IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i15p9245-d874152.html
   My bibliography  Save this article

The Use of Macro-Level Safety Performance Functions for Province-Wide Road Safety Management

Author

Listed:
  • Paolo Intini

    (Department of Civil, Environmental, Land, Building Engineering and Chemistry—DICATECh Politecnico di Bari, 70126 Bari, Italy)

  • Nicola Berloco

    (Department of Civil, Environmental, Land, Building Engineering and Chemistry—DICATECh Politecnico di Bari, 70126 Bari, Italy)

  • Stefano Coropulis

    (Department of Civil, Environmental, Land, Building Engineering and Chemistry—DICATECh Politecnico di Bari, 70126 Bari, Italy)

  • Roberta Gentile

    (Department of Civil, Environmental, Land, Building Engineering and Chemistry—DICATECh Politecnico di Bari, 70126 Bari, Italy)

  • Vittorio Ranieri

    (Department of Civil, Environmental, Land, Building Engineering and Chemistry—DICATECh Politecnico di Bari, 70126 Bari, Italy)

Abstract

Safety Performance Functions (SPFs) play a key role in identifying hotspots. Most SPFs were built at the micro-level, such as for road intersections or segments. On the other hand, in case of regional transportation planning, it may be useful to estimate SPFs at the macro-level (e.g., counties, cities, or towns) to determine ad hoc intervention prioritizations. Hence, the final aim of this study is to develop a predictive framework, supported by macro-level SPFs, to estimate crash frequencies, and consequently possible priority areas for interventions. At a province-wide level. The applicability of macro-level SPFs is investigated and tested thanks to the database retrieved in the context of a province-wide Sustainable Urban Mobility Plan (Bari, Italy). Starting from this database, the macro-areas of analysis were carved out by clustering cities and towns into census macro-zones, highlighting the potential need for safety interventions, according to different safety performance indicators (fatal + injury, fatal, pedestrian and bicycle crashes) and using basic predictors divided into geographic variables and road network-related factors. Safety performance indicators were differentiated into rural and urban, thus obtaining a set of 4 × 2 dependent variables. Then they were linked to the dependent variables by means of Negative Binomial (NB) count data models. The results show different trends for the urban and rural contexts. In the urban environment, where crashes are more frequent but less severe according to the available dataset, the increase in both population and area width leads to increasing crashes, while the increase in both road length and mean elevation are generally related to a decrease in crash occurrence. In the rural environment, the increase in population density, which was not considered in the urban context, strongly influences crash occurrence, especially leading to an increase in pedestrian and bicyclist fatal + injury crashes. The increase in the rural network length (excluding freeways) is generally related to a greater number of crashes as well. The application of this framework aims to reveal useful implications for planners and administrators who must select areas of intervention for safety purposes. Two examples of practical applications of this framework, related to safety-based infrastructural planning, are provided in this study.

Suggested Citation

  • Paolo Intini & Nicola Berloco & Stefano Coropulis & Roberta Gentile & Vittorio Ranieri, 2022. "The Use of Macro-Level Safety Performance Functions for Province-Wide Road Safety Management," Sustainability, MDPI, vol. 14(15), pages 1-16, July.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:15:p:9245-:d:874152
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/15/9245/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/14/15/9245/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Lee, Jaeyoung & Abdel-Aty, Mohamed & Jiang, Ximiao, 2014. "Development of zone system for macro-level traffic safety analysis," Journal of Transport Geography, Elsevier, vol. 38(C), pages 13-21.
    2. Shahnewaz Hasanat-E-Rabbi & Omar Faruqe Hamim & Mithun Debnath & Md. Shamsul Hoque & Rich C. McIlroy & Katherine L. Plant & Neville A. Stanton, 2021. "Exploring the Relationships between Demographics, Road Safety Attitudes, and Self-Reported Pedestrian Behaviours in Bangladesh," Sustainability, MDPI, vol. 13(19), pages 1-16, September.
    3. Lord, Dominique & Mannering, Fred, 2010. "The statistical analysis of crash-frequency data: A review and assessment of methodological alternatives," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(5), pages 291-305, June.
    4. Maja Kiba-Janiak & Jarosław Witkowski, 2019. "Sustainable Urban Mobility Plans: How Do They Work?," Sustainability, MDPI, vol. 11(17), pages 1-15, August.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Farida Saleem & Muhammad Imran Malik, 2022. "Safety Management and Safety Performance Nexus: Role of Safety Consciousness, Safety Climate, and Responsible Leadership," IJERPH, MDPI, vol. 19(20), pages 1-21, October.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Alfonso Montella & Vittorio Marzano & Filomena Mauriello & Roberta Vitillo & Roberto Fasanelli & Mariano Pernetti & Francesco Galante, 2019. "Development of Macro-Level Safety Performance Functions in the City of Naples," Sustainability, MDPI, vol. 11(7), pages 1-21, March.
    2. Najaf, Pooya & Thill, Jean-Claude & Zhang, Wenjia & Fields, Milton Greg, 2018. "City-level urban form and traffic safety: A structural equation modeling analysis of direct and indirect effects," Journal of Transport Geography, Elsevier, vol. 69(C), pages 257-270.
    3. Buddhavarapu, Prasad & Bansal, Prateek & Prozzi, Jorge A., 2021. "A new spatial count data model with time-varying parameters," Transportation Research Part B: Methodological, Elsevier, vol. 150(C), pages 566-586.
    4. Khondoker Billah & Qasim Adegbite & Hatim O. Sharif & Samer Dessouky & Lauren Simcic, 2021. "Analysis of Intersection Traffic Safety in the City of San Antonio, 2013–2017," Sustainability, MDPI, vol. 13(9), pages 1-18, May.
    5. Bo Yang & Yao Wu & Weihua Zhang & Jie Bao, 2020. "Modeling Collision Probability on Freeway: Accounting for Different Types and Severities in Various LOS," Sustainability, MDPI, vol. 12(18), pages 1-13, September.
    6. Bae, Bumjoon & Seo, Changbeom, 2022. "Do public-private partnerships help improve road safety? Finding empirical evidence using panel data models," Transport Policy, Elsevier, vol. 126(C), pages 336-342.
    7. Ghadiri, Mehdi & Rassafi, Amir Abbas & Mirbaha, Babak, 2019. "The effects of traffic zoning with regular geometric shapes on the precision of trip production models," Journal of Transport Geography, Elsevier, vol. 78(C), pages 150-159.
    8. Jaroslaw Witkowski & Jakub Marcinkowski & Maja Kiba-Janiak, 2020. "A Comparative Analysis of Electronic Freight Exchanges in the United States and Europe with the Use of the Multiple Criteria Decision-Making Method “Promethee”," European Research Studies Journal, European Research Studies Journal, vol. 0(Special 1), pages 476-487.
    9. Svetlana BAČKALIĆ & Dragan JOVANOVIĆ & Todor BAČKALIĆ & Boško MATOVIĆ & Miloš PLJAKIĆ, 2019. "The Application Of Reliability Reallocation Model In Traffic Safety Analysis On Rural Roads," Transport Problems, Silesian University of Technology, Faculty of Transport, vol. 14(1), pages 115-125, April.
    10. Izdebski, Mariusz & Jacyna-Gołda, Ilona & Gołda, Paweł, 2022. "Minimisation of the probability of serious road accidents in the transport of dangerous goods," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
    11. Dong, Chunjiao & Shao, Chunfu & Clarke, David B. & Nambisan, Shashi S., 2018. "An innovative approach for traffic crash estimation and prediction on accommodating unobserved heterogeneities," Transportation Research Part B: Methodological, Elsevier, vol. 118(C), pages 407-428.
    12. Magdalena Żak & Anna Mainka, 2020. "Cross-Regional Highway Built through a City Centre as an Example of the Sustainable Development of Urban Transport," Sustainability, MDPI, vol. 12(24), pages 1-17, December.
    13. Jingming Liu & Xianhui Hou & Chuyu Xia & Xiang Kang & Yujun Zhou, 2021. "Examining the Spatial Coordination between Metrorail Accessibility and Urban Spatial Form in the Context of Big Data," Land, MDPI, vol. 10(6), pages 1-20, May.
    14. Renfei Wu & Xunjia Zheng & Yongneng Xu & Wei Wu & Guopeng Li & Qing Xu & Zhuming Nie, 2019. "Modified Driving Safety Field Based on Trajectory Prediction Model for Pedestrian–Vehicle Collision," Sustainability, MDPI, vol. 11(22), pages 1-15, November.
    15. Lv, Jinpeng & Lord, Dominique & Zhang, Yunlong & Chen, Zhi, 2015. "Investigating Peltzman effects in adopting mandatory seat belt laws in the US: Evidence from non-occupant fatalities," Transport Policy, Elsevier, vol. 44(C), pages 58-64.
    16. Dereli, Mehmet Ali & Erdogan, Saffet, 2017. "A new model for determining the traffic accident black spots using GIS-aided spatial statistical methods," Transportation Research Part A: Policy and Practice, Elsevier, vol. 103(C), pages 106-117.
    17. Ruru Xing & Zimu Li & Xiaoyu Cai & Zepeng Yang & Ningning Zhang & Tao Yang, 2023. "Accident Rate Prediction Model for Urban Expressway Underwater Tunnel," Sustainability, MDPI, vol. 15(13), pages 1-28, July.
    18. Wang, Hwachyi & De Backer, Hans & Lauwers, Dirk & Chang, S.K.Jason, 2019. "A spatio-temporal mapping to assess bicycle collision risks on high-risk areas (Bridges) - A case study from Taipei (Taiwan)," Journal of Transport Geography, Elsevier, vol. 75(C), pages 94-109.
    19. Ulak, Mehmet Baran & Ozguven, Eren Erman & Spainhour, Lisa & Vanli, Omer Arda, 2017. "Spatial investigation of aging-involved crashes: A GIS-based case study in Northwest Florida," Journal of Transport Geography, Elsevier, vol. 58(C), pages 71-91.
    20. Petr Halámek & Radka Matuszková & Michal Radimský, 2021. "Modernisation of Regional Roads Evaluated Using Ex-Post CBA," Sustainability, MDPI, vol. 13(4), pages 1-20, February.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:14:y:2022:i:15:p:9245-:d:874152. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.