Sunsetting skim matrices: A trajectory-mining approach to derive travel time skim matrix in dynamic traffic assignment for activity-base model integration

Authors

DOI:

https://doi.org/10.5198/jtlu.2020.1551

Keywords:

Skim matrix, Vehicle trajectories, Dynamic traffic assignment, Activity-based models, Integrated models

Abstract

The travel impedance skim matrix is one of the most essential intermediate products within transportation forecasting models and is a fundamental input for activity-based transportation forecasting models. It reflects interzonal travel time, travel time reliability, travel costs, etc. by time of day. The traditional method to obtain skim matrices is to execute multiple times of time-dependent, shortest-path calculations. However, the computational and memory use burden can easily increase to an intractable level when dealing with mega-scale networks, such as those with thousands of traffic-analysis zones. This research proposes two new approaches to extract the interzonal travel impedance information from the already existing vehicle trajectory data. Vehicle trajectories store travel impedance information in a more compact format when compared to time-dependent link performance profiles. The numerical experiments highlight huge potential advantages of the proposed approaches in terms of saving both memory and CPU time.

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Published

2020-11-12

How to Cite

Tian, Y., Chiu, Y.-C., Sun, J., & Chai, C. (2020). Sunsetting skim matrices: A trajectory-mining approach to derive travel time skim matrix in dynamic traffic assignment for activity-base model integration. Journal of Transport and Land Use, 13(1), 413-428. https://doi.org/10.5198/jtlu.2020.1551

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Section

Special Issue: Innovations for Transport Planning in China