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

delete2016-12-01
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OA
AI
C
Chung‐Cheng Lu
J
Jiangtao Liu
Y
Yunchao Qu
S
Srinivas Peeta
N
Nagui M. Rouphail
DOI:10.1016/j.trb.2016.09.015delete
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摘要

摘要

En 中文
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. (C) 2016 Elsevier Ltd. All rights reserved.
Keyword:
Green transportation
Vehicular emission modeling
Eco-routing
Marginal emission
Multi-scale dynamic network loading
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Transportation Research Part B-Methodological 封面图
Transportation Research Part B-Methodological
IF:
6.3
论文数:
3.6K
被引数:
1.9W

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A
Arizona State University
学者数:
2.7W
论文数: 2.5W
被引数: 4.2W
B
Beijing Jiaotong University
学者数:
2.2W
论文数: 1.7W
被引数: 1.2W
N
National Yang Ming Chiao Tung University
学者数:
2.5W
论文数: 2.3W
被引数: 2.2W
Purdue University System 封面图
Purdue University System
学者数:
4.0W
论文数: 3.6W
被引数: 66
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