Abstract
This study aims to reveal the effect of pavement conditions on traffic accident risk through statistical analysis. The current pavement maintenance is planned based on the road surface survey that measures the physical damage on the pavement surface. The indicators for the physical damage on road surface are good representation for the structural healthiness and the driving comfort, but they do not always measure the traffic safety levels of the pavement. This limitation hinders planning the pavement management scheme ideal in achieving safer driving environment. This study empirically analyzes the relationships between the pavement conditions and accident risk. The pavement conditions are represented by three indicators: rutting depth, IRI and cracking ratio. The accident frequency is modelled based on the Poisson regression analysis. The model estimation results showed that rutting depth could have significant impact in increasing accident risk, particularly in rainy weather, whereas the IRI shows inverse effect. For cracking ratio, the results were not conclusive, but suggested potential influence on accident risk.
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