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Evaluating the role of land use and transport policies in reducing the transport energy dependence of a city

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  • Ignaccolo, Matteo
  • Inturri, Giuseppe
  • Le Pira, Michela
  • Caprì, Salvatore
  • Mancuso, Valentina

Abstract

In this paper a land use and transport model is presented to calculate an indicator of “Transport Energy Dependence” (TED) in order to support the delivery of sustainable urban and transport plans. The model is based on a mathematical description of the transport system, where transport mode choice follows ideal simple rules based on distance from origin to destination and transit network accessibility. For each transport mode unit energy consumption, capacity and load factor are considered. Flows of trips are optimally assigned between origin and destination zones in such a way that transport energy is minimised. Energy ideally required for home-to-school/university travel is assessed as these journeys contribute a significant number of daily trips within a city. In particular, the model was applied to the urban area of Catania, a medium-sized town in Italy, for different scenarios, including improvements in the transit system and in pedestrian/cycling accessibility. The methodology proved to be suitable to evaluate the potential impact of land use and transport policies in terms of transport energy dependence, separating it from behavioural considerations.

Suggested Citation

  • Ignaccolo, Matteo & Inturri, Giuseppe & Le Pira, Michela & Caprì, Salvatore & Mancuso, Valentina, 2016. "Evaluating the role of land use and transport policies in reducing the transport energy dependence of a city," Research in Transportation Economics, Elsevier, vol. 55(C), pages 60-66.
    • Handle: RePEc:eee:retrec:v:55:y:2016:i:c:p:60-66
    DOI: 10.1016/j.retrec.2016.04.011
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    References listed on IDEAS

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    Cited by:

    1. Camilleri, Rosalie & Attard, Maria & Hickman, Robin, 2022. "Understanding barriers to modal shift in Malta: A practice-theoretical perspective of everyday mobility," Journal of Transport Geography, Elsevier, vol. 104(C).
    2. Amr, Alia'a, 2020. "Pattern recognition and transformational growth adjustments alongside ring roads: Descriptive mapping from four case studies," Land Use Policy, Elsevier, vol. 94(C).
    3. Inturri, Giuseppe & Le Pira, Michela & Giuffrida, Nadia & Ignaccolo, Matteo & Pluchino, Alessandro & Rapisarda, Andrea & D'Angelo, Riccardo, 2019. "Multi-agent simulation for planning and designing new shared mobility services," Research in Transportation Economics, Elsevier, vol. 73(C), pages 34-44.

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    More about this item

    Keywords

    Climate change mitigation; Sustainable mobility; Transportation problem; Land use planning; Transport planning; Transport energy; School commuting;
    All these keywords.

    JEL classification:

    • R41 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Transportation: Demand, Supply, and Congestion; Travel Time; Safety and Accidents; Transportation Noise
    • R42 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Government and Private Investment Analysis; Road Maintenance; Transportation Planning
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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