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Crash Risk Analysis in Highway Work Zones: A Predictive Model Based on Technical, Infrastructural, and Environmental Factors

Author

Listed:
  • Sofia Palese

    (Department of Civil, Chemical, Environmental and Materials (DICAM) Engineering, University of Bologna, Viale del Risorgimento 2, 40136 Bologna, Italy)

  • Margherita Pazzini

    (Department of Civil, Chemical, Environmental and Materials (DICAM) Engineering, University of Bologna, Viale del Risorgimento 2, 40136 Bologna, Italy)

  • Davide Chiola

    (R&D and Innovation, Movyon S.p.a., 50013 Firenze, Italy)

  • Claudio Lantieri

    (Department of Civil, Chemical, Environmental and Materials (DICAM) Engineering, University of Bologna, Viale del Risorgimento 2, 40136 Bologna, Italy)

  • Andrea Simone

    (Department of Civil, Chemical, Environmental and Materials (DICAM) Engineering, University of Bologna, Viale del Risorgimento 2, 40136 Bologna, Italy)

  • Valeria Vignali

    (Department of Civil, Chemical, Environmental and Materials (DICAM) Engineering, University of Bologna, Viale del Risorgimento 2, 40136 Bologna, Italy)

Abstract

Road infrastructure is the foundation of the predominant modes of transport, and its effective management is crucial to meet mobility needs. Although necessary for reconstruction, maintenance, and expansion projects, roadworks produce negative impacts, resulting in further risk for workers and drivers and failing to ensure sustainable development. The objective of this paper is twofold: Firstly, investigate the contributing factors to the occurrence of crashes in roadworks. Secondly, develop a model to estimate crash numbers in these areas. The results, which could support municipalities at the planning stage and implement policies for safe and sustainable development, are achieved by examining 121 sites, where 549 crashes occurred, and 25 contributing factors. The variables are divided into three categories: technical characteristics of the site, infrastructural, and environmental. Besides the conventional variables, a risk-increasing factor is calibrated. It assesses the impact of roadworks according to the manoeuvres imposed and the number of lanes. Consistent with previous findings, several variables related to the work zone layout, traffic conditions, infrastructure, and surrounding environment are correlated with the crash number. After performing a further statistical analysis, a multiple linear regression model, statistically significant (0.000) and suitable for accurately estimating the possible number of crashes (R 2 adj = 0.41), is determined.

Suggested Citation

  • Sofia Palese & Margherita Pazzini & Davide Chiola & Claudio Lantieri & Andrea Simone & Valeria Vignali, 2025. "Crash Risk Analysis in Highway Work Zones: A Predictive Model Based on Technical, Infrastructural, and Environmental Factors," Sustainability, MDPI, vol. 17(13), pages 1-20, July.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:13:p:6112-:d:1694226
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    References listed on IDEAS

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    1. Spasoje Mićić & Radoje Vujadinović & Goran Amidžić & Milanko Damjanović & Boško Matović, 2022. "Accident Frequency Prediction Model for Flat Rural Roads in Serbia," Sustainability, MDPI, vol. 14(13), pages 1-14, June.
    2. Rafael Prieto Curiel & Humberto González Ramírez & Steven Richard Bishop, 2018. "A novel rare event approach to measure the randomness and concentration of road accidents," PLOS ONE, Public Library of Science, vol. 13(8), pages 1-18, August.
    3. Ana V. Arias & Sonia Mayordomo Lopez & Itziar Fernandez & Jose Luis Martinez-Rubio & Alejandro Magallares, 2008. "Psychosocial factors, perceived risk and driving in a hostile environment: driving through tunnels," International Journal of Global Environmental Issues, Inderscience Enterprises Ltd, vol. 8(1/2), pages 165-181.
    4. Adriana Vieira & Bertha Santos & Luís Picado-Santos, 2023. "Modelling Road Work Zone Crashes’ Nature and Type of Person Involved Using Multinomial Logistic Regression," Sustainability, MDPI, vol. 15(3), pages 1-24, February.
    5. Nan Ouyang, 2021. "Comprehensive Operation Risk Assessment of a Highway Maintenance Area Based on Reliability," Sustainability, MDPI, vol. 13(16), pages 1-21, August.
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