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Factors affecting the severity of road accidents in Sri Lanka : a logistic regression approach

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dc.contributor.advisor Cooray, TMJA
dc.contributor.author Seneviratna, NAMR
dc.date.accessioned 2019-08-02T09:05:49Z
dc.date.available 2019-08-02T09:05:49Z
dc.identifier.uri http://dl.lib.mrt.ac.lk/handle/123/14644
dc.description.abstract Road accidents have become a leading cause of death and injury as well as property damage worldwide. Ever increasing road accidents and traffic flow is a heavy burden to a developing country like Sri Lanka. In year 2016, 38915 accidents were reported where 7% of them are fatal contributing to 2824 deaths. Therefore, it is urgently needed to find solutions and reduce road accident deaths and injuries. The objective of this study is to identify the significant factors affecting for motorcycle and motor vehicle accidents in Sri Lanka. Secondary data used in this study between the period 2014 to 2016 were acquired from the police traffic headquarters, Colombo in Sri Lanka. A total number of 111457 road accidents where drivers at fault were included in the analysis. Among them 78531were motor vehicle accidents and 32926 were motor cycle accidents. Motorcycle accidents are analyzed separately due to high accident rate of motorcycles. Factors considered in the study were vehicle type, gender of driver, validity of license, accident cause, alcohol test, time of accident, weekday/weekend, road surface, weather condition, light condition, location and age of driver. Results revealed that male drivers (98%) have greater tendency to be involved in motorcycle and motor vehicle accidents rather than female drivers (2%). High number of motorcycle (75%) and motor vehicle (73%) accidents reported due to aggressive /negligent driving. Highest number of motor vehicle accidents (20.5%) reported by the drivers in between 29 - 34 years old. Highest number of motorcycle accidents (28.5%) reported by the drivers in between 19-24 years old. Majority of the accidents were occurred, while the vehicle was moving on a straight road. Among drivers and motorcyclists (7%) were found to have consumed alcohol. Most of motorcycle and motor vehicle accidents occurred in daytime under daylight on weekdays. Binary logistic regression is applied motorcycle and motor vehicles accidents separately to evaluate the odds of grievous accidents compared to non-grievous accidents. For motor vehicle accidents vehicle type, validity of license, time, location, alcohol test, accident cause, age of driver and gender have a significant effect on the severity of accidents. Bend or junction location, aggressive/negligent driving, drive by male drivers, drive at daytime, driving light vehicle and drivers who use alcohol below legal limit or no alcohol, have a high chance to be a grievous accident. Moreover, the older drivers have less accident risk. For motorcycle accidents, location type, time, age of driver, accident cause and gender have a significant effect on the severity of accidents. Among them, location type, accident cause and gender have an increasing effect on the probability of a grievous accident. Time and age of driver have a decreasing effect on the probability of a grievous accident. Straight road, aggressive/negligent driving, drive by male motorcyclists, daytime have a high chance to be a grievous accident. Moreover, the older motorcyclists have less accident risk. These findings can aid modifying regulations and laws and establishing preventive and protective approaches and strategies. en_US
dc.language.iso en en_US
dc.subject Road accidents en_US
dc.subject Logistic Regression en_US
dc.subject Accident severity en_US
dc.subject Motorcycle accidents en_US
dc.subject Motor vehicle accidents en_US
dc.title Factors affecting the severity of road accidents in Sri Lanka : a logistic regression approach en_US
dc.type Thesis-Abstract en_US
dc.identifier.faculty Engineering en_US
dc.identifier.degree M.Sc in Operational Research en_US
dc.identifier.department Department of Mathematics en_US
dc.date.accept 2018
dc.identifier.accno TH3724 en_US


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