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Evaluating Traffic-Calming-Based Urban Road Design Solutions Featuring Cooperative Driving Technologies in Energy Efficiency Transition for Smart Cities

Author

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  • Maria Luisa Tumminello

    (Department of Engineering, University of Palermo, Viale delle Scienze ed 8, 90128 Palermo, Italy)

  • Elżbieta Macioszek

    (Department of Transport Systems, Traffic Engineering and Logistics, Faculty of Transport and Aviation Engineering, Silesian University of Technology, Krasińskiego 8 Street, 40-019 Katowice, Poland)

  • Anna Granà

    (Department of Engineering, University of Palermo, Viale delle Scienze ed 8, 90128 Palermo, Italy
    Sustainable Mobility Center (Centro Nazionale per la Mobilità Sostenibile—CNMS), Via Giovanni Durando, 39, 20158 Milano, Italy)

  • Tullio Giuffrè

    (Faculty of Engineering and Architecture, University of Enna Kore, Viale della Cooperazione, 94100 Enna, Italy)

Abstract

Traffic-calming measures (TCMs) are non-invasive devices designed to improve road mobility and urban areas on a human scale. Despite their potential, they have been in use for a long time and now have to deal with the latest technological innovations in the automotive field, such as cooperative driving technologies (CDTs), to improve energy efficiency in cities. The goal of this study is to explore the safety and operational performances of TCMs featuring CDTs in urban areas. An urban-scale road network close to a seaside area in the City of Mazara del Vallo, Italy, was properly redesigned and simulated in AIMSUN to assess several design solutions, where connected and automated vehicles (CAVs) have been employed as a more energy-efficient public transportation system. Preliminarily, the fine-tuning process of model parameters included CAVs and human-operated vehicles (HOVs) flowing through the network up to saturation conditions. The safety of the planned solutions was tested by using surrogate measures. The micro-simulation approach allowed us to know in advance and compare the operational and safety performances of environmentally friendly solutions involving TCMs and CDTs. These results can also support urban road decision makers in pivoting urban-traffic-calming-based design solutions featuring cooperative driving technologies toward energy efficiency transitions for smart cities.

Suggested Citation

  • Maria Luisa Tumminello & Elżbieta Macioszek & Anna Granà & Tullio Giuffrè, 2023. "Evaluating Traffic-Calming-Based Urban Road Design Solutions Featuring Cooperative Driving Technologies in Energy Efficiency Transition for Smart Cities," Energies, MDPI, vol. 16(21), pages 1-28, October.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:21:p:7325-:d:1269757
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    References listed on IDEAS

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    1. Maria Luisa Tumminello & Elżbieta Macioszek & Anna Granà & Tullio Giuffrè, 2023. "A Methodological Framework to Assess Road Infrastructure Safety and Performance Efficiency in the Transition toward Cooperative Driving," Sustainability, MDPI, vol. 15(12), pages 1-20, June.
    2. Gipps, P.G., 1981. "A behavioural car-following model for computer simulation," Transportation Research Part B: Methodological, Elsevier, vol. 15(2), pages 105-111, April.
    3. Giuseppe Cantisani & Maria Vittoria Corazza & Paola Di Mascio & Laura Moretti, 2023. "Eight Traffic Calming “Easy Pieces” to Shape the Everyday Pedestrian Realm," Sustainability, MDPI, vol. 15(10), pages 1-22, May.
    4. Ye, Lanhang & Yamamoto, Toshiyuki, 2019. "Evaluating the impact of connected and autonomous vehicles on traffic safety," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 526(C).
    5. Jindong Wang & Jianguo Ying & Shengchuan Jiang, 2022. "An Adaptive Traffic-Calming Measure and Effectiveness Evaluation in a Large Urban Complex of Shanghai, China," Sustainability, MDPI, vol. 14(20), pages 1-10, October.
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