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|Title:||Simulation evaluation of the benefits of real-time traffic information to trucks during incidents||Authors:||Ng, S.T.
|Keywords:||Diversion: Travel Time
|Issue Date:||Apr-2006||Citation:||Ng, S.T., Cheu, R.L., Lee, D.-H. (2006-04). Simulation evaluation of the benefits of real-time traffic information to trucks during incidents. Journal of Intelligent Transportation Systems: Technology, Planning, and Operations 10 (2) : 89-99. ScholarBank@NUS Repository. https://doi.org/10.1080/15472450600648566||Abstract:||This article evaluates the potential benefits of real-time traffic information for trucks delivering freight to destinations when an incident occurs en-route. The evaluation was carried out with a microscopic traffic simulation model in a network that consisted of a 26.5 km expressway and its parallel arterials. The diversion behaviors of trucks under the influence of the following sources of real-time traffic information were simulated: (1) variable message signs (VMS); (2) VMS and travel time displays (TTD); and (3) dynamic route guidance systems (DRGS). Other drivers also received and responded to limited real-time traffic information provided by VMS and TTD. A factorial experiment was designed to investigate the effect of five factors, which were the level of traffic information available to truck drivers, network traffic demand, incident locations, incident severity, and percentage of background traffic familiar with the network. It was found that, when an incident occurred during the period of high traffic demand, truck drivers benefited most from the real-time traffic information provided by DRGS, followed by the combination of VMS and TTD, and then only by the VMS with average travel time savings of 12%, 7%, and 5%, respectively, compared to average incident-free travel time. When an incident occurs during low and moderate levels of traffic demand, providing real-time traffic information helped to reduce average truck travel time, hut the average travel time was higher than that of incident-free situations. Results of analysis of variance also indicated that the five factors contributed significantly in affecting the average truck travel time. There were significant interactions between any two of the five factors with the exception of the level of traffic information and incident severity.||Source Title:||Journal of Intelligent Transportation Systems: Technology, Planning, and Operations||URI:||http://scholarbank.nus.edu.sg/handle/10635/66171||ISSN:||15472450||DOI:||10.1080/15472450600648566|
|Appears in Collections:||Staff Publications|
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