Congestion is a common phenomenon in all medium to large cities of the world, and Portland is no exception. For example, the City of Portland Office of Transportation indicates that the growth in truck movement and traffic congestion is rapidly increasing on Portland’s street system. Freight traffic may grow even faster than passenger traffic. Between 2000 and 2020 the number of medium and heavy truck trips is expected to nearly double (COPOT, 2005). From the operational point of view, congestion creates a substantial variation in travel times during peak morning and evening hours. This is problematic for all vehicle routing models which rely on a constant value to represent vehicle speeds. And while the ubiquitous availability of real time traffic information allows drivers to reactively alter routes and customer service sequences to better cope with congestion, static routing models are unable to take advantage of these advances in real-time information provision in order to... View Full Summary

Hide Full Summary
Congestion is a common phenomenon in all medium to large cities of the world, and Portland is no exception. For example, the City of Portland Office of Transportation indicates that the growth in truck movement and traffic congestion is rapidly increasing on Portland’s street system. Freight traffic may grow even faster than passenger traffic. Between 2000 and 2020 the number of medium and heavy truck trips is expected to nearly double (COPOT, 2005). From the operational point of view, congestion creates a substantial variation in travel times during peak morning and evening hours. This is problematic for all vehicle routing models which rely on a constant value to represent vehicle speeds. And while the ubiquitous availability of real time traffic information allows drivers to reactively alter routes and customer service sequences to better cope with congestion, static routing models are unable to take advantage of these advances in real-time information provision in order to proactively find adequate routing solutions. In addition, changes in travel time caused by congestion cannot be accurately represented in static models. Research in time-dependent vehicle routing problem is comparatively meager and current solution methods are inadequate for practical carrier operations which need to provide fast solutions for medium to large instances. Even faster solution methods are essential to take advantage of real time information. The major aim of this proposal is to develop and evaluate new methods for vehicle routing in congested urban areas. The emphasis will be placed on improving the running time of the existing methods using tailored data structures, the efficient handling of local and global variables, hybrid approaches, and parallel computing.

Portland State University Department of Civil and Environmental Engineering

Project Type: Research
Start Date: October 1, 2007
End Date: August 31, 2009
Related Projects: None
Research Area: Advanced Technology