摘要
为提高定时信号控制通行的效率与鲁棒性,提出一种多目标优化模型。将目标函数分为2层:第1层选择平均延误、停车次数、通行能力指标以优化交叉口通行效率;第2层选择车辆延误标准差以提高信号控制稳定性。对不同交通状态的交叉口进行分析,建立流量波动幅度与目标权重的关系,并采用遗传算法求解。结果表明,该模型能有效降低车辆的平均延误,提高信号配时的鲁棒性。
To improve efficiency and robustness of fixed time signal control,the paper establishes an adjustable multi-objective optimization model to optimize signal timing.The objective function consists of two sub-targets,of which the first sub-target including three indicators such as average delay,number of stops,traffic capacity is to optimize efficiency,and the second sub-target is to optimize stability of signal control by minimizing standard deviation of vehicle delay.Based on simulation and analysis of intersections under various traffic conditions,the study establishes the relationship between sub-target weights and flow fluctuating ranges.This paper uses genetic algorithm to solve it.Results show that the multi-objective optimization model reduces the average delay of vehicles and controls maximum delay effectively.
出处
《计算机工程》
CAS
CSCD
北大核心
2011年第6期27-29,共3页
Computer Engineering
基金
国家自然科学基金资助项目(60674062)
教育部高等学校博士学科点专项科研基金资助项目(20060422054)
山东省自然科学基金资助项目(ZR2009GM032)
山东大学自主创新基金资助项目(2009TS046)
关键词
多目标优化模型
鲁棒性
子目标权重
遗传算法
信号配时
multi-objective optimization model
robustness
weights of sub-targets
Genetic Algorithm（GA）
signal timing
