An improved artificial fish swarm algorithm for traffic signal control

Q3 Mathematics
Bin Lu, Qiang Wang, Yang Wang
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引用次数: 0

Abstract

The excessive growth of car ownership has caused great pressure on urban traffic. The traffic congestion is the most acute problem. One of the main causes of traffic congestion is the unreasonable scheme of traffic signal timing at road intersections. In view of the limitation of Webster algorithm, we combine the artificial fish swarm algorithm, chaos search and feedback strategy based on the optimisation theory of the signal timing problem to solve this problem. Furthermore, we apply the algorithm to the field of the traffic signal control. We set the average of vehicle delays and parking numbers as the target and improve the target road intersection timing scheme by using the optimisation algorithm. This method enhances the capacity of the target intersection effectively. Taking the condition of the target road intersection and the basic data into consideration, we construct the simulation model of the road intersection through the VISSIM simulation modelling tool. Then we import the relevant data and obtain a new timing plan which sets a new cycle and the green light duration of each phase. Compared to the original method, the algorithm based on the artificial fish-swarm is feasible and effective.
一种改进的交通信号控制人工鱼群算法
汽车保有量的过度增长给城市交通带来了巨大的压力。交通堵塞是最严重的问题。交叉口交通信号配时方案不合理是造成交通拥堵的主要原因之一。鉴于韦伯斯特算法的局限性,我们结合人工鱼群算法、混沌搜索和基于信号时序优化理论的反馈策略来解决这一问题。并将该算法应用于交通信号控制领域。以车辆延误数和停车数的平均值为目标,利用优化算法对目标交叉口配时方案进行改进。该方法有效地提高了目标交叉口的通行能力。结合目标道路交叉口的条件和基础数据,通过VISSIM仿真建模工具构建道路交叉口的仿真模型。然后导入相关数据,得到一个新的定时方案,该方案设置了一个新的周期和每个相位的绿灯时长。与原方法相比,基于人工鱼群的算法是可行和有效的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
1.80
自引率
0.00%
发文量
3
期刊介绍: The IJSPM is a fully refereed publication providing an international forum for high-quality papers seeking to discuss simulation and process modelling issues.
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