Abstract
This paper examines the value of real-time traffic information to optimal vehicle routing in a nonstationary stochastic network. We present a systematic approach to aid in the implementation of transportation systems integrated with real-time information technology. We develop decision-making procedures for determining the optimal driver attendance time, optimal departure times, and optimal routing policies under time-varying traffic flows based on a Markov decision process formulation. With a numerical study carried out on an urban road network in Southeast Michigan, we demonstrate significant advantages when using this information in terms of total cost savings and vehicle usage reduction while satisfying or improving service levels for just-in-time delivery.
| Original language | English |
|---|---|
| Pages (from-to) | 178-188 |
| Number of pages | 11 |
| Journal | IEEE Transactions on Intelligent Transportation Systems |
| Volume | 6 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - 2005 Jun |
Bibliographical note
Funding Information:Manuscript received February 18, 2003; revised July 29, 2004 and September 22, 2004. This work was supported by the Michigan Department of Transportation and the Alfred P. Sloan Foundation through the University of Michigan Trucking Industry Program. The Associate Editor for this paper was W. Scherer.
All Science Journal Classification (ASJC) codes
- Automotive Engineering
- Mechanical Engineering
- Computer Science Applications
