Driving risk early warning system based on safety score

Abstract

The invention provides a system which comprises a safety score calculation module and belongs to the technical field of intelligent auxiliary driving, and the system comprises the safety score calculation module which calculates a safety score according to the actual condition of vehicle driving; the driving behavior analysis module is used for evaluating the overall driving behavior of the driver; according to the driving risk early-warning system, through specific analysis and scene induction of dangerous driving scenes and real-time calculation of vehicle driving safety scores, comprehensive, accurate and timely driving risk early-warning information is provided for the driver, the driving risk early-warning effect is improved, and the driving risk early-warning effect is improved. And the driving safety is effectively improved.

Description

Technical Field

[0001] This invention belongs to the field of intelligent assisted driving technology, specifically relating to a driving risk warning system based on safety scores. Background Technology

[0002] With the continuous increase in car ownership, the frequency of traffic accidents is also rising, and improper driving behavior is one of the main causes of traffic accidents. Analyzing and evaluating driver behavior has become an important research topic in order to improve it. Currently, many technologies use machine learning methods to detect dangerous driving behaviors, but these methods typically require collecting large amounts of dangerous driving data, are costly, and their accuracy still needs improvement.

[0003] Existing driving risk warning methods primarily rely on historical driver behavior for prediction. This approach suffers from low accuracy and fails to provide timely warnings of current dangerous driving behaviors. Furthermore, most existing advanced driver assistance systems (ADAS) and driver behavior monitoring systems only offer warnings, lacking further analysis and processing of warning effectiveness. Their warning functions are also limited and lack environmental adaptability. Therefore, a driving risk warning system is needed that can assess driver behavior in real time, accurately identify dangerous scenarios, and provide personalized improvement directions. This system should be able to combine vehicle driving safety scores to comprehensively assess driver behavior across daily, weekly, and monthly timeframes. It should also list specific scenarios where dangerous driving occurs, summarize dangerous driving behaviors into scenarios, and further reconstruct the dangerous situations at the time, providing drivers with a comprehensive and accurate overview of their driving capabilities and directions for improvement. Summary of the Invention

[0004] To achieve the above objectives, the technical solution of the present invention is as follows: a driving risk warning system based on safety scores, the system comprising a safety score calculation module, which calculates a safety score based on the actual driving conditions of the vehicle; a driving behavior analysis module, which evaluates the overall driving behavior of the driver; and a warning prompt module, which provides personalized warnings based on the driver's safety assessment results and historical assessment data.

[0005] Preferably, the safety score calculation module includes a safety score setting unit for setting the total safety score and the deduction values ​​corresponding to various dangerous driving behaviors; a driving data acquisition unit for collecting relevant data on vehicle driving; a dangerous scenario analysis unit for analyzing the collected driving data; and a score calculation unit for calculating the vehicle driving safety score based on the collected driving data, the dangerous scenario analysis results, and the preset deduction rules.

[0006] Preferably, the scoring calculation unit includes: The first sub-unit acquires data on the driver's dangerous driving behavior within the current time period, including the number of times dangerous driving behavior occurred and the specific scenario information for each dangerous driving behavior; The second sub-unit obtains the correspondence between the number of times dangerous driving behavior occurs and the actual number of times dangerous scenarios occur. This correspondence truly reflects the correlation between the number of times dangerous driving behavior occurs and the number of times dangerous scenarios occur. The third subunit, based on the correspondence obtained from the second subunit and the number of occurrences of each dangerous driving behavior in the dangerous driving behavior data obtained from the first subunit, accurately predicts the number of times the driver will encounter each dangerous scenario in the current time period. The fourth subunit generates corresponding warning information based on the number of times each dangerous scenario is predicted by the third subunit, and sends the warning information to the driver's terminal.

[0007] Preferably, the driving behavior analysis module includes: The first sub-unit acquires the driver's driving data at various time dimensions, including mileage, driving time, and the number of times dangerous driving behavior occurred. The second sub-unit calculates the driver's safety score across various time dimensions based on the acquired driving data. Specifically, the safety score is calculated as follows: Safety Score = 100 - Total Deductions / (Current Mileage / 1000 km), where the total deductions are the sum of the deductions for all dangerous driving behaviors. The third sub-unit generates an overall safety assessment report for the driver based on safety scores across various time dimensions, including the driver's average safety score, frequency of dangerous driving behaviors, and types of dangerous scenarios frequently encountered. The fourth subunit, in conjunction with ADAS, AEB, or BSD devices, recreates the dangerous scenario at the time through the in-vehicle terminal, and displays the driver's driving behavior characteristics and safety assessment results.

[0008] Preferably, the early warning module includes: The first sub-unit acquires the driver's historical safety assessment data, including the safety assessment results for the most recent 30, 60, and 90 days. The second sub-unit analyzes the driver's safety assessment trends based on the acquired historical data and generates a safety assessment change curve. The third subunit, based on the safety assessment change curve, current driving behavior, and environmental data, performs a safety assessment to determine whether there are any abnormal changes in the safety assessment of the driver's current driving behavior. The fourth subunit generates and sends a warning message to the driver's terminal if any abnormal changes occur, prompting the driver to pay attention to improving their driving behavior.

[0009] Preferably, the system further includes a data storage module for storing vehicle driving data, dangerous driving scenario information, and driver safety assessment results data.

[0010] Preferably, in the safety scoring setting unit, the total score is 100 points, the deduction value for the highest level of dangerous driving behavior is 3 points, the deduction value for the second highest level of dangerous driving behavior is 2 points, and the deduction value for the general level of dangerous driving behavior is 1 point.

[0011] Preferably, the driving data acquisition unit includes vehicle mileage, driving time, and the number of times dangerous driving behavior occurred.

[0012] Preferably, the dangerous scenario analysis unit includes identifying dangerous driving scenarios that occur to the driver during driving and classifying and grading them according to the degree of danger.

[0013] Compared with the prior art, the beneficial effects of the present invention are as follows: 1. This invention employs a tiered deduction mechanism to conduct refined assessments of different levels of dangerous driving situations. Unlike typical attribution analysis, this deduction system directly reflects the driver's current driving risk based on the frequency of current risk events. A safety score is calculated by summing all deductions for a single day. This approach, starting from the perspective of risk issues, enables in-depth analysis of the driver's personalized driving behavior in response to various risk events in the current environment, improving the accuracy and reliability of early warnings. 2. This invention combines vehicle driving safety scores to comprehensively assess driver behavior across time dimensions (immediate, daily, weekly, and monthly), enabling timely warnings of current dangerous driving behaviors. This overcomes the limitations of existing technologies that rely solely on historical behavior for prediction, significantly improving the accuracy of warnings. 3. This invention summarizes dangerous driving behaviors by listing specific scenarios in which dangerous driving occurs, and further reconstructs the dangerous scenarios at the time by cooperating with ADAS, AEB, BSD and other equipment, providing drivers with a comprehensive and accurate overview of their driving capabilities, effectively solving the problems of existing technologies such as single warning function, poor environmental adaptability and weak targeting; 4. This invention can help drivers summarize which scenarios they frequently experience over a monthly time dimension, and summarize their personalized driving behavior deficiencies, providing a clear direction for improving their driving behavior and solving the problem of existing technologies lacking analysis of drivers' personalized needs. 5. This invention provides drivers with comprehensive, accurate, and timely driving risk warning information by specifically analyzing and summarizing dangerous driving scenarios, combined with real-time calculation of vehicle driving safety scores, effectively improving driving safety. Attached Figure Description

[0014] Figure 1 This is a product flowchart. Detailed Implementation

[0015] The present invention will be further illustrated below with reference to the accompanying drawings and specific embodiments. It should be understood that the following specific embodiments are for illustrative purposes only and are not intended to limit the scope of the invention. Example

[0016] The purpose of this invention is to overcome the shortcomings of existing technologies and provide a driving behavior assessment and early warning system based on vehicle driving safety scores. This system includes: I. Safety Score Calculation Module: This module calculates the safety score based on the actual driving conditions of the vehicle. It includes: (1) Safety score setting unit, used to set the total score of safety score and the deduction value corresponding to various dangerous driving behaviors, wherein the total score is 100 points, the deduction value corresponding to the highest level of dangerous driving behavior is 3 points, the deduction value corresponding to the second highest level of dangerous driving behavior is 2 points, and the deduction value corresponding to the general level of dangerous driving behavior is 1 point. (2) Driving data acquisition unit, used to collect relevant data on vehicle driving, including vehicle mileage, driving time, number of times dangerous driving behavior occurred, etc.; (3) Dangerous scene analysis unit, used to analyze the collected driving data, identify dangerous driving scenarios that the driver encounters during driving, and classify and grade them according to the degree of danger; (4) A scoring calculation unit, used to calculate the vehicle's safety score based on the collected driving data, the results of hazardous scenario analysis, and the preset deduction rules, specifically including: 1) First sub-unit: Acquire data on the driver's dangerous driving behavior within the current time period, including the number of times dangerous driving behavior occurred and the specific scenario information for each dangerous driving behavior; 2) Second sub-unit: Obtain the correspondence between the number of times dangerous driving behavior occurs and the actual number of times dangerous scenarios occur. This correspondence truly reflects the correlation between the number of times dangerous driving behavior occurs and the number of times dangerous scenarios occur. 3) Third sub-unit: Based on the correspondence obtained from the second sub-unit and the number of occurrences of each dangerous driving behavior in the dangerous driving behavior data obtained from the first sub-unit, accurately predict the number of times the driver will encounter each dangerous scenario in the current time period; 4) Fourth sub-unit: Based on the number of times each dangerous scenario is predicted by the third sub-unit, generate corresponding warning information and send the warning information to the driver terminal.

[0017] II. Driving Behavior Analysis Module, used to evaluate the driver's overall driving behavior, including: (1) First sub-unit: Acquire the driver's driving data in the daily, weekly and monthly time dimensions, including driving mileage, driving time, number of dangerous driving behaviors, etc.; (2) Second sub-unit: Based on the acquired driving data, calculate the driver's safety score in each time dimension, specifically including: Safety score = 100 - total deductions / (current driving mileage / 1000 km), where the total deductions are the sum of the deductions for all dangerous driving behaviors; (3) Third sub-unit: Based on the safety scores of each time dimension, generate an overall safety assessment report for the driver, including the driver's average safety score, frequency of dangerous driving behavior and types of dangerous scenarios frequently experienced; (4) Fourth sub-unit: Combining advanced equipment such as ADAS, AEB, BSD, etc., the dangerous scene at that time is restored through the vehicle terminal, and the driver is shown his driving behavior characteristics and safety assessment results.

[0018] III. Early Warning Module: This module provides personalized warnings based on the driver's safety assessment results and historical assessment data, including: (1) First subunit: Obtain the driver's historical safety assessment data, including the safety assessment results for the most recent 30 days, 60 days, and 90 days; (2) Second sub-unit: Based on the acquired historical data, analyze the driver's safety assessment trend and generate a safety assessment change curve; (3) Third subunit: Based on the safety assessment change curve; current driving behavior and environmental data, conduct a safety assessment to determine whether there are any abnormal changes in the safety assessment of the driver's current driving behavior; (4) Fourth sub-unit: If abnormal changes occur in a short period of time, generate and send warning information to the driver terminal to remind the driver to pay attention to improving his driving behavior.

[0019] Fourth, the system also includes a data storage module for storing vehicle driving data, dangerous driving scenario information, and driver safety assessment results.

[0020] In summary, the present invention provides a driving behavior assessment and early warning system based on vehicle driving safety scores. The system includes a safety score calculation module, a driving behavior analysis module, an early warning module, and a data storage module.

[0021] The safety score calculation module includes a safety score setting unit, a driving data acquisition unit, a hazardous scenario analysis unit, and a score calculation unit. The safety score setting unit sets the total score to 100 points, with 3 points deducted for the highest level of dangerous driving behavior, 2 points for the next highest level, and 1 point for a general level. The driving data acquisition unit collects relevant vehicle driving data, including mileage, driving time, and the number of times dangerous driving behaviors occurred. The hazardous scenario analysis unit analyzes the collected driving data, identifies hazardous driving scenarios encountered by the driver, and classifies them according to their degree of danger. The score calculation unit calculates the vehicle's safety score based on the collected driving data, the hazardous scenario analysis results, and the preset deduction rules.

[0022] II. The driving behavior analysis module includes four sub-units: the first sub-unit, the second sub-unit, the third sub-unit, and the fourth sub-unit. The first sub-unit acquires the driver's driving data at various time dimensions, including daily, weekly, and monthly, such as mileage, driving time, and the number of times dangerous driving behaviors occurred.

[0023] The second subunit calculates the driver's safety score across various time dimensions based on the acquired driving data. Specifically, the safety score is calculated as follows: Safety Score = 100 - Total Deductions / (Current Mileage / 1000 km), where the total deductions are the sum of the deductions for all dangerous driving behaviors.

[0024] The third subunit generates an overall safety assessment report for drivers based on safety scores across various time dimensions, including the driver's average safety score, frequency of dangerous driving behaviors, and types of dangerous scenarios frequently encountered.

[0025] The fourth subunit combines advanced equipment such as ADAS, AEB, and BSD to recreate the dangerous scenario at the time through the vehicle terminal, and show the driver the characteristics of their driving behavior and the safety assessment results.

[0026] The early warning module includes a first sub-unit, a second sub-unit, a third sub-unit, and a fourth sub-unit.

[0027] The first subunit acquires the driver's historical safety assessment data, including the safety assessment results for the most recent 30, 60, and 90 days.

[0028] The second subunit analyzes the driver's safety assessment trends based on the acquired historical data and generates a safety assessment change curve.

[0029] The third subunit determines whether there are any abnormal changes in the driver's safety assessment based on the safety assessment change curve and the safety assessment results of the current driving behavior.

[0030] If an abnormal change occurs in the fourth subunit, a warning message will be generated and sent to the driver's terminal to remind the driver to improve their driving behavior.

[0031] IV. The data storage module is used to store vehicle driving data, dangerous driving scenario information, and driver safety assessment results.

[0032] It should be noted that the above content merely illustrates the technical concept of the present invention and should not be construed as limiting the scope of protection of the present invention. For those skilled in the art, various improvements and modifications can be made without departing from the principle of the present invention, and all such improvements and modifications fall within the scope of protection of the claims of the present invention.

Claims

1. A driving risk warning system based on safety scoring, characterized in that, The system includes a safety score calculation module, which calculates a safety score based on the actual driving conditions of the vehicle. The driving behavior analysis module evaluates the driver's overall driving behavior. The early warning module provides personalized warnings based on the driver's safety assessment results and historical assessment data.

2. The system according to claim 1, characterized in that, The safety score calculation module includes a safety score setting unit for setting the total safety score and the deduction values ​​corresponding to various dangerous driving behaviors; and a driving data acquisition unit for collecting relevant vehicle driving data. The hazardous scenario analysis unit is used to analyze the collected driving data; The scoring calculation unit is used to calculate the vehicle's safety score based on the collected driving data, the results of hazardous scenario analysis, and the preset deduction rules.

3. The system according to claim 2, characterized in that, The scoring calculation unit includes: The first sub-unit acquires data on the driver's dangerous driving behavior within the current time period, including the number of times dangerous driving behavior occurred and the specific scenario information for each dangerous driving behavior; The second sub-unit obtains the correspondence between the number of times dangerous driving behavior occurs and the actual number of times dangerous scenarios occur. This correspondence truly reflects the correlation between the number of times dangerous driving behavior occurs and the number of times dangerous scenarios occur. The third subunit, based on the correspondence obtained from the second subunit and the number of occurrences of each dangerous driving behavior in the dangerous driving behavior data obtained from the first subunit, accurately predicts the number of times the driver will encounter each dangerous scenario in the current time period. The fourth subunit generates corresponding warning information based on the number of times each dangerous scenario is predicted by the third subunit, and sends the warning information to the driver's terminal.

4. The system according to claim 1, characterized in that, The driving behavior analysis module includes: The first sub-unit acquires the driver's driving data at various time dimensions, including mileage, driving time, and the number of times dangerous driving behavior occurred. The second sub-unit calculates the driver's safety score across various time dimensions based on the acquired driving data. Specifically, the safety score is calculated as follows: Safety Score = 100 - Total Deductions / (Current Mileage / 1000 km), where the total deductions are the sum of the deductions for all dangerous driving behaviors. The third sub-unit generates an overall safety assessment report for the driver based on safety scores across various time dimensions, including the driver's average safety score, frequency of dangerous driving behaviors, and types of dangerous scenarios frequently encountered. The fourth subunit, in conjunction with ADAS, AEB, or BSD devices, recreates the dangerous scenario at the time through the in-vehicle terminal, and displays the driver's driving behavior characteristics and safety assessment results.

5. The system according to claim 1, characterized in that, The early warning module includes: The first sub-unit acquires the driver's historical safety assessment data, including the safety assessment results for the most recent 30, 60, and 90 days. The second sub-unit analyzes the driver's safety assessment trends based on the acquired historical data and generates a safety assessment change curve. The third subunit, based on the safety assessment change curve, current driving behavior, and environmental data, performs a safety assessment to determine whether there are any abnormal changes in the safety assessment of the driver's current driving behavior. The fourth subunit generates and sends a warning message to the driver's terminal if any abnormal changes occur, prompting the driver to pay attention to improving their driving behavior.

6. The system according to claim 1, characterized in that, The system also includes a data storage module for storing vehicle driving data, dangerous driving scenario information, and driver safety assessment results.

7. The system according to claim 2, characterized in that, In the safety scoring setting unit, the total score is 100 points. The highest level of dangerous driving behavior corresponds to a deduction of 3 points, the next highest level of dangerous driving behavior corresponds to a deduction of 2 points, and the general level of dangerous driving behavior corresponds to a deduction of 1 point.

8. The system according to claim 2, characterized in that, The driving data acquisition unit includes vehicle mileage, driving time, and the number of times dangerous driving behavior occurred.

9. The system according to claim 2, characterized in that, The hazardous scenario analysis unit includes identifying hazardous driving scenarios that occur to the driver during driving and classifying and grading them according to the degree of danger.

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