A validated multi-agent simulation test bed to evaluate congestion pricing policies on population segments by time-of-day in New York City
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DOI: 10.1016/j.tranpol.2020.12.011
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Cited by:
- Pablo González-Aliste & Iván Derpich & Mario López, 2023. "Reducing Urban Traffic Congestion via Charging Price," Sustainability, MDPI, vol. 15(3), pages 1-21, January.
- Geng, Kexin & Wang, Yacan & Cherchi, Elisabetta & Guarda, Pablo, 2023. "Commuter departure time choice behavior under congestion charge: Analysis based on cumulative prospect theory," Transportation Research Part A: Policy and Practice, Elsevier, vol. 168(C).
- Tan, Yu & Sun, Zhanbo & Zhu, Baichuan & Qin, Ziye & Zhao, Yu & Wang, Xuting, 2024. "Minimize population exposure to vehicle-generated emissions by road pricing," Transport Policy, Elsevier, vol. 148(C), pages 15-30.
- Wang, Ding & Tayarani, Mohammad & Yueshuai He, Brian & Gao, Jingqin & Chow, Joseph Y.J. & Oliver Gao, H. & Ozbay, Kaan, 2021. "Mobility in post-pandemic economic reopening under social distancing guidelines: Congestion, emissions, and contact exposure in public transit," Transportation Research Part A: Policy and Practice, Elsevier, vol. 153(C), pages 151-170.
- Jiang, Qinhua & Zhang, Ning & Yueshuai He, Brian & Lee, Changju & Ma, Jiaqi, 2024. "Large-scale public charging demand prediction with a scenario- and activity-based approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 179(C).
- Peiyu Jing & Ravi Seshadri & Takanori Sakai & Ali Shamshiripour & Andre Romano Alho & Antonios Lentzakis & Moshe E. Ben-Akiva, 2023. "Evaluating congestion pricing schemes using agent-based passenger and freight microsimulation," Papers 2305.07318, arXiv.org.
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Keywords
Travel demand forecasting; Emerging mobility; Multi-agent simulation; Congestion pricing; New York city;All these keywords.
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