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Implementation of a Fuzzy-Inference-Based, Low-Speed, Close-Range Collision-Warning System for Urban Areas
Journal Article
18-227-2-234
ISSN: 0954-4070
Sector:
Language:
English
Abstract
Traffic accidents are still increasing even though vehicles are becoming more intelligent to enhance driver convenience and safety. Single car-on-car rear impacts in urban areas have increased rapidly due to driver inattention. According to a Road Traffic Authority (ROTA) report in Korea in 2006, 85.2% of single car-on-car rear impact accidents occurred at less than 60 km/h, and 25.3% of the total occurred at between 30 km/h and 50 km/h. To prevent rear vehicle crashes in urban areas, automobile manufacturers have developed various low-speed, close-range collision-warning systems. This paper presents a low-speed, close-range collision-warning algorithm for urban areas using fuzzy inference. Experiments using an embedded microprocessor in the driving track demonstrated the feasibility of the proposed collision-warning system. The results indicate that the fuzzy inference-based, low-speed, close-range collision-warning system could reduce traffic accidents by alerting the driver to potential collisions.
Authors
- Man-Ho Kim - Pusan National Univ. Korea Institute of Industrial Technology Pukyong National Univ.
- Suk Lee - Pusan National Univ. Korea Institute of Industrial Technology Pukyong National Univ.
- Kyoung-Nam Ha - Pusan National Univ. Korea Institute of Industrial Technology Pukyong National Univ.
- Kyung-Chang Lee - Pusan National Univ. Korea Institute of Industrial Technology Pukyong National Univ.