A Markov Chain-based Adaptive Induction Method for Intelligent Transportation Vehicles

Abstract

The invention discloses an intelligent traffic vehicle adaptive induction method based on a Markov chain. The intelligent traffic vehicle adaptive induction method based on the Markov chain comprisesthe steps that first, weather six elements and daylight time are obtained by various sensors, a weather block density map of a highway is established, a model based on the Markov chain is adopted to evaluate the weather, and traffic safety evaluation indexes are formed and stored in a cloud platform of a control center; second, vehicle speed information and vehicle stopping state information of acertain radar block are captured, and the information is stored in the cloud platform of the control center; and the cloud platform combines the traffic safety evaluation indexes, the vehicle speed information and the vehicle stopping state information to realize adaptive switching of an induction mode and intelligent induction of adjacent radar blocks. According to the intelligent traffic vehicleadaptive induction method based on the Markov chain, the environment is subjected to forecast evaluation on the basis of the Markov chain, the precision and the intellectualization of vehicle induction are realized, and the method has a wide application prospect.

Description

Technical field [0001] The present invention belongs to the field of intelligent transportation, and specifically relates to an intelligent transportation vehicle adaptive guidance method based on Markov chain. The method uses the Markov chain model to evaluate environmental factors and completes the adaptive switching of vehicle guidance modes and adjacent Push the traffic status information of the block. Background technique [0002] Existing guidance technologies often use guidance lights or guidance road signs for guidance. Guiding light guidance means that the control center measures and induces according to the overall weather conditions, and cannot effectively evaluate the special weather conditions such as local fog and rainfall, making the set guidance method unreasonable and prone to traffic accidents. Traffic signs have a single guiding function and are difficult to see in low visibility conditions, which have certain limitations. Therefore, it is very necessary to s...

AI Technical Summary

Problems solved by technology

Induction light induction is the control center's measurement induction based on the overall weather conditions. It cannot effectively evaluate the special weather conditions such as local fog and rainfall, which makes the set induction method unreasonable and prone to traffic accidents.

The traffic sign guidance function is single, and it is difficult to see clearly in low visibility conditions, which has certain limitations

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