[论文解读] Design Of Fuzzy Logic Traffic Controller For Isolated Intersections With Emergency Vehicle Priority System Using MATLAB Simulation

Mohit Jha, Shailja Shukla|arXiv (Cornell University)|May 5, 2014

Smart Parking Systems Research参考文献 11被引用 12

一句话总结

本文提出了一种基于模糊逻辑的孤立交叉口交通信号控制器，通过动态调整信号配时，利用排队长度和等待时间输入以最小化延误和拥堵。系统通过警报传感器集成紧急车辆优先通行功能，使救护车和消防车能够快速通过。MATLAB仿真结果表明，交通流得到改善，等待时间减少，尤其在紧急情况下表现更优。

ABSTRACT

Traffic is the chief puzzle problem which every country faces because of the enhancement in number of vehicles throughout the world, especially in large urban towns. Hence the need arises for simulating and optimizing traffic control algorithms to better accommodate this increasing demand. Fuzzy optimization deals with finding the values of input parameters of a complex simulated system which result in desired output. This paper presents a MATLAB simulation of fuzzy logic traffic controller for controlling flow of traffic in isolated intersections. This controller is based on the waiting time and queue length of vehicles at present green phase and vehicles queue lengths at the other phases. The controller controls the traffic light timings and phase difference to ascertain sebaceous flow of traffic with least waiting time and queue length. In this paper, the isolated intersection model used consists of two alleyways in each approach. Every outlook has different value of queue length and waiting time, systematically, at the intersection. The maximum value of waiting time and vehicle queue length has to be selected by using proximity sensors as inputs to controller for the ameliorate control traffic flow at the intersection. An intelligent traffic model and fuzzy logic traffic controller are developed to evaluate the performance of traffic controller under different pre-defined conditions for oleaginous flow of traffic. Additionally, this fuzzy logic traffic controller has emergency vehicle siren sensors which detect emergency vehicle movement like ambulance, fire brigade, Police Van etc. and gives maximum priority to him and pass preferred signal to it.

研究动机与目标

• 为应对车辆数量增加导致的城市交通拥堵问题。
• 设计一种实时交通控制系统，以最小化孤立交叉口的车辆等待时间和排队长度。
• 通过警报检测集成紧急车辆优先通行功能，实现快速响应。
• 利用MATLAB仿真评估系统在各种交通条件下的性能表现。
• 基于动态输入参数，通过模糊逻辑优化信号配时。

提出的方法

• 控制器以各方向的排队长度和等待时间作为主要输入，用于相位控制决策。
• 基于‘低’、‘中’和‘高’排队长度与等待时间的语义变量定义模糊逻辑规则。
• 动态调整相位时长，优先处理更长的排队，以减少整体延误。
• 通过警报传感器实现紧急车辆检测，触发立即分配绿灯信号。
• MATLAB仿真模型模拟一个具有两个方向各两个方向的孤立交叉口，每个方向具有独立的排队长度和等待时间。
• 系统使用近距离传感器检测最大排队长度和等待时间，以实现最优信号相位切换。

实验结果

研究问题

• RQ1 如何有效应用模糊逻辑来优化交通流量变化下孤立交叉口的信号配时？
• RQ2 紧急车辆优先通行对整体交通延误和排队管理有何影响？
• RQ3 与固定配时系统相比，实时检测排队长度和等待时间输入能否提升信号配时决策的准确性？
• RQ4 集成警报检测如何影响紧急车辆的信号响应时间？
• RQ5 模糊逻辑控制器在减少等待时间和排队长度方面实现了哪些性能提升？

主要发现

• 模糊逻辑控制器成功通过基于实时排队和延迟数据的动态信号相位调整，显著降低了平均车辆等待时间。
• 在检测到紧急车辆后数秒内即实现优先通行，显著缩短了救护车和消防车的响应时间。
• 系统在高峰时段表现出更稳定的交通流，所有方向的排队积压均有所减少。
• MATLAB仿真结果证实，该控制器在减少延误和排队长度方面优于固定配时信号系统。
• 近距离传感器的集成实现了最大排队长度的精确检测，提升了控制精度。
• 控制器在多种交通条件下均保持高效运行，验证了其鲁棒性和适应性。