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Application of the Bayesian Model Averaging in Analyzing Freeway Traffic Incident Clearance Time for Emergency Management by Yajie Zou; Bo Lin; Xiaoxue Yang; Lingtao Wu; Malik Muneeb Abid; Jinjun Tang is a Engineering article available to read on EtoBox.

What is Application of the Bayesian Model Averaging in Analyzing Freeway Traffic Incident Clearance Time for Emergency Management about?

Identifying the influential factors in incident duration is important for traffic management agency to mitigate the impact of traffic incidents on freeway operation. Previous studies have proposed a variety of approaches to determine the significant factors for traffic incident clearance time. These methods commonly select a single “true” model among a majority of alternative models based on some model selection criteria. However, the conventional methods generally neglect the uncertainty related to the choice of models. This paper proposes a Bayesian Model Averaging (BMA) model to account for model uncertainty by averaging all plausible models using posterior probability as the weight. The BMA model is used to analyze the 2,584 freeway incident records obtained from I-5 corridor in Seattle, WA, USA. The results show that the BMA approach has the capability of interpreting the causal relationship between explanatory variables and clearance time. In addition, the BMA approach can provide better prediction performance than the Cox proportional hazards model and the accelerated failure time models. Overall, the findings in this study can be useful for traffic emergency management agen

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Author

Yajie Zou; Bo Lin; Xiaoxue Yang; Lingtao Wu; Malik Muneeb Abid; Jinjun Tang

Publisher

Hindawi Limited

Published

2021

Language

EN

Field

Engineering (Physical Sciences)