Digital hormone-based traffic control optimization method

Abstract

The invention relates to a digital hormone-based traffic control optimization method. A digital hormone theory is applied to traffic coordination control, the dynamic characteristics of traffic flow distribution and signal control are fully considered, a traffic flow distribution and signal lamp control coordination model is established, and the digital hormone-based traffic control optimization method is applied to the solution of the coordination problem of traffic flow distribution and signal lamp control. The method is a totally distributed control method, and the problems of uncertainness, randomness, nonlinearity, locality and the like of a traffic system can be well solved by the method. In addition, compared with other intelligent algorithms, the method has the advantages that: the structure is simple, performance is stable, and modifiability and expandability are high.

Description

technical field [0001] The invention relates to the technical field of intelligent traffic, in particular to a digital hormone-based traffic control optimization method. Background technique [0002] The mass popularity of vehicles has brought us convenience, but it has also caused many traffic problems and some subsidiary crises. The whole world is eager to solve these problems. Traffic problems are especially serious in large and medium-sized cities, and for them, the overall architectural planning has been finalized, and it is difficult to improve the communication efficiency of roads in terms of "hardware". Signal light control is one of the most important functional sub-modules in the intelligent transportation system, and it is also one of the most important means to improve the efficiency of the traffic system. Relevant scholars have proposed many algorithm theories applied to the signal light control system, mainly including neural network and genetic algorithm. And...

AI Technical Summary

Problems solved by technology

Traffic problems are especially serious in large and medium-sized cities, and for them, the overall architectural planning has been finalized, and it is difficult to improve the communication efficiency of roads in terms of "hardware"

Signal light control is one of the most important functional sub-modules in the intelligent transportation system, and it is also one of the most important means to improve the efficiency of the traffic system. Relevant scholars have proposed many algorithm theories applied to the signal light control system, mainly including neural network and genetic algorithm. and fuzzy control, etc., but they generally have disadvantages such as complex calculation, poor fault tolerance, difficult expansion, and poor real-time performance.

In addition, the existing systems focus on the timing optimization of signal lamps, that is, they are limited to the calculation of the three basic control attributes of signal lamp cycle length, green signal ratio, and phase difference, which cannot achieve ideal results.

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