An intelligent assisted driving system for urban public transportation based on vehicle-road cooperative technology

Abstract

The present invention discloses an intelligent assisted driving system for urban public transportation based on vehicle-road cooperative technology, which specifically relates to the field of intelligent driving, including a system central processing unit module, a system operation database and a user information terminal, and also includes a vehicle-road cooperative perception module, a bus driving judgment module, a bus driving information acquisition module, a bus driving information mining module, a data standardization processing module, a bus driving information analysis module, an assisted driving system effect judgment module and a human-computer interaction module. The present invention creatively constructs a comprehensive and accurate mathematical model by deeply analyzing the detailed data mined. The model cleverly integrates the four core dimensions of driving efficiency, driving safety, system performance, and bus energy consumption and environmental protection, and realizes a comprehensive and comprehensive measurement of the performance of the assisted driving system. Through the establishment of this comprehensive model, the present invention can significantly improve the accuracy and comprehensiveness of the evaluation.

Description

Technical Field

[0001] The present invention relates to the field of intelligent driving technology, and more specifically, to an urban bus intelligent assisted driving system based on vehicle-road cooperative technology. Background Art

[0002] Vehicle-road collaborative technology refers to the information interaction between vehicles and all surrounding elements including roads, traffic signals, other vehicles, etc. This interaction is achieved through communication between on-board communication equipment and infrastructure equipment, and aims to improve traffic efficiency, safety and environmental friendliness.

[0003] The urban bus intelligent assisted driving system based on vehicle-road collaborative technology is a highly integrated and intelligent system. It uses advanced technical means to achieve collaborative work between vehicles and road infrastructure, providing strong support for the intelligent development of urban transportation.

[0004] However, there are still some shortcomings in its actual use. For example, the existing technology lacks an indicator system for comprehensive monitoring of the performance of urban bus intelligent assisted driving systems, making it difficult to achieve a comprehensive and accurate evaluation of the performance of urban bus intelligent assisted driving systems. This deficiency directly restricts the performance of urban bus intelligent assisted driving systems in practical applications, and may lead to problems such as unstable performance, false alarms or missed alarms in practical applications. Therefore, developing a new monitoring indicator system that can accurately reflect the performance of urban bus intelligent assisted driving systems is of great significance to improving the practicality of urban bus intelligent assisted driving systems. Summary of the invention

[0005] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides an urban bus intelligent assisted driving system based on vehicle-road cooperative technology, which solves the problems raised in the above-mentioned background technology through the following scheme.

[0006] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: an intelligent assisted driving system for urban public transportation based on vehicle-road cooperative technology, comprising a system central processing unit module, a system operation database and a user information terminal, and also comprising a vehicle-road cooperative perception module, a bus driving judgment module, a bus driving information acquisition module, a bus driving information mining module, a data standardization processing module, a bus driving information analysis module, an assisted driving system effect judgment module and a human-computer interaction module;

[0007] The system operation database includes all data texts of an urban public transportation intelligent assisted driving system based on vehicle-road cooperative technology, and collects information texts output by each module in real time. The system central processor module is used to centrally control the information text instructions output by each module. The user information terminal is an information output device for receiving an urban public transportation intelligent assisted driving system based on vehicle-road cooperative technology.

[0008] The vehicle-road cooperative perception module is used to obtain bus driving information data and road information data through sensors and GPS;

[0009] The bus driving judgment module is used to judge the real-time operation and driving route of the bus according to the bus driving information data and road information data;

[0010] The bus driving information acquisition module: filters the bus driving feature text according to different buses to obtain the bus driving feature text data, the number of screenings is recorded as 1, 2, 3, ..., i, and outputs the bus driving feature text data to the bus driving information mining module;

[0011] The bus driving information mining module includes a driving efficiency information collection unit, a driving safety information collection unit, a system performance information collection unit, and a bus energy consumption and environmental protection information collection unit, which is used to select a first key text from the bus driving characteristic text data to obtain a first key text, and output the first key text to the data standardization processing module;

[0012] The data standardization processing module is used to perform standardization processing and analysis on the first key text data to obtain the second key text, and output the second key text to the bus travel information analysis module;

[0013] The bus driving information analysis module is used to import the second key text data into the mathematical model of driving efficiency coefficient, the mathematical model of driving safety coefficient, the mathematical model of system performance coefficient, the mathematical model of vehicle energy consumption and environmental protection level coefficient, and the mathematical model of auxiliary driving system comprehensive evaluation coefficient, and process and analyze them to obtain a text output value based on the second key text, and output the text output value to the auxiliary driving system effect judgment module;

[0014] The auxiliary driving system effect judgment module is used to compare the comprehensive evaluation coefficient of the auxiliary driving system with the preset value, and input the comparison result into the human-computer interaction module;

[0015] Human-computer interaction module: used to import the comparison results into the user information terminal.

[0016] Preferably, the first key text in the bus travel information mining module is as follows:

[0017] The first key text specifically refers to an average driving speed parameter, an average travel time parameter, a congestion avoidance rate parameter, an accident occurrence rate parameter, an emergency braking number parameter, an obstacle avoidance success rate parameter, a system response time parameter, a system failure number parameter, a system accuracy parameter, an average fuel consumption rate parameter, and an average emission concentration parameter;

[0018] The average driving speed parameter refers to the average driving speed in the bus driving feature text data screened for the i-th time. ;

[0019] The average travel time parameter refers to the average travel time in the bus travel feature text data screened for the i-th time. ;

[0020] The congestion avoidance rate parameter refers to the congestion avoidance rate in the bus driving feature text data screened for the i-th time. ;

[0021] The accident rate parameter refers to the accident rate in the bus driving feature text data screened for the i-th time. ;

[0022] The emergency braking number parameter refers to the number of emergency braking times in the bus driving feature text data screened for the i-th time. ;

[0023] The obstacle avoidance success rate parameter refers to the obstacle avoidance success rate in the bus driving feature text data screened for the i-th time. ;

[0024] The system response time parameter refers to the system response time in the bus driving feature text data screened for the i-th time ;

[0025] The system failure number parameter refers to the number of system failures in the bus driving feature text data screened for the i-th time. ;

[0026] The system accuracy parameter refers to the system accuracy in the bus driving feature text data screened for the i-th time ;

[0027] The average fuel consumption rate parameter refers to the average fuel consumption rate in the bus driving feature text data screened for the i-th time ;

[0028] The average emission concentration parameter refers to the average emission concentration in the bus driving characteristic text data screened for the i-th time. .

[0029] Preferably, the sensor includes a laser radar, a camera, a millimeter wave radar and an inertial measurement unit, which are used to obtain environmental information around the bus in real time, such as speed, distance, acceleration, bus condition, road condition and traffic condition;

[0030] The laser radar refers to a device that can emit and receive laser beams to measure the distance, reflectivity and speed of objects. It can build a high-precision 3D model of the surrounding environment and provide accurate path planning and environmental perception for autonomous driving. Specific models include VelaDome, Velarray and Vella.

[0031] The cameras include a front-view camera, a surround-view camera and a side-view camera, which are used to obtain image information around the bus. The front-view camera is installed at the windshield and the rear-view mirror for forward driving assistance, covering distance measurement, object recognition, and road markings. The surround-view camera is installed at the front and rear signs of the bus to identify parking channel signs, road conditions and surrounding bus conditions. The side-view cameras are installed at the left and right rear-view mirrors for blind spot monitoring. The specific camera models include OV9284, VG5661 and VG5761, etc.;

[0032] The millimeter wave radar refers to equipment such as AWR1642 that uses the millimeter wave band for ranging and positioning, and has the ability to penetrate harsh environments such as fog, smoke, and dust, and is used to detect free space and obstacles around vehicle doors and trunks;

[0033] The inertial measurement unit is used to detect the speed, acceleration, direction and other motion states of the bus, and can perform real-time heading correction. Specific models include TDKIAM-20680 and IAM-20680HP;

[0034] The bus travel information data includes bus location information, bus travel destination information, obstacle direction information, distance information from the obstacle, bus relative speed information toward the obstacle, and bus relative acceleration information toward the obstacle;

[0035] The road information data includes road sign information, lane bus flow information, location information, traffic light time information and traffic light quantity information.

[0036] Preferably, the driving route determination method is as follows:

[0037] Generate multiple driving paths according to the bus destination information and the bus location information, prioritize the obtained road information, the first priority is the lane bus flow information, the second priority is the traffic light quantity information, the third priority is the traffic light time information, and judge the driving paths in turn according to the priority ranking to obtain the final driving path;

[0038] The real-time operation judgment method is as follows:

[0039] The collision time under the current driving state is obtained based on the obstacle direction information, the distance to the obstacle information, the relative speed information of the bus toward the obstacle, and the relative acceleration information of the bus toward the obstacle. If the collision time is less than the time required for emergency braking, the bus is controlled to slow down and move away from the obstacle.

[0040] Preferably, the mathematical model of the driving efficiency coefficient is as follows:

[0041] = ,in Refers to the driving efficiency coefficient, Refers to the average travel time in the bus travel feature text data screened for the i-th time, Refers to the average driving speed in the bus driving feature text data screened for the i-th time, Refers to the congestion avoidance rate in the bus driving feature text data screened for the i-th time, Refers to other influencing factors;

[0042] The mathematical model of the driving safety coefficient is specifically as follows:

[0043] = ,in Refers to the driving safety factor, Refers to the accident rate in the bus driving feature text data screened for the i-th time, Refers to the number of emergency braking times in the bus driving feature text data screened for the i-th time, Refers to the obstacle avoidance success rate in the bus driving feature text data screened for the i-th time, Refers to other influencing factors;

[0044] The mathematical model of the system performance coefficient is as follows:

[0045] = ,in Refers to the system performance coefficient, Refers to the system response time in the bus driving feature text data screened for the i-th time, Refers to the number of system failures in the bus driving feature text data screened for the i-th time, Refers to the system accuracy of the bus driving feature text data screened for the i-th time, Refers to other influencing factors;

[0046] The mathematical model of the vehicle energy consumption and environmental protection level coefficient is as follows:

[0047] = ,in Refers to the vehicle energy consumption and environmental protection level coefficient, which refers to the average fuel consumption rate in the bus driving characteristic text data screened for the i-th time. Refers to the average emission concentration in the bus driving feature text data screened for the i-th time, Refers to other influencing factors;

[0048] The mathematical model of the comprehensive evaluation coefficient of the auxiliary driving system is as follows:

[0049] = ,in Refers to the comprehensive evaluation coefficient of the auxiliary driving system. Refers to the driving efficiency coefficient, Refers to the driving safety factor, Refers to the system performance coefficient, Refers to the vehicle energy consumption and environmental protection level coefficient, , , , Refers to the weight coefficient;

[0050] The weight coefficient , , , It is calculated by the entropy method, and the specific calculation steps of the entropy method are as follows:

[0051] Data standardization: Since the measurement units of various indicators may be different, in order to eliminate the impact of the dimension, the collected data needs to be standardized. Commonly used standardization methods include Z-score standardization and range method standardization;

[0052] Calculate the proportion of indicators: Calculate the proportion of the zth sample value under the jth indicator to the sum of all sample values ​​of the indicator. This step is the basis for the subsequent calculation of information entropy;

[0053] Calculate information entropy: According to the definition and calculation formula of information entropy, calculate the information entropy ej of the jth indicator. The smaller the information entropy, the greater the degree of variation of the indicator and the greater the amount of information provided;

[0054] Calculate information entropy redundancy: Information entropy redundancy dj is the complement of information entropy, that is, dj=1-ej. The greater the information entropy redundancy, the more information the indicator contains, and the greater the impact on the comprehensive evaluation;

[0055] Calculate weight: Calculate the weight of each indicator in the comprehensive evaluation according to its information entropy redundancy. The weight coefficient is the ratio of the information entropy redundancy of each indicator to the sum of the information entropy redundancy of all indicators.

[0056] Preferably, the preset value is a warning value obtained based on practice to evaluate the impact of the assisted driving system on the bus's driving efficiency, driving safety, vehicle energy consumption and environmental protection level, and system performance. When the text output value is lower than the preset value, it means that the bus's driving efficiency is low, driving safety is poor, vehicle energy consumption is high, environmental protection level is low, and system performance is poor when the assisted driving system is used, and the assisted driving system needs to be improved.

[0057] Preferably, the user information terminal is an information output device that receives the text output value screened by the auxiliary driving system effect judgment module, including a smart phone, a tablet, a computer and other devices that can realize remote communication.

[0058] Technical effects and advantages of the present invention:

[0059] 1. The present invention obtains key parameters covering driving efficiency, driving safety, system performance, and bus energy consumption and environmental protection by deeply mining the driving characteristics text of buses. By integrating and comprehensively analyzing these multi-dimensional parameters, the present invention can accurately monitor and evaluate the performance of the assisted driving system in real time, and can timely discover potential deficiencies, providing a scientific basis for the maintenance and optimization of the assisted driving system, thereby ensuring the efficiency, stability and reliability of the assisted driving system, and laying a solid foundation for the practical application of the assisted driving system;

[0060] 2. The present invention creatively constructs a comprehensive and accurate mathematical model by deeply analyzing the detailed data mined. The model cleverly integrates the four core dimensions of driving efficiency, driving safety, system performance, and bus energy consumption and environmental protection, and realizes a comprehensive and integrated measurement of the performance of the assisted driving system. Through the establishment of this comprehensive model, the present invention not only significantly improves the accuracy and comprehensiveness of the evaluation, but also provides users with an intuitive and quantitative tool, enabling them to more accurately grasp the overall status of the assisted driving system. This innovative achievement not only provides a more scientific and reliable basis for users to judge the performance of the assisted driving system, but also provides strong technical support and guarantee for the safe and stable operation and subsequent maintenance and management of the assisted driving system. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] Figure 1 It is a schematic diagram of the overall structure of the present invention.

[0062] Figure 2 It is a schematic diagram of the structure of the bus travel information mining module of the present invention. DETAILED DESCRIPTION

[0063] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0064] As attached Figure 1 The urban bus intelligent assisted driving system based on vehicle-road cooperative technology shown includes a system central processing unit module, a system operation database and a user information terminal, and also includes a vehicle-road cooperative perception module, a bus driving judgment module, a bus driving information acquisition module, a bus driving information mining module, a data standardization processing module, a bus driving information analysis module, an assisted driving system effect judgment module and a human-computer interaction module.

[0065] The system operation database includes all data texts of an urban public transportation intelligent assisted driving system based on vehicle-road cooperative technology, and collects information texts output by each module in real time. The system central processor module is used to centrally control the information text instructions output by each module. The user information terminal is an information output device for receiving an urban public transportation intelligent assisted driving system based on vehicle-road cooperative technology.

[0066] The output end of the vehicle-road cooperative perception module is telecommunication connected to the input end of the bus driving judgment module, the output end of the bus driving judgment module is telecommunication connected to the input end of the bus driving information acquisition module, the output end of the bus driving information acquisition module is telecommunication connected to the input end of the bus driving information mining module, the output end of the bus driving information mining module is telecommunication connected to the input end of the data standardization processing module, the output end of the data standardization processing module is telecommunication connected to the input end of the bus driving information analysis module, the output end of the bus driving information analysis module is telecommunication connected to the input end of the assisted driving system effect judgment module, and the output end of the assisted driving system effect judgment module is telecommunication connected to the input end of the human-computer interaction module.

[0067] Vehicle-road cooperative perception module: used to obtain bus driving information data and road information data through sensors and GPS;

[0068] The sensors include laser radar, camera, millimeter wave radar and inertial measurement unit, which are used to obtain real-time environmental information around the bus, such as speed, distance, acceleration, bus condition, road condition and traffic condition;

[0069] The laser radar refers to a device that can emit and receive laser beams to measure the distance, reflectivity and speed of an object, and can build a high-precision 3D model of the surrounding environment to provide accurate path planning and environmental perception for autonomous driving. Specific models include VelaDome, Velarray and Vella, which are not specifically limited in this embodiment;

[0070] The cameras include a front-view camera, a surround-view camera and a side-view camera, which are used to obtain image information around the bus. The front-view camera is installed at the windshield and the rear-view mirror for forward driving assistance, covering distance measurement, object recognition, and road markings. The surround-view camera is installed at the front and rear vehicle signs of the bus to identify parking channel signs, road conditions and surrounding bus conditions. The side-view cameras are installed at the left and right rear-view mirrors for blind spot monitoring. The specific models of the cameras include OV9284, VG5661 and VG5761, etc., which are not specifically limited in this embodiment;

[0071] The millimeter wave radar refers to equipment such as AWR1642 that uses the millimeter wave band for ranging and positioning, and has the ability to penetrate harsh environments such as fog, smoke, and dust, and is used to detect free space and obstacles around vehicle doors and trunks;

[0072] The inertial measurement unit is used to detect the speed, acceleration, direction and other motion states of the bus, and can perform real-time heading correction. Specific models include TDKIAM-20680 and IAM-20680HP, etc., which are not specifically limited in this embodiment;

[0073] The bus travel information data includes bus location information, bus travel destination information, obstacle direction information, distance information from the obstacle, bus relative speed information toward the obstacle, and bus relative acceleration information toward the obstacle;

[0074] The road information data includes road sign information, lane bus flow information, location information, traffic light time information and traffic light quantity information;

[0075] Bus driving judgment module: used to judge the real-time operation and driving route of the bus based on the bus driving information data and road information data;

[0076] It should be specifically explained in this embodiment that the driving route determination method is as follows:

[0077] Generate multiple driving paths according to the bus destination information and the bus location information, prioritize the obtained road information, the first priority is the lane bus flow information, the second priority is the traffic light quantity information, the third priority is the traffic light time information, and judge the driving paths in turn according to the priority ranking to obtain the final driving path;

[0078] It should be specifically explained in this embodiment that the real-time operation determination method is as follows:

[0079] The collision time under the current driving state is obtained according to the obstacle direction information, the distance information from the obstacle, the relative speed information of the bus toward the obstacle, and the relative acceleration information of the bus toward the obstacle. If the collision time is less than the time required for emergency braking, the bus is controlled to slow down and move away from the obstacle.

[0080] Bus driving information acquisition module: filter bus driving feature texts according to different buses to obtain bus driving feature text data, the number of filter times is recorded as 1, 2, 3, ..., i, and the bus driving feature text data is output to the bus driving information mining module;

[0081] It should be specifically explained in this embodiment that the bus driving characteristic text data refers to the classification and screening of all data collected by the vehicle-road cooperative perception module according to the bus number, the number of screenings is the bus number, and the bus numbers are recorded as 1, 2, 3, ..., i in sequence, and the bus driving characteristic text data screened for the i-th time is all the data collected by the bus numbered i in the vehicle-road cooperative perception module;

[0082] As attached Figure 2 The bus driving information mining module shown includes a driving efficiency information collection unit, a driving safety information collection unit, a system performance information collection unit, and a bus energy consumption and environmental protection information collection unit, which is used to select a first key text from the bus driving characteristic text data to obtain a first key text, and output the first key text to the data standardization processing module;

[0083] The first key text in the bus travel information mining module in the preferred technical solution of this application is as follows:

[0084] It should be specifically noted that in this embodiment, the first key text specifically refers to an average driving speed parameter, an average travel time parameter, a congestion avoidance rate parameter, an accident occurrence rate parameter, an emergency braking number parameter, an obstacle avoidance success rate parameter, a system response time parameter, a system failure number parameter, a system accuracy parameter, an average fuel consumption rate parameter, and an average emission concentration parameter;

[0085] The average driving speed parameter refers to the average driving speed in the bus driving feature text data screened for the i-th time. ;

[0086] The average travel time parameter refers to the average travel time in the bus travel feature text data screened for the i-th time. ;

[0087] The congestion avoidance rate parameter refers to the congestion avoidance rate in the bus driving feature text data screened for the i-th time. ;

[0088] The accident rate parameter refers to the accident rate in the bus driving feature text data screened for the i-th time. ;

[0089] The emergency braking number parameter refers to the number of emergency braking times in the bus driving feature text data screened for the i-th time. ;

[0090] The obstacle avoidance success rate parameter refers to the obstacle avoidance success rate in the bus driving feature text data screened for the i-th time. ;

[0091] The system response time parameter refers to the system response time in the bus driving feature text data screened for the i-th time ;

[0092] The system failure number parameter refers to the number of system failures in the bus driving feature text data screened for the i-th time. ;

[0093] The system accuracy parameter refers to the system accuracy in the bus driving feature text data screened for the i-th time ;

[0094] The average fuel consumption rate parameter refers to the average fuel consumption rate in the bus driving feature text data screened for the i-th time ;

[0095] The average emission concentration parameter refers to the average emission concentration in the bus driving characteristic text data screened for the i-th time. ;

[0096] Data standardization processing module: used for standardizing and analyzing the first key text data to obtain the second key text, and outputting the second key text to the bus driving information analysis module;

[0097] It should be specifically noted that the standardization process specifically refers to Z-score standardization process, which converts the original data into a standardized Z-score by calculating the mean and standard deviation of the original data. This method can eliminate the magnitude differences between data, so that data of different magnitudes can be compared and comprehensively analyzed.

[0098] The bus driving information analysis module is used to import the second key text data into the mathematical model of driving efficiency coefficient, the mathematical model of driving safety coefficient, the mathematical model of system performance coefficient, the mathematical model of vehicle energy consumption and environmental protection level coefficient, and the mathematical model of auxiliary driving system comprehensive evaluation coefficient, and process and analyze them to obtain a text output value based on the second key text, and output the text output value to the auxiliary driving system effect judgment module;

[0099] It should be specifically explained in this embodiment that the mathematical model of the driving efficiency coefficient is as follows:

[0100] = ,in Refers to the driving efficiency coefficient, Refers to the average travel time in the bus travel feature text data screened for the i-th time, Refers to the average driving speed in the bus driving feature text data screened for the i-th time, Refers to the congestion avoidance rate in the bus driving feature text data screened for the i-th time, Refers to other influencing factors;

[0101] It should be specifically explained in this embodiment that the mathematical model of the driving safety coefficient is as follows:

[0102] = ,in Refers to the driving safety factor, Refers to the accident rate in the bus driving feature text data screened for the i-th time, Refers to the number of emergency braking times in the bus driving feature text data screened for the i-th time, Refers to the obstacle avoidance success rate in the bus driving feature text data screened for the i-th time, Refers to other influencing factors;

[0103] It should be specifically explained in this embodiment that the mathematical model of the system performance coefficient is as follows:

[0104] = ,in Refers to the system performance coefficient, Refers to the system response time in the bus driving feature text data screened for the i-th time, Refers to the number of system failures in the bus driving feature text data screened for the i-th time, Refers to the system accuracy of the bus driving feature text data screened for the i-th time, Refers to other influencing factors;

[0105] It should be specifically explained in this embodiment that the mathematical model of the vehicle energy consumption and environmental protection level coefficient is as follows:

[0106] = ,in Refers to the vehicle energy consumption and environmental protection level coefficient, which refers to the average fuel consumption rate in the bus driving characteristic text data screened for the i-th time. Refers to the average emission concentration in the bus driving feature text data screened for the i-th time, Refers to other influencing factors;

[0107] It should be specifically explained in this embodiment that the mathematical model of the comprehensive evaluation coefficient of the auxiliary driving system is as follows:

[0108] = ,in Refers to the comprehensive evaluation coefficient of the auxiliary driving system. Refers to the driving efficiency coefficient, Refers to the driving safety factor, Refers to the system performance coefficient, Refers to the vehicle energy consumption and environmental protection level coefficient, , , , Refers to the weight coefficient;

[0109] It should be specifically explained in this embodiment that the weight coefficient , , , It is calculated by the entropy method, and the specific calculation steps of the entropy method are as follows:

[0110] Data standardization: Since the measurement units of various indicators may be different, in order to eliminate the impact of the dimension, the collected data needs to be standardized. Commonly used standardization methods include Z-score standardization and range method standardization;

[0111] Calculate the proportion of indicators: Calculate the proportion of the zth sample value under the jth indicator to the sum of all sample values ​​of the indicator. This step is the basis for the subsequent calculation of information entropy;

[0112] Calculate information entropy: According to the definition and calculation formula of information entropy, calculate the information entropy ej of the jth indicator. The smaller the information entropy, the greater the degree of variation of the indicator and the greater the amount of information provided;

[0113] Calculate information entropy redundancy: Information entropy redundancy dj is the complement of information entropy, that is, dj=1-ej. The greater the information entropy redundancy, the more information the indicator contains, and the greater the impact on the comprehensive evaluation;

[0114] Calculate weight: Calculate the weight of each indicator in the comprehensive evaluation according to its information entropy redundancy. The weight coefficient is the ratio of the information entropy redundancy of each indicator to the sum of the information entropy redundancy of all indicators.

[0115] Assisted driving system effect judgment module: used to compare the comprehensive evaluation coefficient of the assisted driving system with the preset value, and input the comparison result into the human-computer interaction module;

[0116] What needs to be specifically explained in this embodiment is that the preset value is a warning value obtained based on practice to evaluate the impact of the assisted driving system on the bus's driving efficiency, driving safety, vehicle energy consumption and environmental protection level, and system performance. When the text output value is lower than the preset value, it means that the bus's driving efficiency is low, driving safety is poor, the vehicle energy consumption is high and the environmental protection level is low, and the system performance is poor when the assisted driving system is used, and the assisted driving system needs to be improved.

[0117] Human-computer interaction module: used to import the comparison results into the user information terminal.

[0118] What needs to be specifically explained in this embodiment is that the user information terminal is used to upload the text output value whose comparison result is lower than the preset value to the user information terminal, so as to help the user analyze the effect of the assisted driving system and give the reasons affecting the performance of the assisted driving system.

[0119] It should be specifically explained in this embodiment that the user information terminal is an information output device that receives the text output value screened by the auxiliary driving system effect judgment module, including a smart phone, a tablet, a computer and other devices that can remotely realize remote communication;

[0120] Secondly: In the drawings of the embodiments disclosed in the present invention, only the structures related to the embodiments disclosed in the present invention are involved, and other structures can refer to the general design. In the absence of conflict, the same embodiment and different embodiments of the present invention can be combined with each other;

[0121] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. An intelligent assisted driving system for urban public transportation based on vehicle-road cooperative technology, characterized in that: include: The system central processor module, system operation database and user information terminal also include vehicle-road cooperative perception module, bus driving judgment module, bus driving information acquisition module, bus driving information mining module, data standardization processing module, bus driving information analysis module, auxiliary driving system effect judgment module and human-computer interaction module; The system operation database includes all data texts of an urban public transportation intelligent assisted driving system based on vehicle-road cooperative technology, and collects information texts output by each module in real time. The system central processor module is used to centrally control the information text instructions output by each module. The user information terminal is an information output device for receiving an urban public transportation intelligent assisted driving system based on vehicle-road cooperative technology. The vehicle-road cooperative perception module is used to obtain bus driving information data and road information data through sensors and GPS; The bus driving judgment module is used to judge the real-time operation and driving route of the bus according to the bus driving information data and road information data; The bus driving information acquisition module: filters the bus driving feature text according to different buses to obtain the bus driving feature text data, the number of screenings is recorded as 1, 2, 3, ..., i, and outputs the bus driving feature text data to the bus driving information mining module; The bus driving information mining module includes a driving efficiency information collection unit, a driving safety information collection unit, a system performance information collection unit, and a bus energy consumption and environmental protection information collection unit, which is used to select a first key text from the bus driving characteristic text data to obtain a first key text, and output the first key text to the data standardization processing module; The data standardization processing module is used to perform standardization processing and analysis on the first key text data to obtain the second key text, and output the second key text to the bus travel information analysis module; The bus driving information analysis module is used to import the second key text data into the mathematical model of driving efficiency coefficient, the mathematical model of driving safety coefficient, the mathematical model of system performance coefficient, the mathematical model of vehicle energy consumption and environmental protection level coefficient, and the mathematical model of auxiliary driving system comprehensive evaluation coefficient, and process and analyze them to obtain a text output value based on the second key text, and output the text output value to the auxiliary driving system effect judgment module; The mathematical model of the driving efficiency coefficient is specifically as follows: = ,in Refers to the driving efficiency coefficient, Refers to the average travel time in the bus travel feature text data screened for the i-th time, Refers to the average driving speed in the bus driving feature text data screened for the i-th time, Refers to the congestion avoidance rate in the bus driving feature text data screened for the i-th time, Refers to other influencing factors; The mathematical model of the driving safety coefficient is specifically as follows: = ,in Refers to the driving safety factor, Refers to the accident rate in the bus driving feature text data screened for the i-th time, Refers to the number of emergency braking times in the bus driving feature text data screened for the i-th time, Refers to the obstacle avoidance success rate in the bus driving feature text data screened for the i-th time, Refers to other influencing factors; The mathematical model of the system performance coefficient is as follows: = ,in refers to the system performance coefficient, Refers to the system response time in the bus driving feature text data screened for the i-th time, Refers to the number of system failures in the bus driving feature text data screened for the i-th time, Refers to the system accuracy of the bus driving feature text data screened for the i-th time, Refers to other influencing factors; The mathematical model of the vehicle energy consumption and environmental protection level coefficient is as follows: = ,in Refers to the vehicle energy consumption and environmental protection level coefficient, Refers to the average fuel consumption rate in the bus driving feature text data screened for the i-th time, Refers to the average emission concentration in the bus driving feature text data screened for the i-th time, Refers to other influencing factors; The mathematical model of the comprehensive evaluation coefficient of the auxiliary driving system is as follows: = ,in Refers to the comprehensive evaluation coefficient of the auxiliary driving system. Refers to the driving efficiency coefficient, Refers to the driving safety factor, refers to the system performance coefficient, Refers to the vehicle energy consumption and environmental protection level coefficient, , , , Refers to the weight coefficient; The auxiliary driving system effect judgment module is used to compare the comprehensive evaluation coefficient of the auxiliary driving system with the preset value, and input the comparison result into the human-computer interaction module; Human-computer interaction module: used to import the comparison results into the user information terminal.

2. According to claim 1, the intelligent assisted driving system for urban public transportation based on vehicle-road cooperative technology is characterized by: The first key text in the bus travel information mining module is as follows: The first key text specifically refers to an average driving speed parameter, an average travel time parameter, a congestion avoidance rate parameter, an accident occurrence rate parameter, an emergency braking number parameter, an obstacle avoidance success rate parameter, a system response time parameter, a system failure number parameter, a system accuracy parameter, an average fuel consumption rate parameter, and an average emission concentration parameter; The average driving speed parameter refers to the average driving speed in the bus driving feature text data screened for the i-th time. ; The average travel time parameter refers to the average travel time in the bus travel feature text data screened for the i-th time. ; The congestion avoidance rate parameter refers to the congestion avoidance rate in the bus driving feature text data screened for the i-th time. ; The accident rate parameter refers to the accident rate in the bus driving feature text data screened for the i-th time. ; The emergency braking number parameter refers to the number of emergency braking times in the bus driving feature text data screened for the i-th time. ; The obstacle avoidance success rate parameter refers to the obstacle avoidance success rate in the bus driving feature text data screened for the i-th time. ; The system response time parameter refers to the system response time in the bus driving feature text data screened for the i-th time ; The system failure number parameter refers to the number of system failures in the bus driving feature text data screened for the i-th time. ; The system accuracy parameter refers to the system accuracy in the bus driving feature text data screened for the i-th time ; The average fuel consumption rate parameter refers to the average fuel consumption rate in the bus driving feature text data screened for the i-th time ; The average emission concentration parameter refers to the average emission concentration in the bus driving characteristic text data screened for the i-th time. .

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