基于TdPN的中小流量交叉口信号控制研究

Signal Control of Small and Medium Flow Intersection Based on Timed Petri Net

摘要:

针对城市中小流量交叉口交通拥堵问题，提出了一种基于时延Petri网(Timed Petri Net, TdPN)的可变相序信号控制模型。利用TdPN建立交叉口车流模型和信号控制模型，结合马尔可夫链，建立交通流的动态生成模型。通过将通行权赋予当前等待车辆数最大的相位来实现相位的随机选择。以平均延迟时间最小为优化目标，通过遗传算法求解最优相位配时。在信号周期固定的情况下，分析基于TdPN的四相位可变相序控制模型在不平衡交通流下对交叉口平均排队长度的影响，并将此模型与四相位固定相序控制模型进行对比。研究结果表明，该方案在单位时间内有效地减少了交叉口的平均排队长度。

Abstract:

Aiming at the traffic congestion problem of small and medium traffic intersections in cities, this paper proposed a variable phase sequence signal control model based on Timed Petri Net(TdPN). This paper used TdPN to establish the intersection traffic model and signal control model and also used Markov chain to establish the dynamic generation model of traffic flow. This paper assign a grant to the phase which had the largest number of waiting vehicles to select phase randomly. With the minimum average delay time as the optimization goal, this paper used genetic algorithm to solve the optimal phase timing. In the case of fixed signal period, this paper analysis the influence of TdPN-based four-phase variable phase sequence control model on the average queue length of intersections under unbalanced traffic flow. The simulation compared this with the four-phase fixed phase sequence control model. The research results show the scheme reduced the average queue length of intersections per unit time.