Joint Optimization of Road Classification and Road Capacity for Urban Freight Transportation Networks
Publication: Journal of Transportation Engineering, Part A: Systems
Volume 146, Issue 10
Abstract
In previous studies, almost all urban network design models/methods made attempts to optimize transportation system performance, such as minimizing road traffic congestion, by determining optimal road capacity expansion schemes, with the assumption of indestructible road infrastructure. However, road infrastructure definitely deteriorates over time, and needs periodic maintenance and repairs. This paper proposes a bilevel programming model for the urban freight transportation network design problem (UFTNDP) by taking into account the heterogeneity of road classifications and road damages from the perspective of road maintenance. The model aims to improve network performance as much as possible by determining an optimal joint scheme of road capacities and classifications. At the upper level, road planning aims to minimize total system cost by determining a joint optimal scheme of road capacities and road classifications. The lower level is a traffic assignment problem that characterizes network users’ path choice behavior. We then propose an improved system optimum (SO) relaxation–based method to solve the optimization model. Numerical examples validated the developed model and tested the computational efficiency of the proposed algorithm. Numerical results revealed that (1) the improved solution algorithm performs better, because it saves 97.3% of computational time compared with the original SO relaxation–based method; (2) the algorithm has the potential to be extended to solving a general discrete network design problem; and (3) a simultaneous optimization of road classification and capacity works better in improving system performance of an urban freight transportation network.
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Data Availability Statement
Some or all data, models, or code generated or used during the study are available from the corresponding author by request, including the traffic network, origin-destination (OD) demand table, link travel time, link volume, and road damage parameters.
Acknowledgments
This study has been substantially supported by the National Natural Science Foundation Council of China through projects (Grant Nos. 71601142, 71531011, and 71890970/71890973), and a project sponsored by the program of Shanghai Academic Research Leader.
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Published In
Journal of Transportation Engineering, Part A: Systems
Volume 146 • Issue 10 • October 2020
Copyright
© 2020 American Society of Civil Engineers.
History
Received: Apr 3, 2020
Accepted: Jun 8, 2020
Published online: Aug 14, 2020
Published in print: Oct 1, 2020
Discussion open until: Jan 14, 2021
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