title: Modeling fault among motorcyclists involved in crashes.
abstract: Singapore crash statistics from 2001 to 2006 show that the motorcyclist fatality and injury rates per registered vehicle are higher than those of other motor vehicles by 13 and 7 times, respectively. The crash involvement rate of motorcyclists as victims of other road users is also about 43%. The objective of this study is to identify the factors that contribute to the fault of motorcyclists involved in crashes. This is done by using the binary logit model to differentiate between at-fault and not-at-fault cases and the analysis is further categorized by the location of the crashes, i.e., at intersections, on expressways and at non-intersections. A number of explanatory variables representing roadway characteristics, environmental factors, motorcycle descriptions, and rider demographics have been evaluated. Time trend effect shows that not-at-fault crash involvement of motorcyclists has increased with time. The likelihood of night time crashes has also increased for not-at-fault crashes at intersections and expressways. The presence of surveillance cameras is effective in reducing not-at-fault crashes at intersections. Wet-road surfaces increase at-fault crash involvement at non-intersections. At intersections, not-at-fault crash involvement is more likely on single-lane roads or on median lane of multi-lane roads, while on expressways at-fault crash involvement is more likely on the median lane. Roads with higher speed limit have higher at-fault crash involvement and this is also true on expressways. Motorcycles with pillion passengers or with higher engine capacity have higher likelihood of being at-fault in crashes on expressways. Motorcyclists are more likely to be at-fault in collisions involving pedestrians and this effect is higher at night. In multi-vehicle crashes, motorcyclists are more likely to be victims than at-fault. Young and older riders are more likely to be at-fault in crashes than middle-aged group of riders. The findings of this study will help to develop more targeted countermeasures to improve motorcycle safety and more cost-effective safety awareness program in motorcyclist training.
authors.affiliation: Traffic Lab, Department of Civil Engineering, National University of Singapore, Engineering Drive 2, EW1, 04-02B, Singapore 117576, Singapore. mmh@nus.edu.sg
authors.forename: Md Mazharul
authors.initials: MM
authors.lastname: Haque
authors.forename: Hoong Chor
authors.initials: HC
authors.lastname: Chin
authors.forename: Helai
authors.initials: H
authors.lastname: Huang
mesh_terms: D000063:Accidents, Traffic / Q000706:statistics & numerical data*; D000293:Adolescent; D000328:Adult; D000367:Age Factors; D005260:Female; D006801:Humans; D016015:Logistic Models; D008297:Male; D009049:Motorcycles / Q000706:statistics & numerical data*; D016017:Odds Ratio; D018570:Risk Assessment; D013997:Time Factors; D014505:Urban Population; D014887:Weather; D055815:Young Adult