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Road safety is a worldwide issue, while urban roads account for a high share of serious road injuries, especially involving vulnerable road users, such as pedestrians or cyclists. Specifically, the safety of major roads through built up areas (through-roads) is insufficient due to mixed traffic conditions including vulnerable road users, varying driving behaviour, and many disruptions, which are combined with excessive speed. In this context, various traffic calming measures have been implemented to improve road safety, such as gateways or pedestrian refuge islands. However, the specific safety impacts of traffic calming combined with specific characteristics of through-roads are often unknown, since most traditional evaluations have been limited by small sample sizes of crash data, as well as wide variations in physical and road characteristics. To overcome the limitations of crash-based evaluations, we used the GPS-based data from a sample of 21 Czech and 12 Polish through-roads to develop the Speed-Safety Index, which combines speed, speed variance, and traffic volume. Our study has three novelty features: (1) To assess safety, we used speed and speed variance simultaneously. (2) To complete the missing link between specific traffic calming measures and safety, we validated the statistical relationship between the developed Speed-Safety Index and crash history. (3) To prove the usefulness of the developed index, we also showed its practical interpretation by proving the effect of spacing between traffic calming measures on safety. The index proved to be well correlated to crash frequency and it also proved the effect of spacing between traffic calming measures: the longer spacing, the smaller speed-reducing effect. The paper concludes with a discussion on the limitations, which we plan to address in further research, by moving from the current macro-perspective (Speed-Safety Index on the level of through-roads) to the micro-perspective (focusing on individual directions, locations, and traffic calming measures). We also plan to investigate the method’s applicability in different contexts. If the approach proves feasible, with reliable and valid results, it may become an alternative for a proactive network-wide road assessment, as called for by the European Road Infrastructure Safety Management Directive.
Czasopismo
Rocznik
Tom
Strony
113--125
Opis fizyczny
Bibliogr. 42 poz., fot., rys., tab., wykr.
Twórcy
autor
- CDV – Transport Research Centre, Brno, Czechia
autor
- CDV – Transport Research Centre, Brno, Czechia
autor
- CDV – Transport Research Centre, Brno, Czechia
autor
- Faculty of Civil Engineering, Cracow University of Technology, Poland
autor
- Faculty of Civil Engineering, Cracow University of Technology, Poland
Bibliografia
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- [5] Ambros, J., Elgner, J., Turek, R., & Valentová, V. (2020). Where and when do drivers speed? A feasibility study of using probe vehicle data for speeding analysis. Archives of Transport, 53(1), 103-113. https://doi.org/10.5604/01.3001.0014.1747.
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- [7] Ambros, J., Křivánková, Z., Zůvala, R., Bucsuházy, K., & Frič J. (2021a). Analysis of safety impact of paved shoulder width on Czech secondary roads. Archives of Transport, 60(4), 125-136. https://doi.org/10.5604/01.3001.0015.6148.
- [8] Ambros, J., Tomešová, L., Jurewicz, C., & Valentová, V. (2023). A review of the best practice in traffic calming evaluation. Accident Analysis & Prevention, 189, 107073. https://doi.org/10.1016/j.aap.2023.107073.
- [9] Ambros, J., Turek, R., Šragová, E., Petr, K., Šucha, M., & Frič, J. (2021b). How fast would you (or should you) drive here? Investigation of relationships between official speed limit, perceived speed limit, and preferred speed. Transportation Research Part F, 83, 164-178. https://doi.org/10.1016/j.trf.2021.09.003.
- [10] Ambros, J., Valentová, V., Gogolín, O., Andrášik, R., Kubeček, J., & Bíl, M. (2017). Improving the self explaining performance of Czech national roads. Transportation Research Record, 2635, 62-70. https://doi.org/10.3141/2635-08.
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- [14] Daniel, B. D., Nicholson, A., & Koorey, G. (2011). Analysing speed profiles for the estimation of speed on traffic-calmed streets. Road & Transport Research, 20(4), 57-70.
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- [17] Edquist, J., Rudin-Brown, C. M., & Lenné, M. G. (2012). The effects of on-street parking and road environment visual complexity on travel speed and reaction time. Accident Analysis & Prevention, 45, 759-765. https://doi.org/10.1016/j.aap.2011.10.001.
- [18] EU (2019). Directive (EU) 2019/1936 of the European Parliament and of the Council of 23 October 2019 amending Directive 2008/96/EC on road infrastructure safety management. https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3A32019L1936. Accessed 20 November 2023.
- [19] Farah, H., van Beinum, A., & Daamen, W. (2017). Empirical Speed Behavior on Horizontal Ramp Curves in Interchanges in the Netherlands. Transportation Research Record, 2618, 38-47. https://doi.org/10.3141/2618-04.
- [20] Figueroa-Medina, A. M., & Tarko, A. P. (2005). Speed Factors on Two-Lane Rural Highways in Free Flow Conditions. Transportation Research Record, 1912, 39-46. https://doi.org/10.3141/1912-05.
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- [22] Gaca, S., & Pogodzińska, S. (2017). Speed management as a measure to improve road safety on Polish regional roads. Archives of Transport, 43(3), 29-42. https://doi.org/10.5604/01.3001.0010.4225.
- [23] Gitelman, V., Doveh, E., & Bekhor, S. (2017). The relationship between travel speeds, infrastructure characteristics and crashes on two-lane highways. Journal of Transportation Safety & Security, 10(6), 545-571. https://doi.org/10.1080/19439962.2017.1324931.
- [24] Hillier, P., Makwasha, T., & Turner, B. (2016). Achieving Safe System Speeds on Urban Arterial Roads: Compendium of Good Practice. Publication AP-R514-16. Sydney: Austroads.
- [25] Hinkle, D. E., Wiersma, W., & Jurs, S. G. (2003). Applied Statistics for the Behavioral Sciences. 5th Edition. Boston: Cengage Learning.
- [26] Jurewicz, C. (2009). Impact of LATM Treatments on Speed and Safety. Publication AP-T123/09. Sydney: Austroads.
- [27] Lord, D., Qin, X., & Geedipally, S. R. (2021). Highway Safety Analytics and Modeling. Amsterdam: Elsevier.
- [28] Moreno, A. T., & García, A. (2013). Use of speed profile as surrogate measure: Effect of traffic calming devices on cross town road safety performance. Accident Analysis & Prevention, 61, 23-32. https://doi.org/10.1016/j.aap.2012.10.013.
- [29] Mountain, L. J., Hirst, W. M., & Maher, M. J. (2005). Are speed enforcement cameras more effective than other speed management measures? The impact of speed management schemes on 30 mph roads. Accident Analysis & Prevention, 37(4), 742-754. https://doi.org/10.1016/j.aap.2005.03.017.
- [30] NHTSA (2023). Countermeasures That Work: A Highway Safety Countermeasure Guide for State High way Safety Offices. 11th Edition. https://www.nhtsa.gov/book/countermeasures/countermeasures-that work. Accessed 20 November 2023.
- [31] OECD (1997). Road safety principles and models: Review of descriptive, predictive, risk and accident consequence models. Paris: OECD.
- [32] OECD/ITF (2018). Speed and Crash Risk. https://www.itf-oecd.org/speed-crash-risk. Accessed 20 November 2023.
- [33] OECD/ITF (2022). Road Safety Annual Report 2022. https://www.itf-oecd.org/road-safety-annual-report-2022. Accessed 20 November 2023.
- [34] Pei, X., Wong, S. C., & Sze, N. N. (2012). The roles of exposure and speed in road safety analysis. Accident Analysis & Prevention, 48, 464-471. https://doi.org/10.1016/j.aap.2012.03.005.
- [35] Shinar, D. (2017). Traffic Safety and Human Behavior. Second Edition. Bingley: Emerald. https://doi.org/10.1108/9781786352217.
- [36] Sobhani, A., Jurewicz, C., Makwasha, T., Alawi, H., & Nieuwesteeg, M. (2016). Assessing key engineering treatments addressing major pedestrian serious casualties in Victoria, Australia. in Australasian Transport Research Forum, Melbourne.
- [37] Soole, D. W., O’Hern, S., Cameron, M., Peiris, S., Newstead, S., Anderson, W., & Smith, T. (2023). Using GPS Probe Speed Data to Estimate the Attribution of Speeding on Casualty Crashes: A Case Study in Queensland. Journal of Road Safety, 34(1). https://doi.org/10.33492/JRS-D-22-00003.
- [38] Steinbakk, R. T., Ulleberg, P., Sagberg, F., & Fostervold, K. I. (2019). Speed preferences in work zones: The combined effect of visible roadwork activity, personality traits, attitudes, risk perception and driving style. Transportation Research Part F, 62, 390-405. https://doi.org/10.1016/j.trf.2019.01.017.
- [39] Straka, J., & Pelešková, J. (2023). Ročenka nehodovosti na pozemních komunikacích za rok 2022. Prague: Directorate of Service of Traffic Police.
- [40] Symon, E., & Rzepka, P. (2023). Wypadki drogowe w Polsce w 2022 roku. Warsaw: Polish Police Headquarters.
- [41] Van den Berghe, W. (2021). European Road Safety Observatory. Road Safety Thematic Report – Speed. https://ec.europa.eu/transport/road_safety/statistics-and-analysis/data-and-analysis/thematic-reports_en. Accessed 20 November 2023.
- [42] Yannis, G., Papadimitriou, E., Evgenikos, P., & Dragomanovits, A. (2015). Good practices on cost-effective road infrastructure safety investments. International Journal of Injury Control and Safety Promotion, 23(4), 373-387. https://doi.org/10.1080/17457300.2015.1047864.
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024)
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-70b5e026-9b1e-4b1f-9eab-2615a90b8032