基于分层并行灾变粒子群算法的交通控制

Traffic signal control based on hierarchic parallel catastrophic particle swarm optimization algorithm

提出了分层并行策略结合灾变模型的混合粒子群算法——分层并行灾变粒子群算法(HPCPSO),它能提高算法的收敛性和稳定性。同时通过对交叉口交通情况的研究,把车辆延误、车辆停车数和能源消耗都纳入性能指标值,建立了区域交通协调控制优化模型。在此模型的基础上,应用分层并行灾变粒子群算法实现了交通信号优化控制及验证算法。仿真结果表明,分层并行灾变粒子群算法相对于基本粒子群算法提高了寻找全局最优解的能力,能够有效实现交通信号优化控制。

A hierarchic parallel catastrophic particle swarm optimization（HPCPSO） algorithm has been developed through introducing hierarchic parallel tactics and a cusp catastrophic model in particle swarm optimization algorithm,the new algorithm increases its con-vergence rate and stability.A new traffic control model based on value are presented,the contains traffic waiting delay,stops and start-ups.Based on the model,hierarchic parallel catastrophic particle swarm optimization algorithm can be applied to the optimal contro1 of traffic signal and examined.Simulation data shows that the new method proposed is feasible and efficient.