The car following collision prevention controller based on the fuzzy basis function network
✍ Scribed by Jeich Mar; Feng-Jie Lin; Hung-Ta Lin; Li-Chin Hsu
- Publisher
- Elsevier Science
- Year
- 2003
- Tongue
- English
- Weight
- 448 KB
- Volume
- 139
- Category
- Article
- ISSN
- 0165-0114
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✦ Synopsis
The car following collision prevention controller based on the fuzzy basis function network (FBFN) to non-linearly control the car speed is presented. The distance and speed relative to the car in front are measured by a radar sensor and applied to the controller. The output acceleration or deceleration rate of the controller is based on the characteristics of the vehicles. The initial input and output membership functions and ÿve rules of FBFN are constructed by a fuzzy inference system. The design method of the reference signals, which is used to on-line update the consequent parameters according to the recursive least-squares algorithm, is proposed. The presented FBFN controller can solve the oscillation problems for ÿnal relative distance between the leading vehicle (LV) and the following vehicle (FV) and relative speed. The required processing time to achieve safe distance between the LV and the FV is about 6 -7 s that is faster than those proposed by other schemes. The FBFN car following collision prevention controller proposed in the paper can provide a safe, reasonable and comfortable drive.