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Simulation-based evaluation of traffic safety performance using surrogate safety measures
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Yang, Hong. Simulation-based evaluation of traffic safety performance using surrogate safety measures. Retrieved from https://doi.org/doi:10.7282/T3FX78GP

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TitleSimulation-based evaluation of traffic safety performance using surrogate safety measures
NameYang, Hong (author); Ozbay, Kaan (chair); Nassif, Hani (internal member); Gonzales, Eric (internal member); Bartin, Bekir (internal member); Ozmen-Ertekin, Dilruba (outside member); Rutgers University; Graduate School - New Brunswick
Date Created2012
Other Date2012-01 (degree)
SubjectCivil and Environmental Engineering, Traffic safety--Evaluation
Extentxvii, 156 p. : ill.
DescriptionTraffic safety evaluation is one of the most important processes in the analysis of transportation systems performance. The use of traditional crash-data-oriented methodologies to analyze traffic safety problems has been frequently questioned due to shortcomings such as unavailability and low quality of historical crash data. The advancement of traffic conflict techniques and micro-simulation tools motivated this dissertation to develop a simulation-based approach of combining micro-simulation models and traffic conflict technique to investigate the safety issues in traffic systems. The proposed simulation-based approach consists of two major components: the development of surrogate safety measures; and the integration of the developed surrogate safety measures with micro-simulation models. In this dissertation, a new surrogate safety measure is derived and applied in micro-simulation models to capture the conflict risk of the interactions among vehicles. The conceptual and computational logics of the proposed surrogate safety indicator are described in detail. A calibration procedure that focuses on safety evaluation using the simulation model with the new surrogate measure has been proposed. The proposed calibration approach has been developed based on the stochastic gradient approximation algorithms to find optimal parameters of the stochastic traffic simulation models. The calibration methodology has been implemented on a selected traffic simulation platform to test its performance. Simulated operational measurements and traffic conflict risk in terms of the surrogate safety measure are quantified and compared with observations derived from high resolution vehicle trajectory data. The calibrated traffic model has also been validated by using independent vehicle trajectory data saved as a hold-out sample. The results show that the fine-tuning of parameters using the proposed calibration approach can significantly improve the performance of the simulation model to describe actual traffic conflict risk as well as operational performance. The applicability of the proposed new surrogate measure and the simulation-based safety evaluation approach using this surrogate measure has been successfully demonstrated through several cases studies. The overall findings can inform road safety investigators as to how operations-oriented simulation models in conjunction with the surrogate safety measure can complement traffic safety evaluation in cases to which traditional approaches are not applicable.
NotePh.D.
NoteIncludes bibliographical references
NoteIncludes vita
Noteby Hong Yang
Genretheses, ETD doctoral
Persistent URLhttps://doi.org/doi:10.7282/T3FX78GP
Languageeng
CollectionGraduate School - New Brunswick Electronic Theses and Dissertations
Organization NameRutgers, The State University of New Jersey
RightsThe author owns the copyright to this work.
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