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Erschienen in:
2018 | OriginalPaper | Buchkapitel
A Crash Counts by Severity Based Hotspot Identification Method and Its Application on a Regional Map Based Analytical Platform
verfasst von : Xinxin Xu, Ziqiang Zeng, Yinhai Wang, John Ash
Erschienen in: Proceedings of the Eleventh International Conference on Management Science and Engineering Management
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Abstract
This paper aims to develop a crash counts by severity based hotspot identification method by extending the traditional empirical Bayes method to a generalized nonlinear model-based mixed multinomial logit approach. A new safety performance index and a new potential safety improvement index are developed by introducing the risk weight factor and compared with traditional indexes by employing four hotspot identification evaluating methods. The comparison results reveal that the new safety performance index derived by the generalized nonlinear model-based mixed multinomial logit approach is the most consistent and reliable method for identifying hotspots. Finally, a regional map based analytical platform is developed by expanding the safety performance module with the new safety performance index and potential safety improvement functions.