Reversible lane optimization method considering traffic control and guidance collaboration

Abstract

The invention discloses a reversible lane optimization method considering traffic control and guidance collaboration. According to the method, a user selects a to-be-optimized road network and a to-be-optimized time period and inputs geometric characteristic data of a research road network and OD data in a research time period; the problem of reversible lane optimization considering traffic control and guidance collaboration is abstracted into a three-layer programming model, wherein an upper-layer model is a reversible lane optimization model based on non-linear 0-1 programming, a middle-layer model is a traffic control optimization model based on multi-target optimization, and a lower-layer model is a user equilibrium model considering intersection delay; and a heuristic iterative optimization algorithm is established to solve the three-layer programming model, wherein the upper-layer model is solved through a genetic algorithm, the middle-layer model is solved through a non-dominated sorting genetic algorithm, and the lower-layer model is solved through an iterative weighting method. Through the method, traffic control and guidance collaboration is introduced into reversible lane optimization.

Description

technical field [0001] The invention belongs to the field of traffic planning and management, and relates to a tidal lane optimization method considering traffic control and induction coordination, which improves the traffic efficiency of urban traffic road network under tidal congestion. Background technique [0002] Land use is the main factor affecting the characteristics of traffic demand. The spatial distribution of residential areas, employment areas, living facilities, and public facilities determines the total amount of travel, travel distance, and travel direction of urban residents. At present, the separation of jobs and residences is serious, resulting in tidal phenomena and traffic congestion. Tidal congestion reflects the contradiction between dynamic traffic demand and static traffic facilities. Combined with the tidal characteristics of road traffic flow, research on tidal lane optimization is an important means to solve the above contradictions. At present,...

AI Technical Summary

Problems solved by technology

However, for road networks with obvious tidal phenomena, only considering the collaborative optimization of traffic control and induction cannot solve the problem of traffic congestion very well, and it is necessary to further consider tidal lane optimization

However, comparing the research status of traffic control and induced collaborative optimization methods, it is found that: although some studies consider timing control, the model system ignores issues such as intersection phase design and the impact of delays in different flow directions on traffic allocation; some studies apply induction control , but the model has too many assumptions, and does not consider the acquisition of dynamic data at the practical application level. In the absence of data, the model is difficult to achieve the expected effect; in addition, in the research field of traffic control and induced collaborative optimization, little consideration is given to Modeling Problems for Tidal Lane Optimization

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