Traffic guidance scheduling system based on particle swarm optimization algorithm and scheduling method thereof

Abstract

The invention discloses a traffic guidance scheduling system based on a particle swarm optimization algorithm and a scheduling method thereof, and belongs to the field of traffic control. The system comprises a guidance strategy making module, a guidance information generating module and a guidance information issuing module; the guidance information making module is used for making a management strategy according to the change of the traffic flow state and sending the management strategy to the guidance information generation module; the induction information generation module is used for generating driving time, traffic jam, driving distance and other indicative or inductive traffic information according to an induction strategy and sending the information to the induction information release module; and the induction information issuing module is used for issuing induction information to travelers. According to the method, constraints such as the flow, the inflow rate and the green time ratio are combined, the minimum sum of the road network driving time and the delay time serves as a target function, optimization is conducted through the particle swarm optimization, balanced distribution of the road network traffic flow is achieved, and the operation performance of the road network is effectively improved.

Description

technical field [0001] The invention belongs to the field of traffic control, and in particular relates to a traffic guidance scheduling system based on a particle swarm optimization algorithm and a scheduling method thereof. Background technique [0002] With the rapid development of the city and the improvement of the quality of life, the problem of traffic congestion is becoming more and more serious. It is very important to improve the measures and methods of traffic guidance. The traffic guidance system optimizes the flow distribution of the entire road network at the macro level, while the urban traffic system is a complex whole, and it is necessary to optimize the management of the city from the macro and micro levels. Therefore, in order to improve the efficiency, adjusting the travel time of the intersection on the micro level makes the research more comprehensive. [0003] The traditional traffic guidance technology focuses on how to obtain an optimized traffic fl...

AI Technical Summary

Problems solved by technology

[0003] The traditional traffic guidance technology focuses on how to obtain the optimized traffic flow allocation plan, ignoring the research on how to effectively conduct traffic guidance and diversion for travelers, and there is a certain deviation between the calculation of travel time and the actual situation, while solving the model When , the travel needs of travelers in the road network are ignored, resulting in the optimal solution obtained by solving the model is not the optimal solution of the road network traffic management scheme

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