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Traffic Accident Prediction Model Implementation in Traffic Safety Management
Linköping University, Department of Science and Technology, Communications and Transport Systems.
2009 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

As one of the highest fatalities causes, traffic accidents and collisions always requires a large amounteffort to be reduced or prevented from occur. Traffic safety management routines therefore always needefficient and effective implementation due to the variations of traffic, especially from trafficengineering point of view apart from driver education.Traffic Accident Prediction Model, considered as one of the handy tool of traffic safety management,has become of well followed with interested. Although it is believed that traffic accidents are mostlycaused by human factors, these accident prediction models would help from traffic engineering point ofview to enlarge the traffic safety level of road segments. This thesis is aiming for providing a guidelineof the accident prediction model implementation in traffic safety management, regarding to trafficengineering field. Discussion about how this prediction models should merge into the existing routinesand how well these models would perform would be given. As well, cost benefit analysis of theimplementation would be at the end of this thesis. Meanwhile, a practical field study would bepresented in order to show the procedures of the implementation of traffic accident prediction model.The field study is about this commercial model set SafeNET, from TRL Limited UK, implemented inRoad Safety Audit procedures combined with microscopic simulation tool. Detailed processing andinput and output data will be given accompany with the countermeasures for accident frequencyreduction finalization.

Place, publisher, year, edition, pages
2009. , 55 p.
Keyword [en]
Traffic Engineering, Traffic Accident Management, Accident Prediction Models, Implementation Models, SafeNET
National Category
Engineering and Technology
URN: urn:nbn:se:liu:diva-52203ISRN: LiU-ITN-TEK-A--09/053--SEOAI: diva2:280307
2009-10-22, TP32, Bredgatan 33, Täppan, 10:15 (English)
Available from: 2009-12-15 Created: 2009-12-09 Last updated: 2009-12-15Bibliographically approved

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