City traffic optimization service method and system based on swarm intelligence

Abstract

The invention discloses a city traffic optimization service method and system based on swarm intelligence; the method comprises the following steps: simulating local traffic situations according to swarm intelligence, and selecting a local scheduling strategy allowing each vehicle driving time and the local traffic situations to reach balance according to the simulation result and a local trafficoptimization target; using swarm intelligence to simulate the global traffic situation, and selecting a global scheduling strategy allowing the local traffic situation and the global traffic situationto reach balance according to the simulation result and a global traffic optimization target; recommending optical routes for each participating vehicle according to the swarm intelligence calculation result, thus realizing city traffic optimization services; finally, using the method to realize the city traffic optimization service system based on swarm intelligence. The system comprises a vehicle mounted platform, a situation cognition system and a swarm intelligence decision and control system, and aims to improve the city traffic optimization service decision enforceability and validity.

Description

technical field [0001] The invention relates to a group intelligence-based urban traffic optimization service method and system, belonging to the field of intelligent traffic. Background technique [0002] The intelligent transportation system is a kind of system that effectively integrates advanced information technology, data communication transmission technology, electronic sensing technology, control technology and computer technology into the entire transportation management system, and plays a role in a wide range and in all directions. A real-time, accurate and efficient integrated transportation management system. Among them, the prediction and optimization of urban traffic status is an important part of intelligent transportation. Using artificial intelligence, big data and other methods to predict and optimize urban traffic conditions can alleviate urban traffic congestion and improve urban traffic operation efficiency. [0003] The traditional intelligent transp...

AI Technical Summary

Problems solved by technology

However, since the driving behavior of the vehicle is the embodiment of the will of the driver or passengers, the essence of the formation of the traffic state is the result of independent driving decisions made by each relatively independent vehicle based on the cognition of the traffic state. The result of ignoring the driving decisions of individual vehicles is that the traditional The judgment of the traffic situation by the intelligent transportation system is not accurate, so the current traffic optimization service can only provide qualitative guidance on a macro level, and it is difficult to apply it to the specific vehicle dispatching control process

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