Evaluation of data‐driven performance measures for comparing and ranking traffic bottlenecks

Author:

Hale David1,Chrysikopoulos Georgios2,Kondyli Alexandra2,Ghiasi Amir1

Affiliation:

1. Leidos Inc. Reston Virginia USA

2. Civil, Environmental, and Architectural Engineering University of Kansas Lawrence Kansas USA

Publisher

Institution of Engineering and Technology (IET)

Subject

Law,Mechanical Engineering,General Environmental Science,Transportation

Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A Data-Driven and Human-Centric EV Charging Recommendation System at City-Scale;Proceedings of the 14th ACM International Conference on Future Energy Systems;2023-06-16

2. Modelling Bottlenecks of Bike-Sharing Travel Using the Distinction between Endogenous and Exogenous Demand: A Case Study in Beijing;ISPRS International Journal of Geo-Information;2022-11-08

3. Estimating key traffic state parameters through parsimonious spatial queue models;Transportation Research Part C: Emerging Technologies;2022-04

4. An s-shaped three-parameter (S3) traffic stream model with consistent car following relationship;Transportation Research Part B: Methodological;2021-11

5. Evaluation of data‐driven performance measures for comparing and ranking traffic bottlenecks;IET Intelligent Transport Systems;2021-02-23

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