Intersection signal control method based on multiple intelligent agents

Abstract

The present invention relates to an intersection signal control method based on multiple intelligent agents, and belongs to the intelligent traffic intersection control technology field. The method realizes the traffic information real-time dynamic sharing by respectively establishing the intelligent agent models of the traffic entities, such as the vehicles, the road sections, the intersections, the signal lamps, etc., and by utilizing the interactivity and the coordinated cooperation among the multiple intelligent agents, and concretely comprises the three links of the signal cycle optimal regulation and control, the phase conflict green light signal control and the vehicle speed guide auxiliary control. The method can obtain the individual operation state of each vehicle intelligent agent real-timely, and can realize the dynamic interaction between the vehicle intelligent agents and a traffic control system via the speed guide. Meanwhile in allusion to a multi-intelligent agent traffic environment, the caused green light time waste is considered when no vehicle passes at the current phase while a whole phase cycle is optimized, the collision is avoided, and the total number of the vehicles passing the whole intersection is increased by switching to the conflicting phases, the queuing waiting time of the vehicles in phase conflict is reduced, and the average delay of the intersection and the parking times can be reduced effectively.

Description

technical field [0001] The invention belongs to the technical field of intelligent traffic intersection control, and relates to a multi-agent-based intersection signal control method. Background technique [0002] With the continuous acceleration of my country's urbanization process, the number of motor vehicles has increased rapidly, and the demand for road traffic has increased sharply. Although the government has continuously increased investment in urban transportation infrastructure construction in recent years, the problem of traffic congestion is still acute. Traffic congestion not only causes huge economic losses and deterioration of environmental quality, but even leads to the paralysis of urban functions. However, the continuous development of the economy is bound to cause the number of motor vehicles to continue to increase at a high speed for a long time. Only relying on strengthening the construction of transportation infrastructure cannot solve the problem fro...

AI Technical Summary

Problems solved by technology

[0005] Among them: offline control is the timing control method. Although the timing control is simple and easy to operate, it is not demand-responsive. Once the signal timing parameters are determined, they will not be adjusted with the change of traffic flow, so it cannot meet the actual traffic demand. ; Inductive control overcomes the deficiency of timing control, and can adapt to random changes in traffic demand to a certain extent, but in traditional inductive control methods, the green light time, especially the green light delay time may still not be fully utilized; although adaptive control can By adjusting the signal control parameters to change the cycle duration, phase sequence, etc. to meet the needs of the traffic system, but the algorithm complexity is high, the implementation is difficult, and it is not suitable for general promotion and application.

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