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 |
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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)
Cite this
Dangerous driving event analysis system by a cascaded fuzzy reasoning Petri net. / Fang, C. Y.; Hsueh, H. L.; Chen, S. W.
Proceedings of ITSC 2006: 2006 IEEE Intelligent Transportation Systems Conference. 2006. p. 337-342 1706764.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Dangerous driving event analysis system by a cascaded fuzzy reasoning Petri net
AU - Fang, C. Y.
AU - Hsueh, H. L.
AU - Chen, S. W.
PY - 2006
Y1 - 2006
N2 - 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.
AB - 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.
KW - Active driver assistance system
KW - Driving event analysis
KW - Fuzzy reasoning Petri net
UR - http://www.scopus.com/inward/record.url?scp=41849097070&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=41849097070&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:41849097070
SN - 1424400945
SN - 9781424400942
SP - 337
EP - 342
BT - Proceedings of ITSC 2006: 2006 IEEE Intelligent Transportation Systems Conference
ER -