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Congestion pricing policies: Design and assessment for the city of Rome, Italy

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  • Cipriani, Ernesto
  • Mannini, Livia
  • Montemarani, Barbara
  • Nigro, Marialisa
  • Petrelli, Marco

Abstract

Congestion pricing is classified as a transportation demand management measure adopted to reduce impacts modern cities are suffering in terms of traffic congestion, road accidents and air and noise pollution. Such a measure allows linking road transport externalities directly to travelers producing them. The definition of proper tolling schemes enables this measure to act on demand short-term choices, forcing travellers to shift towards low impact road itineries (route diversion) and sustainable transport systems (modal diversion).

Suggested Citation

  • Cipriani, Ernesto & Mannini, Livia & Montemarani, Barbara & Nigro, Marialisa & Petrelli, Marco, 2019. "Congestion pricing policies: Design and assessment for the city of Rome, Italy," Transport Policy, Elsevier, vol. 80(C), pages 127-135.
    • Handle: RePEc:eee:trapol:v:80:y:2019:i:c:p:127-135
    DOI: 10.1016/j.tranpol.2018.10.004
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    4. Chen, Fangxi & Yin, Zhiwei & Ye, Yingwei & Sun, Daniel(Jian), 2020. "Taxi hailing choice behavior and economic benefit analysis of emission reduction based on multi-mode travel big data," Transport Policy, Elsevier, vol. 97(C), pages 73-84.
    5. Nihat Can Karabulut & Murat Ozen & Oruc Altintasi, 2024. "Understanding the Determinants of Lane Inefficiency at Fully Actuated Intersections: An Empirical Analysis," Sustainability, MDPI, vol. 16(2), pages 1-17, January.
    6. Feng, Tong & Sun, Yuechi & Shi, Yating & Ma, Jie & Feng, Chunmei & Chen, Zhenni, 2024. "Air pollution control policies and impacts: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 191(C).
    7. Sen, Suman & Charles, Michael B. & Harrison, Jennifer L., 2022. "Usage-based road pricing and potential equity issues: A study of commuters in South East Queensland, Australia," Transport Policy, Elsevier, vol. 118(C), pages 33-43.
    8. Wang Yu & Zhang Dongbo & Zhang Yu, 2022. "GPS data Mining at Signalized Intersections for Congestion Charging," Computational Economics, Springer;Society for Computational Economics, vol. 59(4), pages 1713-1734, April.
    9. 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).
    10. Chapala, Sai Bharath Kumar & Nair, Preetha & Sreekumar, M. & Bhavathrathan, B.K., 2024. "A dynamic traffic assignment framework for policy analysis in cities with significant share of two-wheelers," Transport Policy, Elsevier, vol. 147(C), pages 125-139.
    11. 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.
    12. Adnan, Muhammad & Nahmias Biran, Bat-hen & Baburajan, Vishnu & Basak, Kakali & Ben-Akiva, Moshe, 2020. "Examining impacts of time-based pricing strategies in public transportation: A study of Singapore," Transportation Research Part A: Policy and Practice, Elsevier, vol. 140(C), pages 127-141.
    13. Oum, Tae Hoon & Wang, Kun, 2020. "Socially optimal lockdown and travel restrictions for fighting communicable virus including COVID-19," Transport Policy, Elsevier, vol. 96(C), pages 94-100.
    14. Ortúzar, Juan de Dios & Bascuñán, Raúl & Rizzi, Luis Ignacio & Salata, Andrés, 2021. "Assessing the potential acceptability of road pricing in Santiago," Transportation Research Part A: Policy and Practice, Elsevier, vol. 144(C), pages 153-169.
    15. Fowri, Hamid R. & Seyedabrishami, Seyedehsan, 2020. "Assessment of urban transportation pricing policies with incorporation of unobserved heterogeneity," Transport Policy, Elsevier, vol. 99(C), pages 12-19.

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