Self-adaptive intersection signal control method

Abstract

The invention belongs to the field of urban traffic control, and provides a self-adaptive intersection signal control method. By installing vehicle monitors to detect the number of vehicles, the lengths of vehicle queues are acquired, and a signal control strategy for the next cycle is determined according to the lengths of vehicle queues at an intersection in the previous cycle. The method utilizes the vehicle detectors already arranged in a city to acquire traffic flow data and calculate the length of the queue of each lane, and the signal timing scheme of the next cycle is dynamically adjusted according to the different proportions of queue lengths. Taking a cycle as a unit, a timing scheme is calculated, the load of calculation is low, and moreover, the method also can achieve the purpose that intersection signals can be self-adaptively controlled according to the density of traffic flow. In addition, the algorithm of the method is simple, and the method has low requirement on hardware and construction quantity, and therefore is convenient to popularize.

Description

technical field [0001] The invention belongs to the field of urban traffic control, and in particular relates to an adaptive intersection signal control method. Background technique [0002] Traffic signal control takes the microscopic traffic flow at the intersection as the control object, allocates the right of way of the vehicle at the intersection with the phase and time as the scale, separates the conflicting traffic flow from the time, and conducts reasonable guidance and scheduling of the traffic flow, so as to reduce traffic accidents and improve traffic safety. The purpose of traffic safety and transportation efficiency. [0003] At present, the intersection signal control methods at home and abroad mainly include timing control, induction control and adaptive control. Timing control is suitable for intersections with large traffic volume and uniform traffic distribution; Uneven intersections, but when the traffic volume is heavy, it is impossible to adjust and opt...

AI Technical Summary

Problems solved by technology

However, the calculation of queue length is complicated, usually relying on multiple detectors or using video image data, real-time image processing requires a large amount of calculation, is expensive, and is easily affected by weather, and the reliability of the system is poor

At present, most cities have laid induction coils and other equipment to obtain real-time traffic information such as traffic volume, vehicle occupancy time, road occupancy rate, congestion level and queue length, but the traffic demand in all directions at the intersection is not necessarily balanced. The queue lengths are not necessarily

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