Routing strategy including time and carbon dioxide emissions

Routing strategy including time and carbon dioxide emissions: effects on network performance

Zhang, Fan
Chen, Y. (TU Delft Transport and Planning)
Goni Ros, B. (TU Delft Transport and Planning)
GAO, Jian
Knoop, V.L. (TU Delft Transport and Planning)

2016-01-12

Traffic congestion leads to delays and increased carbon dioxide (CO2) emissions. Traffic management measures such as providing information on environmental route costs have been proposed to mitigate congestion. Multi-criteria routing dynamic traffic assignment (MCR-DTA) models are needed to evaluate the effectiveness of such measures. This paper presents a simulation-based bi-level optimization method to solve the MCR-DTA problem, which works as follows. Route costs include travel times and emissions, but those are updated inside two different loops. In the inner loop, emission costs are considered fixed; the assignment is performed by updating route travel times, using a traditional DTA tool. Then, in the outer loop, emissions are calculated based on link loads and fed back to the DTA tool, which performs a new assignment. The MCR user equilibrium is found when emissions or predefined generalized costs converge to an equilibrium. The bi-level method is first tested on a small network, showing that the proposed method is able to effectively solve the MCR-DTA problem. Next, the method is applied to a medium-size urban network. The results show that if drivers choose routes based on emissions besides travel time, the average travel time and emissions per vehicle decrease. This occurs because congested links have a higher impact on route costs; hence the equilibrium is pushed away from the single-criteria routing (SCR) user optimum towards the SCR system optimum. Results support the conclusion that informing drivers about CO2 emissions per route can potentially lead to decreased delay and emissions in real networks.

carbon dioxide
Dynamic traffic assignment
Methodology
Network analysis (Planning)
Optimization
Traffic congestion

http://resolver.tudelft.nl/uuid:dc326e56-3146-49a9-ba0b-a474326acdec

Proceedings of the 95th Annual Meeting of the Transportation Research Board: Washington, United States

Transportation Research Board 95th annual meeting, 2016-01-10 → 2016-01-14, Washington, United States

Institutional Repository

conference paper

© 2016 Fan Zhang, Y. Chen, B. Goni Ros, Jian GAO, V.L. Knoop