Large-scale road network group traffic induction task decomposing method

Abstract

The invention discloses a large-scale road network group traffic induction task decomposing method, and belongs to the field of smart traffic, in particular to a large-scale road network group trafficinduction task decomposing method capable of changing signal timing dial. In a conventional path induction, a single function is difficult to describe a mutual relation among a plurality of variables. A plurality of target functions are established for optimal processing. The problem is solved by adopting an immune genetic algorithm, and the immune genetic algorithm is combined with an optimal heuristic search algorithm which adopts an immune theory and a genetic algorithm, and the advantages of the two kinds of algorithms are kept. The problem that the genetic algorithm is lost in local optimal solution is solved, the immune genetic algorithm has search feature, the optimal self-adaptive feature is solved by using a target function, and over-quick local convergence is avoided. A large-scale road network is decomposed into a plurality of induction cells, an induction strategy based on a tree structure chart is adopted, and an induction task is decomposed layer by layer for building aroad network to serve as a specific example for verifying the effectiveness and superiority of the method.

Description

technical field [0001] The invention designs a practical model, which belongs to the category of intelligent transportation, specifically a method for decomposing traffic flow induction tasks of large-scale road network groups that can dynamically change signal timing. Background technique [0002] With the acceleration of urban development and the improvement of people's living standards, the number of motor vehicles is also increasing year by year. According to statistics from the Ministry of Public Security, as of the end of 2017, the number of motor vehicles in China reached 310 million. In terms of distribution, there are 24 cities in the country with more than 2 million motor vehicles, and 7 cities with more than 3 million vehicles. The urban road network load is increasing year by year, and traffic congestion is becoming more and more serious. The intelligent process of road network traffic flow induction lags behind the current demand. Therefore, effective road netw...

AI Technical Summary

Problems solved by technology

However, in reality, there are often multiple variables that are mutually constrained, and it is difficult for a single function to describe the relationship between multiple variables

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