• Journal of Korean Society of Transportation
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• v.32 no.6
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• pp.662-674
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• 2014

In this study, accident frequency prediction models were constructed by collecting variables such as geometric structures, safety facilities, traffic volume and weather conditions, land use, highway design-satisfaction criteria along 780km (4,372 sections) of 4 lane-highways over 8 areas. As for models, a fixed parameter model and a random parameter model were employed. In the random parameter model, some influences were reversed as the range was expressed based on specific probability in the case of no fixed coefficients. In the fixed parameter model, the influences of independent variables on accident frequency were interpreted by using one coefficient, but in the random parameter model, more various interpretations were took place. In particular, curve radius, securement of shoulder lane, vertical grade design criteria satisfaction showed both positive and negative influence, according to specific probability. This means that there could be a reverse effect depending on the behavioral characteristics of drivers and the characteristics of highway sections. Rather, they influence the increase of accident frequency through the all sections.

• Journal of Korean Society of Transportation
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• v.30 no.2
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• pp.43-52
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• 2012

A lane departure warning system (LDWS) is an effective technology-based countermeasure for preventing traffic crashes as it provides warning information to drivers. Understanding the characteristics of perception and satisfaction levels on LDWS is fundamental for deriving better performance and functionality enhancements of the system. The purpose of this study is to evaluate the user satisfaction of LDWS. A survey to collect user perception and user preference data was conducted. Both cross-tabulation analysis and binary logistic regression technique were adopted to identify the factors affecting user satisfaction for LDWS. The results revealed that the accuracy and timeliness of warning information was significant for evaluating the effectiveness of LDWS. In particular, the warning accuracy at a curve segment on the road was the most dominant factor affecting user satisfaction. The outcome of this study would be valuable in evaluating and designing LDWS functionalities.