Quantifying benefits of traffic information provision under stochastic demand and capacity conditions: A multi-day traffic equilibrium approach

Mingxin Li, Xuesong Zhou, Nagui M. Rouphail

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Citations (Scopus)

Abstract

This paper aims to systematically evaluate benefits of traveler information provision strategies in a realistic environment with stochastic traffic demand, stochastic road capacity, and different degrees of traveler knowledge and traffic information provision quality. Based on a stochastic user equilibrium modeling framework, the proposed model uses a multi-day representation scheme to describe stochastic samples of uncertain demand and capacity supply, as well as day-dependent travel time. A gap-function based optimization model is further developed to find equilibrium solutions.

Original languageEnglish (US)
Title of host publicationIEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC
Pages2118-2123
Number of pages6
DOIs
StatePublished - 2011
Externally publishedYes
Event14th IEEE International Intelligent Transportation Systems Conference, ITSC 2011 - Washington, DC, United States
Duration: Oct 5 2011Oct 7 2011

Other

Other14th IEEE International Intelligent Transportation Systems Conference, ITSC 2011
CountryUnited States
CityWashington, DC
Period10/5/1110/7/11

Fingerprint

Travel time

Keywords

  • Stochastic demand
  • stochastic road capacity
  • stochastic user-equilibrium assignment
  • travel time variability

ASJC Scopus subject areas

  • Automotive Engineering
  • Mechanical Engineering
  • Computer Science Applications

Cite this

Li, M., Zhou, X., & Rouphail, N. M. (2011). Quantifying benefits of traffic information provision under stochastic demand and capacity conditions: A multi-day traffic equilibrium approach. In IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC (pp. 2118-2123). [6082843] https://doi.org/10.1109/ITSC.2011.6082843

Quantifying benefits of traffic information provision under stochastic demand and capacity conditions : A multi-day traffic equilibrium approach. / Li, Mingxin; Zhou, Xuesong; Rouphail, Nagui M.

IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC. 2011. p. 2118-2123 6082843.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Li, M, Zhou, X & Rouphail, NM 2011, Quantifying benefits of traffic information provision under stochastic demand and capacity conditions: A multi-day traffic equilibrium approach. in IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC., 6082843, pp. 2118-2123, 14th IEEE International Intelligent Transportation Systems Conference, ITSC 2011, Washington, DC, United States, 10/5/11. https://doi.org/10.1109/ITSC.2011.6082843
Li, Mingxin ; Zhou, Xuesong ; Rouphail, Nagui M. / Quantifying benefits of traffic information provision under stochastic demand and capacity conditions : A multi-day traffic equilibrium approach. IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC. 2011. pp. 2118-2123
@inproceedings{efb175a910644ae394463f611d7f1b26,
title = "Quantifying benefits of traffic information provision under stochastic demand and capacity conditions: A multi-day traffic equilibrium approach",
abstract = "This paper aims to systematically evaluate benefits of traveler information provision strategies in a realistic environment with stochastic traffic demand, stochastic road capacity, and different degrees of traveler knowledge and traffic information provision quality. Based on a stochastic user equilibrium modeling framework, the proposed model uses a multi-day representation scheme to describe stochastic samples of uncertain demand and capacity supply, as well as day-dependent travel time. A gap-function based optimization model is further developed to find equilibrium solutions.",
keywords = "Stochastic demand, stochastic road capacity, stochastic user-equilibrium assignment, travel time variability",
author = "Mingxin Li and Xuesong Zhou and Rouphail, {Nagui M.}",
year = "2011",
doi = "10.1109/ITSC.2011.6082843",
language = "English (US)",
isbn = "9781457721984",
pages = "2118--2123",
booktitle = "IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC",

}

TY - GEN

T1 - Quantifying benefits of traffic information provision under stochastic demand and capacity conditions

T2 - A multi-day traffic equilibrium approach

AU - Li, Mingxin

AU - Zhou, Xuesong

AU - Rouphail, Nagui M.

PY - 2011

Y1 - 2011

N2 - This paper aims to systematically evaluate benefits of traveler information provision strategies in a realistic environment with stochastic traffic demand, stochastic road capacity, and different degrees of traveler knowledge and traffic information provision quality. Based on a stochastic user equilibrium modeling framework, the proposed model uses a multi-day representation scheme to describe stochastic samples of uncertain demand and capacity supply, as well as day-dependent travel time. A gap-function based optimization model is further developed to find equilibrium solutions.

AB - This paper aims to systematically evaluate benefits of traveler information provision strategies in a realistic environment with stochastic traffic demand, stochastic road capacity, and different degrees of traveler knowledge and traffic information provision quality. Based on a stochastic user equilibrium modeling framework, the proposed model uses a multi-day representation scheme to describe stochastic samples of uncertain demand and capacity supply, as well as day-dependent travel time. A gap-function based optimization model is further developed to find equilibrium solutions.

KW - Stochastic demand

KW - stochastic road capacity

KW - stochastic user-equilibrium assignment

KW - travel time variability

UR - http://www.scopus.com/inward/record.url?scp=83755229188&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=83755229188&partnerID=8YFLogxK

U2 - 10.1109/ITSC.2011.6082843

DO - 10.1109/ITSC.2011.6082843

M3 - Conference contribution

AN - SCOPUS:83755229188

SN - 9781457721984

SP - 2118

EP - 2123

BT - IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC

ER -