Modeling and intelligent control design of car following behavior in real traffic flow

A. Khodayari, R. Kazemi, A. Ghaffari, N. Manavizadeh
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引用次数: 26

Abstract

The control of car following is essential to its safety and its operational efficiency. For this purpose, this paper builds a linear, continuous and time-delay model of car following. And then, presents a controller based on an adaptive network fuzzy inference system (ANFIS) for the car-following collision avoidance system to adaptively control the speed of the vehicle. The relative distance and relative speed to the in front car are measured and are applied to the controller. The output acceleration or deceleration rate of the controller is based on the characteristics of the vehicles. The presented ANFIS controller can solve the problems of the oscillations for final distance between the leader vehicle (LV) and the follower vehicle (FV) and their relative speed. The designed ANFIS controller is linked to the car following model. The simulation results show that the ANFIS control design is more effective and can provide a safe, reasonable, and comfortable drive than real driver.
真实交通流中汽车跟随行为建模与智能控制设计
汽车跟车控制对汽车的安全性和运行效率至关重要。为此,本文建立了一个线性、连续、时滞的汽车跟随模型。在此基础上,提出了一种基于自适应网络模糊推理系统(ANFIS)的汽车跟车避碰系统自适应控制车速的控制器。测量与前车的相对距离和相对速度,并将其应用于控制器。控制器的输出加减速速率是根据车辆的特性来决定的。所提出的ANFIS控制器可以解决前导车辆与跟随车辆之间的最终距离和相对速度的振荡问题。所设计的ANFIS控制器与汽车跟随模型相连接。仿真结果表明,与真实驾驶员相比,ANFIS控制设计更加有效,能够提供安全、合理、舒适的驾驶体验。
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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