Development and evaluation of an effective sequential approach for dynamic accident duration forecasting

Ying Lee, Chien Hung Wei

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

This study creates a sequential approach to represent the dynamic update forecast of accident duration. This procedure includes two Artificial Neural Network-based models. Model A is used to forecast the duration time at the instant of accident notification while Model B provides multi-period updates of duration time after the moment of accident notification. These two models together provide a sequential forecast of accident duration from the accident notification to the accident site clearance. With these two models, the estimated duration time can be provided by plugging in relevant traffic data as soon as an incident is reported. This study shows very promising practical applicability of the proposed models in the Intelligent Transportation Systems context.

Original languageEnglish
Title of host publicationRoad Traffic
Subtitle of host publicationSafety, Modeling and Impacts
PublisherNova Science Publishers, Inc.
Pages347-365
Number of pages19
ISBN (Electronic)9781616680039
ISBN (Print)9781604568844
Publication statusPublished - 2009 Jan 1

All Science Journal Classification (ASJC) codes

  • Engineering(all)

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  • Cite this

    Lee, Y., & Wei, C. H. (2009). Development and evaluation of an effective sequential approach for dynamic accident duration forecasting. In Road Traffic: Safety, Modeling and Impacts (pp. 347-365). Nova Science Publishers, Inc..