Intersection self-adaptive signal control method based on real-time queuing information

Abstract

The invention relates to an intersection self-adaptive signal control method based on real-time queuing information, which determines the control scheme of the optimal phase sequence S* and the optimal green light time g*(S*) according to the control state signal CS, and specifically comprises the following steps: S1: determining a phase sequence alternative set omega S according to the current queuing information and selecting an alternative phase sequence Si which is not yet optimized; S2-S6: solving the optimal solution and the optimal value of the phase sequence according to the constraint conditions; S7: checking whether all Si in the phase sequence alternative set omega S complete optimization; S8: taking out a set lambda S of S with the maximum CS value from the phase sequence alternative set omega S, finding out S with the minimum f* value from the lambda S to serve as an optimal phase sequence S*, and taking the corresponding green light time as an optimal green light time g*(S*). Compared with the prior art, the intersection self-adaptive signal control method has the advantages that the queuing information is used for replacing traditional fixed-point detection flow data as input, various control states are more scientifically and effectively identified, corresponding countermeasures are made, complex and changeable traffic environments can be dealt with, and the effects of reducing queuing and preventing queuing overflow are achieved.

Description

technical field [0001] The invention relates to the field of intelligent traffic control, in particular to an intersection adaptive signal control method based on real-time queuing information. Background technique [0002] Urban traffic plays a vital role in the development of the whole society. However, the problem of traffic congestion has become increasingly prominent and has become a major obstacle to the further development of cities. As the throat of the road network, the signalized intersection is the key to ensure the efficient and stable operation of urban traffic. At present, most of the existing traffic signal control systems at home and abroad use the traffic flow data collected by traditional fixed-point detectors as the basis to formulate and optimize the signal control scheme for intersections. Due to the high construction cost of the fixed-point detector, the difficulty in later maintenance, and the high damage rate, the detection error is large and the sig...

AI Technical Summary

Problems solved by technology

Due to the high construction cost of the fixed-point detector, the difficulty in later maintenance, and the high damage rate, the detection error is large and the signal control effect is affected. The existing traffic information collection methods and signal control methods are in urgent need of reform.

Images