摘要: |
Tennessee has a substantial amount of truck shipments, but some of them are delayed due to unexpected incident-induced traffic congestion with large economic consequences. The purpose of this study is to focus on delay-inducing large-scale incidents and accidents, and mitigating the impacts of incident-related congestion on freight movements. The main strategies will focus on more effectively using statewide Advanced Traveler Information Systems (ATIS) to provide customized information facilitating truck diversions. More broadly, this project will focus on leveraging the opportunity provided by Intelligent Transportation Systems to effectively manage large-scale incidents. The objectives are to understand the current situation regarding large-scale incidents in Tennessee and collect information describing truck driver behaviors, correlating their behaviors with incident, roadway, and trip characteristics. Next, truck diversions will be modeled and consequent outcomes will be evaluated under various disruption scenarios. The project will develop ATIS strategies that can disseminate information customized to truck drivers, supporting their route diversion decisions. The study will also quantify benefits (reduced congestion costs and enhanced reliability) from appropriate truck diversion schemes. |