile by the system is further improved, and the situation that the original judgment result is larger in error due to weather or road surface condition change is avoided;

for an automobile for transporting goods, emergency braking cannot be timely carried out when sudden abnormal points are encountered, the automobile is required to be turned and regulated, a plurality of station ends are added on the basis of an original carrier end and a control cloud end for guaranteeing the stable and safe form of the automobile all the time during braking, multiparty collaborative operation is achieved, the automobile enters the corresponding station end at a very small deflection angle by combining a turning braking unit in an emergency braking module, the automobile and the station end can be guaranteed to be relatively static by utilizing all modules arranged in the station end until wheels of the automobile stop rotating, the risk of traffic accidents is reduced, the automobile or the abnormal points of a road can be timely maintained later, and the driving safety of the automobile in the braking process is greatly improved.

Drawings

FIG. 1 is a schematic diagram of a carrier end in an unmanned remote control collaborative decision-making system of the present application;

FIG. 2 is a block diagram of a station end in the unmanned remote control collaborative decision-making system of the present application;

FIG. 3 is a schematic diagram of an unmanned remote control collaborative decision-making system of the present application;

FIG. 4 is a schematic diagram of a path of an automobile at a station entering end in the unmanned remote control collaborative decision-making system of the application;

legend description: 110. a rubber roller; 111. a driver.

Detailed Description

The following description of the embodiments of the present application will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.

Referring to fig. 1-4, the present application provides an unmanned remote control collaborative decision-making system, which includes a carrier terminal, a control cloud terminal and a plurality of site terminals;

the control cloud end is used for acquiring data fed back from the carrier end in real time;

the wireless communicator is arranged in the carrier terminal, the control cloud can remotely acquire data fed back by the carrier terminal through the wireless communicator, and the follow-up control cloud and each site terminal also adopt the same principle to perform data feedback and control operation;

the process for judging whether the abnormal point exists is as follows:

s101, acquiring a front road surface image in real time by a vehicle-mounted camera in the running process of an automobile; the vehicle-mounted camera is a high-definition camera arranged in the automobile, and a shooting area of the vehicle-mounted camera always faces the running direction of the automobile;

s102, preprocessing a front road surface image, and extracting edge characteristics in the road surface image by adopting an edge detection algorithm; the preprocessing is to perform conventional graying or filtering processing on the image to improve the image quality, and then the adopted edge detection algorithm is a Canny algorithm;

s103, analyzing the extracted edge features of the road surface image, and distinguishing an abnormal area from a normal road surface by adopting a segmentation image algorithm; the image segmentation algorithm used therein is a segmentation algorithm based on threshold, clustering or deep learning

S104, constructing a rule engine, judging whether the abnormal area is in a protruding shape or a concave shape, if so, judging that the abnormal area is an abnormal point, and if not, judging that the abnormal area is a non-abnormal point; the protruding shape and the concave shape respectively correspond to the protruding obstacle and the ground concave;

to build a rule engine to determine whether the abnormal region is in a protruding shape or a recessed shape, the rule is defined by the following steps: defining rule sentences according to the judging conditions; for example: if the abnormal region is in a protruding shape, determining that the abnormal region is an abnormal point; if the abnormal region is concave, determining that the abnormal region is an abnormal point; data preparation: acquiring data of an abnormal region, which can be image or characteristic data; rule matching: matching the extracted characteristic data with a rule defined in advance, and determining whether the abnormal region meets the condition according to the rule; and (3) outputting results: outputting a conclusion for judging whether the abnormal area is an abnormal point or not according to the rule matching result;

for example: the method is characterized in that the indication arrows of the new coating on the ground are identified as abnormal areas, the abnormal areas are not further judged to be abnormal points because the indication arrows are not protruding or concave, the unmanned automobile used in a logistics park is adopted, and large parts or cargoes are transported by the automobile, so that the abnormal points of the protruding road are mostly parts or cargoes falling during transportation, and the abnormal points of the concave road are corresponding to the situation of road collapse, and the road collapse is caused by heavy transportation vehicles and wet weather.

The method comprises the steps that when related data of an automobile are collected, the related data comprise deceleration of the automobile when a deceleration request is executed, the distance between the abnormal point and the current automobile and the estimated occupied area and height of the abnormal point are applied to a data collection unit arranged in an abnormal point detection module;

specifically, the deceleration of the vehicle when executing the deceleration request is obtained through feedback of the ECU, and the vehicles on the market are equipped with an Electronic Control Unit (ECU) for processing the vehicle state and the control signal, and the ECU can infer the magnitude of the deceleration by monitoring the change of the vehicle state and the signal for executing the deceleration request;

the distance between the abnormal point and the current automobile can be directly obtained by installing a laser range finder on the automobile;

the estimated occupation area and height of the abnormal points are obtained in the following manner:

viewing angle and distance calibration: the vehicle-mounted camera is calibrated in view angle and distance, and the view angle and the distance can be achieved through matching with a motion sensor or a GPS of a vehicle, so that more accurate distance and angle information can be obtained;

angle measurement: the angle information of the object in the image can be measured by using a computer vision algorithm through the image acquired by the vehicle-mounted camera; for example, using feature point detection and image matching algorithms, calculating the estimated height of an outlier by measuring the angular relationship of the outlier to the ground in the field of view of the vehicle-mounted camera;

measurement of dimensions: using a remote ground image shot by an on-board camera, and performing scale measurement by using a perspective transformation technology in computer vision; for example, by detecting and measuring a reference point (e.g., lane line, road sign) on the ground, the estimated floor area of a remote ground anomaly is calculated in combination with known dimensions.

The evaluation judging module builds a data analysis model, generates an automobile braking state evaluation value Pvce, compares the automobile braking state evaluation value Pvce with an evaluation threshold value, and inputs a comparison result into the braking subsystem;

the generation step of the vehicle brake state evaluation value Pvce is as follows:

；

in the method, in the process of the application,、/>、/>respectively the preset proportional coefficients of the deceleration of the automobile when the automobile executes the deceleration request, the distance between the abnormal point and the current automobile and the occupation coefficient of the abnormal point, and +.>＞/>＞/>＞0，/>，/>Is a constant correction factor whose specific value can be set by user adjustment or generated by fitting an analytical function,/->The specific value range of (2) is 1.5-1.8.

It should be noted that: a person skilled in the art collects a plurality of groups of sample data and sets a corresponding preset scaling factor for each group of sample data; substituting the preset proportionality coefficient, which can be the preset proportionality coefficient and the collected sample data, into a formula, forming a ternary once equation set by any three formulas, screening the calculated coefficient and taking an average value to obtain、/>、/>Is a value of (2); the magnitude of the coefficient is a specific numerical value obtained by quantizing each parameter, so that the subsequent comparison is convenient, the magnitude of the coefficient depends on the number of sample data and the corresponding preset proportional coefficient preliminarily set by a person skilled in the art for each group of sample data, that is, the coefficient is preset according to the actual practice, so long as the proportional relation between the parameter and the quantized numerical value is not influenced, and the above description is also adopted for the preset proportional coefficient and the constant correction coefficient described in other formulas.

The process of comparing the vehicle braking state evaluation value Pvce with the evaluation threshold value is as follows:

s301, when the vehicle is running in a special environment, evaluating a threshold value=a correction value xz+a preset threshold value; the special environment is a road surface in a rainy day state, so that the road surface is wet, a higher coefficient Sxt of slip can lead to skidding of wheels of the automobile, the driving stability of the automobile is affected, a road surface with a fixed gradient is selected for the subsequent road gradient Po, the road surface with up-and-down fluctuation is not considered, and the higher the road gradient Po is, the automobile may not need emergency braking when ascending the slope;

it should be noted that: the preset threshold may be a fixed value, set based on historical data acquisition.

S302, calculating a correction value as follows:

in the method, in the process of the application,、/>respectively the coefficient of slip of the road surface environment and the preset proportional coefficient of the road surface gradient, and +.>，/>The method comprises the steps of carrying out a first treatment on the surface of the The coefficient Sxt of the road surface environment is directly obtained by a laser remote sensing road surface condition sensor, the model of the laser remote sensing road surface condition sensor is YGLM-Z2 type, and the states of road surface dryness, dampness, snow accumulation, icing and the like, the temperature of the road surface, the thickness of ice and snow, the degree of wet skid and the like provided by the YGLM-Z2 type laser remote sensing road surface condition sensor are all important indexes for controlling traffic safety, wherein the coefficient Sxt of the road surface is the index required by the application; road gradient is directly obtained by a gradient sensor carried in the automobile.

By adding the correction value to the originally fixed preset threshold before comparing the automobile braking state evaluation value Pvce with the evaluation threshold, the evaluation threshold can be automatically adjusted according to actual conditions, influence caused by external environmental factors is considered when conventional braking or emergency braking is judged, the accuracy of judging how to brake the automobile by the system is further improved, and the situation that the original judgment result is larger in error due to weather or road surface condition change is avoided.

The deceleration, the distance between the abnormal point and the current automobile and the occupation coefficient of the abnormal point are obtained when the automobile executes the deceleration request, wherein the built data analysis model not only analyzes and calculates the occupation coefficient of the abnormal point, but also generates the automobile braking state evaluation value Pvce, not only considers the deceleration as a single factor, but also comprehensively considers the related factors between the automobile and the abnormal point, and improves the judgment accuracy of the conventional braking or emergency braking request.

The braking subsystem comprises a conventional braking module, an emergency braking module and a position prediction module;

the ACC is self-adaptive cruise control, and a conventional braking module in automobile software, namely the ACC module receives a deceleration request and realizes the deceleration request in a comfortable and gentle mode;

the emergency braking module is used for realizing braking torque control under AEB working conditions; AEB is collision mitigation control, and an emergency braking module in the automobile software, namely a CMS module, controls the automobile to realize an emergency deceleration request, namely AEB working conditions.

The position prediction module is used for comparing the acquired automobile deceleration distance Lr and the distance Hu between the abnormal point and the current automobile, wherein the automobile deceleration distance Lr is the distance from the deceleration request to the running of the automobile in the stationary time period;

if the automobile deceleration distance Lr is greater than the distance Hu between the abnormal point and the current automobile, starting a steering braking unit arranged in the emergency braking module;

if the automobile deceleration distance Lr is not greater than the distance Hu between the abnormal point and the current automobile, continuing normal braking running until the automobile is stationary;

the automobile deceleration distance Lr is larger than the distance Hu between the abnormal point and the current automobile, which is represented by the following formula: according to the current braking mode, the automobile still passes through an abnormal point before being stationary, so as to ensure the stable operation of the automobile, and a steering braking unit is started;

the cloud end is controlled, the initial position and the position of the abnormal point of the automobile when the deceleration request is executed are also obtained, and whether a station end exists between the initial position and the position of the abnormal point or not is judged;

if so, a starting instruction is sent to a station end closest to the abnormal point position, and a control instruction is sent to a steering braking unit under the condition that the automobile runs to the station end closest to the abnormal point position so as to control the automobile to steer into the corresponding station end;

if not, a control instruction is sent to a steering braking unit directly so as to control the steering of the automobile to enter a roadside area;

specifically, when the automobile executes a deceleration request, the initial position can be directly obtained through the built-in GPS module of the automobile, and the position of the abnormal point can be obtained through calculation according to the running direction (road direction) of the automobile and the distance Hu between the abnormal point and the current automobile;

each site end is also internally provided with a GPS module, the initial position, the position of an abnormal point and the position of each site end of the automobile when the deceleration request is executed are reflected on an online map model constructed in a control cloud, the number of site ends existing between the initial position and the position of the abnormal point can be directly obtained by using a coordinate system of the map, the distance between the position of the abnormal point and each site end can be calculated, and the nearest site end is found; for example: and establishing an XY coordinate system by taking the position of the abnormal point as the circle center, wherein the site end with the smallest distance from the circle center is the site end closest to the abnormal point.

The roadside area of the present application may be filled with a liquid, for example: the water level is far smaller than the automobile, and when the automobile runs in the road side area, the filled liquid can play a role in buffering and reducing speed.

It should be noted that: the more the number of the station ends is, the lower the probability that the automobile enters the roadside area is, when the steering braking unit controls the automobile to steer, the rotating angle is adjusted according to the installation angle of the station ends, and the automobile is ensured not to rub with the inner wall of the station ends after entering the corresponding station ends.

Any station end comprises a roller supporting module and a speed regulating module; the plurality of site ends are site end 1, site ends 2 and …, site end n, n is the number of the corresponding site end, and n is a positive integer.

The roller supporting module comprises a plurality of uniformly distributed rubber rollers 110 and a driver 111 for driving each rubber roller to rotate, and the speed regulating module performs braking control, wherein the specific process of the braking control is as follows:

s401, acquiring real-time vehicle speed Vt of an automobile;

s402, controlling the driver 111 to drive the rotation speed of each rubber roller 110 to be equal to the real-time speed Vt of the automobile, wherein the rotation direction of any rubber roller 110 is opposite to the rotation direction of the wheels of the automobile;

s403, stopping braking control after the automobile completely enters the corresponding station end;

the rotation direction of each rubber roller 110 is opposite to the rotation direction of the corresponding station end, so that the automobile can keep relative static with the corresponding station end, namely, when the automobile wheels completely run onto each rubber roller 110, the automobile moves on the roller supporting module, but keeps relative static with the corresponding station end, the automobile completes braking operation in the corresponding station end, the running stability of the automobile is ensured, and meanwhile, the subsequent corresponding overhaul and maintenance treatment on the automobile is also convenient.

It should be noted that: the spacing between adjacent sets of rubber rollers 110 is less than the diameter of the vehicle wheels.

For an automobile for transporting goods, emergency braking cannot be timely carried out when sudden abnormal points are encountered, the automobile is required to be turned and regulated, a plurality of station ends are added on the basis of an original carrier end and a control cloud end for guaranteeing the stable and safe form of the automobile all the time during braking, multiparty collaborative operation is realized, the automobile enters the corresponding station end at a very small deflection angle by combining a turning braking unit in an emergency braking module, the automobile and the station end can be guaranteed to be relatively static by utilizing all modules arranged in the station end until wheels of the automobile stop rotating, the risk of traffic accidents is reduced, the subsequent maintenance of the automobile or the abnormal points of a road can be timely carried out, and the driving safety of the automobile in the braking process is greatly improved.

The above formulas are all formulas with dimensions removed and numerical values calculated, the formulas are formulas with a large amount of data collected for software simulation to obtain the latest real situation, and preset parameters in the formulas are set by those skilled in the art according to the actual situation.

The above embodiments may be implemented in whole or in part by software, hardware, firmware, or any other combination. When implemented in software, the above-described embodiments may be implemented in whole or in part in the form of a computer program product. Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution.

The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

The foregoing is merely illustrative of the present application, and the present application is not limited thereto, and any person skilled in the art will readily recognize that variations or substitutions are within the scope of the present application.

Claims

1. Unmanned remote control collaborative decision-making system, including carrier end, control high in the clouds and a plurality of website end, control high in the clouds is used for obtaining the data from the carrier end feedback, its characterized in that:

2. The unmanned remote control collaborative decision-making system according to claim 1, wherein: in the abnormal point detection module, the process of judging whether an abnormal point exists is as follows:

3. The unmanned remote control collaborative decision-making system according to claim 1, wherein: the method comprises the steps of applying the vehicle-related data to a data acquisition unit built in an abnormal point detection module when the vehicle-related data is acquired, wherein the related data comprise deceleration of the vehicle when a deceleration request is executed, the distance between the abnormal point and the current vehicle and the estimated occupied area and height of the abnormal point.

4. The unmanned remote control collaborative decision-making system according to claim 1, wherein: in the evaluation determination module, the generation step of the vehicle brake state evaluation value Pvce is as follows:

；

5. The unmanned remote control collaborative decision-making system according to claim 4, wherein: the process of comparing the vehicle braking state evaluation value Pvce with the evaluation threshold value is as follows:

s302, calculating a correction value as follows:

in the method, in the process of the application,、/>respectively the coefficient of slip of the road surface environment and the preset proportional coefficient of the road surface gradient, and +.>，；

6. The unmanned remote control collaborative decision-making system according to claim 1, wherein: the braking subsystem comprises a conventional braking module, an emergency braking module and a position prediction module;

7. The unmanned remote control collaborative decision-making system according to claim 1, wherein: any station end comprises a roller supporting module and a speed regulating module, the station ends are station end 1, station ends 2 and … and station end n respectively, n is the number of the corresponding station end, and n is a positive integer.

8. The unmanned remote control collaborative decision-making system according to claim 7, wherein: the roller supporting module comprises a plurality of rubber rollers (110) which are uniformly distributed and a driver (111) for driving each rubber roller to synchronously rotate, the speed regulating module carries out braking control, and the specific process of the braking control is as follows:

s401, acquiring real-time vehicle speed Vt of an automobile;

s402, controlling a driver (111) to drive the rotating speed of each rubber roller (110) to be consistent with the real-time vehicle speed Vt of the vehicle, wherein the rotating direction of any rubber roller (110) is opposite to the rotating direction of the vehicle wheel;