Abstract
This study applies a modified cascaded fuzzy reasoning Petri net (CFRPN) model to analyze dangerous driving events on a freeway. The dangerous driving events can be divided into two groups: (1) the interaction between a driver's vehicle and the road environment, and (2) the interaction between a driver's vehicle and nearby vehicles. These two classes of driving events may occur simultaneously and lead to certain serious traffic situations. The proposed system analyzes these two kinds of events determines dangerous situations from data collected by various sensors. Since collecting real driving event data on freeway is dangerous and time consuming, a data generation system is developed to generate the experimental data. Such data can help evaluate the performance of the proposed analysis system. Finally, experimental results show that the proposed system is accurate and robust.
| Original language | English |
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| Title of host publication | Proceedings of ITSC 2006: 2006 IEEE Intelligent Transportation Systems Conference |
| Pages | 337-342 |
| Number of pages | 6 |
| Publication status | Published - 2006 |
| Event | ITSC 2006: 2006 IEEE Intelligent Transportation Systems Conference - Toronto, ON, Canada Duration: 2006 Sep 17 → 2006 Sep 20 |
Other
| Other | ITSC 2006: 2006 IEEE Intelligent Transportation Systems Conference |
|---|---|
| Country | Canada |
| City | Toronto, ON |
| Period | 06/9/17 → 06/9/20 |
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Keywords
- Active driver assistance system
- Driving event analysis
- Fuzzy reasoning Petri net
ASJC Scopus subject areas
- Engineering(all)