Traffic Signal Control Optimization Based on Fuzzy Neural Network

摘要：

With the development of road transport, traffic problems seriously interfere with the cities. Traffic Signal control optimization is the main way to solve this problem. This paper presents a control method which based on fuzzy neural network. Separately, using the number of vehicles on the queue for the current and next phase as input, as well as using green delay for the current phase as output Simulation results show that this method can effectively lower the average vehicle delay than the traditional signal timing method (Weber Staffa), thereby increasing the traffic capacity of the intersection. Given the traffic problems in harsh environment, a new function is added in the signal timing calculation, which reduces the average delay time effectively and optimizes the system better.

关键词： Intelligent Control Traffic Control Fuzzy neural network signal timing

作者: Dongyao JIA Zuo CHEN

作者单位: School of Electronics and Information Engineering, Advanced Control Systems Laboratory Beijing Jiaotong University Beijing,China

会议类型: 国际会议

会议名称: 2012 International Conference on Measurement,Information and Control(2012测量、信息与控制国际会议 ICMIC2012)

会议地点: 哈尔滨

会议语种:英文

页码: 1007-1010

在线出版日期: 2012-05-18（万方平台首次上网日期，不代表论文的发表时间）