The University of Toledo University Transportation Center : UTUTC-IU-17: Value Of ITS Information For Congestion Avoidance In Inter-Modal Transportation Systems, Phase III

Focus Area: Infrastructure Utilization

Principle Investigator:

Alper E. Murat, Ph.D.
Assistant Professor
Department of Industrial and Manufacturing Engineering
Wayne State University       
313.577.3872
amurat@wayne.edu

Project Dates: 08/15/2009 – 08/15/2010

Project Year: Year 4

UT-UTC Designation: UTUTC-IU-17

Abstract:

This research project continues to address a major issue contributing to the transportation network efficiency that directly affects supply chain efficiency. The issue is the effect of congestion at inter-modal terminal facilities and road network incidents on the delivery reliability within inter-modal freight transportation networks. Non-recurring events on road network, such as incidents, as well as inter-modal terminal incidents (accidents, repair, construction, equipment breakdown, labor strikes, etc.) and peak period congestions (e.g., due to seasonal loads) at the inter-modal terminals are the major sources of delay in inter-modal transportation systems. Traditional methods such as capacity expansion with infrastructure investments (network and inter-modal terminals) or buffering methods (e.g., inventory, headways, surplus fleet capacity) prove to be expensive coping mechanisms. Alternative to these expensive and temporary coping mechanisms, Intelligent Transportation Systems (ITS) can provide real-time inter-modal network status information to the users who can then respond to avoid and/or reduce the impact of transportation delays. In particular, we plan to evaluate the benefits to supply chain logistics from real-time information available through current and future ITS Systems to reduce congestion at both inter-modal freight terminals as well as road networks. More specifically, we will first compare the effectiveness of exact and heuristic optimization models and algorithms developed over the course of past two years. Next, we will implement these models and validate their effectiveness in improving inter-modal delivery reliability of selected carriers (e.g., C.H. Robinson) and JIT supply chains (Ford inbound and outbound logistics). Finally, we will perform a selective cost/benefit analysis of utilizing real-time information from ITS systems for some of our collaborators.