Accident prediction model for highw ays with rest area by using poisson and binomial regression model

dc.contributor.authorTipakornkiat, Chalat
dc.date.accessioned2018-09-13T19:47:34Z
dc.date.available2018-09-13T19:47:34Z
dc.description.abstractCurrently, rest area positively impacts on road users in terms of business points and information providers; however, the important task of rest area is reducing the number of road accident cause of fatigue. In the past, truck drivers in Thailand usually parked their vehicles on roadside or shoulder, which these harmful areas could generate road accidents when parked vehicles move out from the road shoulder to the travelled way. In Thailand, road accident situation is top 10 of the world. Research objectives consist of the determination of influencing factors that affect the road accident within upstream and downstream 16 km of rest areas in Thailand and built the accident prediction models. It was found out that main variables such as serviceability of rest areas and the number of the truck users in rest areas are significantly impacted into the accident prediction model. In summary, rest area could help to reduce the number of road accidents.en_US
dc.identifier.conference9th Asia Pacific Conference on Transportation & the Environmenten_US
dc.identifier.departmentDepartment of Civil Engineeringen_US
dc.identifier.doihttps://doi.org/10.31705/APTE.2014.21en_US
dc.identifier.facultyEngineeringen_US
dc.identifier.pgnos234-242en_US
dc.identifier.placeMount Laviniaen_US
dc.identifier.proceedingProceedings of the Asia Pacific Conference on Transportation & the Environmenten_US
dc.identifier.urihttp://dl.lib.mrt.ac.lk/handle/123/13546
dc.identifier.year2014en_US
dc.language.isoenen_US
dc.subjectRest Areaen_US
dc.subjectAccident Prediction Modelen_US
dc.subjectTrucken_US
dc.subjectHeavy Vehicleen_US
dc.titleAccident prediction model for highw ays with rest area by using poisson and binomial regression modelen_US
dc.typeConference-Full-texten_US

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