- author = "S. Paul Sathiyan and A. Wisemin Lins and S. Suresh Kumar",
- title = "Optimization of {ACC} using Soft Computing Technique",
- journal = "International Journal of Computer Science and Information Security",
- year = "2011",
- volume = "9",
- number = "2",
- pages = "150--154",
- month = feb,
- keywords = "genetic algorithms, genetic programming, adaptive cruise control, fuzzy Logic Control",
- ISSN = "1947-5500",
-
URL = "
http://www.scribd.com/doc/50265760",
- broken = "http://www.docstoc.com/docs/73173040/Optimization-of-ACC-using-Soft-Computing-Technique",
- oai = "oai:doaj-articles:76e70384736cbe18b167329212a51451",
- abstract = "The important feature of the Adaptive Cruise Control (ACC) system is the ability to maintain a proper inter-vehicle gap based on the speed of leading vehicle and the desired distance. Adaptive Cruise Control operates in two modes (i) Velocity Control mode, (ii) Distance Control mode. ACC acts like a conventional Cruise Controller (CC) under velocity control mode. In the case of the distance control mode, the speed of the host vehicle is reduced according to the surrounding environment to maintain the safe distance between the leading vehicle and the host vehicle. 25 rules have been used in Fuzzy logic Controller (FLC) with the knowledge base of the system. The inputs of the FLC are distance error and the speed error. The host vehicle adapts to the lead vehicle speed changes and tries to maintain a proper distance between them. The performance of the FLC based ACC is improved by Genetic Algorithm to tune the fuzzy rule base. Genetic Programming is used to select the best rule out of the 25 for a corresponding input. The result showed a better improvement over the Fuzzy Controlled System.",
-
notes = "http://sites.google.com/site/ijcsis/
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