Patrol route planning method and system based on traffic violation hotspot prediction and readable storage medium

Abstract

The invention discloses a patrol route planning method and system based on traffic violation hotspot prediction and a readable storage medium, and the method specifically comprises the following steps: enabling discrete traffic violation events to be matched with a road network, and obtaining traffic violation hotspot candidate regions; extracting related spatial-temporal features of the traffic violation hotspot candidate regions to form a data set; extracting three groups of training data sets from the data set by adopting a boot-pulling sampling method, training three groups of prediction models by using the three groups of training data sets through collaborative training and active learning respectively, wherein a tree integration model is adopted as the prediction model; classifyingthe label-free traffic data by utilizing the three groups of prediction models, and predicting the distribution condition of future traffic violation hotspots; and modeling and optimizing a traffic police patrol route according to the traffic violation hotspot distribution condition. The method provided by the invention can perceive and predict traffic violation hotspots in a city in real time with low cost and high coverage, plans a traffic police patrol route, helps an urban traffic management department to comprehensively and deeply grasp the traffic violation hotspots in the city, and efficiently plans the traffic police patrol route.

Description

technical field [0001] The present invention relates to the field of traffic forecasting, in particular to a patrol route planning method, system and readable storage medium based on traffic violation hot spot forecasting. Background technique [0002] With the development of the economy, the number of urban motor vehicles has increased sharply, and various road traffic problems such as traffic accidents and traffic jams have caused great harm to the safety of people's lives and property. According to the data of the World Health Organization, more than one million people die in traffic accidents all over the world every year, causing the vast majority of countries to lose 3% of their GDP. According to the data released by the Ministry of Transport of China, the economic loss caused by traffic congestion accounts for 20% of the disposable income of the urban population, reaching 250 billion yuan per year. Among the various factors causing road traffic problems, the illegal ...

AI Technical Summary

Problems solved by technology

However, this method often needs to make a trade-off between path distance and route coverage by adjusting parameters, and cannot automatically adapt to the actual situation.

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