作者: Jwan Kamla , Tony Parry , Andrew Dawson
DOI: 10.1016/J.AAP.2018.04.031
关键词:
摘要: In order to reduce accident risk, highway authorities prioritise maintenance budgets partly based upon previous history. However, as rates have continued fall, this approach has become problematic ‘black spots’ been treated and the number of accidents at any individual site fallen, making history a less reliable indicator future risk. Another way identifying sites higher risk might be identify near-miss (where an nearly happened but was avoided). The principal aim paper is analyze potentially unsafe truck driving conditions from counts Harsh Braking Incidents (HBIs) roundabouts compare results similar, studies numbers same sites, explore if HBIs can studied surrogate for accidents. This achieved by processing telematics data with geo-referenced incidents harsh braking. Models are then developed characterise relationships between geometric traffic variables. These likely occur more often than may, therefore, useful in high Based on study, it concluded that influenced variables similar accidents; therefore they may considering roundabouts. They source volumes accidents, which important changes or trends over time. showed random-parameters count models provide better goodness fit compared fixed-parameters were found significant, giving prediction events.