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 1 |
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All Science Journal Classification (ASJC) codes
- Automotive Engineering
- Mechanical Engineering
- Computer Science Applications
Cite this
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Optimal vehicle routing with real-time traffic information. / Kim, Seongmoon; Lewis, Mark E.; White, Chelsea C.
In: IEEE Transactions on Intelligent Transportation Systems, Vol. 6, No. 2, 01.06.2005, p. 178-188.Research output: Contribution to journal › Article
TY - JOUR
T1 - Optimal vehicle routing with real-time traffic information
AU - Kim, Seongmoon
AU - Lewis, Mark E.
AU - White, Chelsea C.
PY - 2005/6/1
Y1 - 2005/6/1
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=21644453002&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=21644453002&partnerID=8YFLogxK
U2 - 10.1109/TITS.2005.848362
DO - 10.1109/TITS.2005.848362
M3 - Article
AN - SCOPUS:21644453002
VL - 6
SP - 178
EP - 188
JO - IEEE Transactions on Intelligent Transportation Systems
JF - IEEE Transactions on Intelligent Transportation Systems
SN - 1524-9050
IS - 2
ER -