Research On Vehicle Longitudinal Controller Based On Neuro-Fuzzy Control

Intelligent Transportation Systems (ITS) technology is progressing at an ever-increasing rate, with exciting developments in all fronts. One important aspect of ITS is the advanced automotive automatic control technologies including longitudinal control, lateral control, automatic driving and platoon control.Automobile driving system is a complicated nonlinear system. Classical control techniques for longitudinal control commonly use precise system mathematical model and apply linearization and the optimum performance can not be achieved.In recent years, the research of Fuzzy Logic Control (FLC) and Artificial Neural Networks (ANN) and the application of them to automatic control are progressing rapidly. They have superiority in the uncertain model and non-linear system and time variant system control, due mostly to their being independent of precise mathematical model. On the other hand, they can benefit from each other in system modeling. So the research of Neuro-Fuzzy Control' s application in vehicle longitudinal control spreads out in the article.In the article, I establish vehicle model, design cruise Fuzzy Logic Controller, design vehicle-to-vehicle distance controller using ANFIS and optimize it via system simulation, create platoon controller by integrating speed and distance control. The control methods are proved to be promising by its simulation in Matlab.