Eco-system optimal time-dependent flow assignment in a congested network

Chung Cheng Lu, Jiangtao Liu, Yunchao Qu, Srinivas Peeta, Nagui M. Rouphail, Xuesong Zhou

Research output: Contribution to journalArticle

23 Scopus citations

Abstract

This research addresses the eco-system optimal dynamic traffic assignment (ESODTA) problem which aims to find system optimal eco-routing or green routing flows that minimize total vehicular emission in a congested network. We propose a generic agent-based ESODTA model and a simplified queueing model (SQM) that is able to clearly distinguish vehicles’ speed in free-flow and congested conditions for multi-scale emission analysis, and facilitates analyzing the relationship between link emission and delay. Based on the SQM, an expanded space-time network is constructed to formulate the ESODTA with constant bottleneck discharge capacities. The resulting integer linear model of the ESODTA is solved by a Lagrangian relaxation-based algorithm. For the simulation-based ESODTA, we present the column-generation-based heuristic, which requires link and path marginal emissions in the embedded time-dependent least-cost path algorithm and the gradient-projection-based descent direction method. We derive a formula of marginal emission which encompasses the marginal travel time as a special case, and develop an algorithm for evaluating path marginal emissions in a congested network. Numerical experiments are conducted to demonstrate that the proposed algorithm is able to effectively obtain coordinated route flows that minimize the system-wide vehicular emission for large-scale networks.

Original languageEnglish (US)
Pages (from-to)217-239
Number of pages23
JournalTransportation Research Part B: Methodological
Volume94
DOIs
StatePublished - Dec 1 2016

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Keywords

  • Eco-routing
  • Green transportation
  • Marginal emission
  • Multi-scale dynamic network loading
  • Vehicular emission modeling

ASJC Scopus subject areas

  • Transportation
  • Management Science and Operations Research

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