Traffic safety evaluation method, system and device based on traffic conflict prediction

Abstract

The invention discloses a traffic safety evaluation method, system and device based on traffic conflict prediction, and the method comprises the steps: obtaining a corresponding reconstruction set group and a non-reconstruction set group of a traffic road in a limited region range, obtaining the data in a preset period corresponding to each set group in a historical time range, and obtaining a reconstruction set group and a non-reconstruction set group; and screening the continuous collision duration in the group to obtain extreme value collision duration distribution, applying the obtained data and the extreme value collision duration distribution to obtain a constructed traffic safety evaluation model, and applying the traffic safety evaluation model to obtain a traffic safety evaluation result. According to the invention, the traffic roads are evaluated in groups, so that the deviation of traffic safety evaluation results is reduced, and the accuracy and reliability of traffic safety evaluation are greatly improved.

Description

technical field [0001] The present invention relates to the field of traffic safety management, in particular to a traffic safety evaluation method, system and device based on traffic conflict prediction. Background technique [0002] Traffic safety evaluation is an important part of road traffic safety management. It can intuitively provide scientific support for traffic safety transformation and improvement measures, and provide a basis for traffic safety audit. Traditional traffic safety evaluation uses traffic accident data for evaluation, and traffic accident data The collection of traffic accidents requires a long process, so the quality of the data is unstable, and the reliability and reliability of the safety evaluation results obtained are not high. In addition, when using traffic accident data for safety evaluation, traffic accidents have already occurred, which is a passive evaluation The method is not real-time, and for some new traffic facilities without traffic...

AI Technical Summary

Problems solved by technology

[0002] Traffic safety evaluation is an important part of road traffic safety management. It can intuitively provide scientific support for traffic safety transformation and improvement measures, and provide a basis for traffic safety audit. Traditional traffic safety evaluation uses traffic accident data for evaluation, and traffic accident data The collection of traffic accidents requires a long process, so the quality of the data is unstable, and the reliability and reliability of the safety evaluation results obtained are not high. In addition, when using traffic accident data for safety evaluation, traffic accidents have already occurred, which is a passive evaluation The method is not real-time, and for some new traffic facilities without traffic accident records, traditional traffic safety evaluation cannot be carried out;

[0003] Compared with traffic accidents, the occurrence of traffic conflicts is more common, and traffic accidents will only occur after traffic conflict avoidance behaviors fail. The existing traffic safety evaluation obtains the safety evaluation results by observing the changes of traffic accidents over a period of time, but There are certain deficiencies: after the transformation of traffic facilities, only the reduction or increase in the number of traffic accidents indicates that the traffic safety effect has improved or decreased, and the qualitative safety evaluation results cannot be quantified, nor can it be judged whether the factors affecting the safety evaluation results are It is related to the influence of external factors, and the occurrence of random traffic accidents makes the data quality of the collected information unstable. Therefore, in the existing technology, only relying on the number of traffic accidents in a period of time has great impact on traffic safety. Evaluation, the obtained evaluation results are unstable and lack precision

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