Automotive Adaptive Cruise Control, Follow The Mode Of Study

In modern society, people concern more on vehicle's performances as safety, comfort and intelligence. Adaptive cruise control (ACC) which comes of cruise control technique is the way to satisfy people and becomes one of the focuses of modern vehicle technique research. But the first generation of ACC applied currently is far from being satisfactory. It is highly desirable to develop a new generation of ACC. As the following mode is the most common working state of ACC, it becomes the focus of ACC research. This paper has discussed two aspects concerning the following mode of vehicle ACC, one is the safe distance of the following mode, the other is the control modeling of this mode.This paper proposes a new method to calculate the safe distance based on the results of frontal collision avoidance system's (FCAS) research. The new method has a few advantages over the existing method. It assumes that the two vehicles with the same speed lining in the same lane are stably running in the following mode. When the leading car decelerates, the following car will take various measures according the leading car's different status in order that they can keep critical safe distance and avoid chasing bump. This distance is the expected value of the ACC following distance. It takes many factors into account, such as velocity, deceleration etc. and is more thoughtful than former values. ACC system is very complicated. Fortunately fuzzy neural network (FNN) techniques can deal system such systems efficiently. This paper designs a FNN model to solve the associated control problem. A model in the form of fuzzy control table is created. This is a foundation for the next steps. Then a five-layer BP FNN is constructed. Cells of this network adopt the logic comparing computing method. This makes the network's working style more like human's so that it can adapt to different road conditions and be more robust.This paper discusses also the expressions and determination of the studying parameters for the FNN system. A simulation test adopting the data of the referred document is also performed. Analysis on the result proves that adaptive studying of the parameters can improve the precision of control and deduce the over-adjusting. Comparing with human drivers, this model's output is very personated and satisfying. It can also reduced over-adjusting .