Identification of road safety measures by elderly pedestrians based on K-Means clustering and hierarchical cluster analysis

• Autorzy: Leonardi Salvatore , Distefano Natalia , Pulvirenti Giulia

Identyfikatory

DOI

10.5604/01.3001.0014.5630

• Języki publikacji: EN

Abstrakty

EN

Introduction: Pedestrians aged over 65 are known to be a critical group in terms of road safety because they represent the age group with the highest number of fatalities or injured people in road accidents. With a current ageing population throughout much of the developed world, there is an imminent need to understand the current transportation requirements of older adults, and to ensure sustained safe mobility and healthy. Objectives: The aim of this study is to capture and analyze the key components that influence the identification of design solutions and strategies aimed at improving the safety of pedestrian paths for elderly. Method: A survey was conducted in 5 different locations in Catania, Italy. The locations were specifically chosen near to attraction poles for elderly pedestrians (e.g. centers for the elderly, squares, churches). Participants were recruited in person, so as to select exclusively people over 70. The sample comprised 322 participants. Both Hierarchical and K-Means clustering were used in order to explore which solutions elderly pedestrian propose for improving the safety of pedestrian path. Results: The results show that the judgment expressed by the elderly on the solutions for improving pedestrian safety is linked to the gender, to the experience as road users, and to mobility and vision problems. All solutions proposed regard road infrastructure (improvement of pedestrian crossings and of sidewalks, implementation of traffic calming measures, improvement of lighting), except for police supervision. Conclusion: This study has identified the factors that influence the identification of the best solutions to increase the safety level of pedestrian paths for elderly people. The aspects related to human factors considered were the gender, the factors associated with the experience as road users and the factors related to age related problems (mobility, vision and hearing problems). The results of this research could support traffic engineers, planners, and decision-makers to consider the contributing factors in engineering measures to improve the safety of vulnerable users such as elderly pedestrians.

Słowa kluczowe

EN

road traffic; safety measures; road safety; cluster analysis; human factor; vulnerable users; elderly pedestrians

PL

ruch drogowy; środki bezpieczeństwa; bezpieczeństwo na drogach; analiza skupień; czynnik ludzki; wrażliwi użytkownicy

• Wydawca: Warsaw University of Technology, Faculty of Transport
• Czasopismo: Archives of Transport
• Rocznik: 2020
• Tom: Vol. 56, iss. 4
• Strony: 107--118
• Opis fizyczny: Bibliogr. 51 poz., rys., tab.

Twórcy

autor

Leonardi Salvatore

• University of Catania, Department of Civil Engineering and Architectural, Catania, Italy

autor

Distefano Natalia

• University of Catania, Department of Civil Engineering and Architectural, Catania, Italy

autor

Pulvirenti Giulia

• University of Catania, Department of Civil Engineering and Architectural, Catania, Italy

Bibliografia

• [1] Abay, K. A. (2013). Examining pedestrian-in-jury severity using alternative disaggregate models. Research in Transportation Economics, 43(1), 123-136.
• [2] Barnett, A., Cerin, E., Zhang, C. J. P., Sit, C. H. P., Johnston, J. M., Cheung, M. M. C., & Lee, R. S. Y. (2016). Associations between the neighbourhood environment characteristics and physical activity in older adults with specific types of chronic conditions: The ALECS cross-sectional study. International Journal of Behavioral Nutrition and Physical Activity, 13(1), 53. https://doi.org/10.1186/s12966-016-0377-7
• [3] Benenson, I., Martens, K., Rofé, Y., Kwartler, A. (2011). Public transport versus private car GIS-based estimation of accessibility applied to the Tel Aviv metropolitan area. The Annals of Regional Science, 47(3), pp. 499-515.
• [4] Campisi, T., Canale, A. and Tesoriere, G. (2018). SWOT analysis for the implementation of spaces and pedestrian paths at the street markets of Palermo in AIP Conference Proceedings, 140003.
• [5] Canale, S., Distefano, N. and Leonardi, S. (2015). Comparative analysis of pedestrian accidents risk at unsignalized intersections. The Baltic Journal of Road and Bridge Engineering, 10(4), 283-292.
• [6] Chen, J. and Millar, W. J. (2000). Are recent cohorts healthier than their predecessors?, in Health Reports / Statistics Canada, Canadian Centre for Health Information.
• [7] Choudhari, T. and Maji, A. (2019). Socio-demographic and experience factors affecting drivers’ runoff risk along horizontal curves of two-lane rural highway. Journal of Safety Research, 71, 1-11.
• [8] Depaire, B., Wets, G. and Vanhoof, K. (2008). Traffic accident segmentation by means of latent class clustering. Accident Analysis & Prevention, 40(4), 1257-1266.
• [9] Distefano, N., Leonardi, S. and Pulvirenti, G. (2018). Factors with the greatest influence on drivers’ judgment of roundabouts safety. An analysis based on web survey in Italy. IATSS Research, 42(4), 265-273.
• [10] Distefano, N. and Leonardi, S. (2019). Evaluation of the Benefits of Traffic Calming on Vehicle Speed Reduction. Civil Engineering and Architecture, 7(4), 200-214.
• [11] Distefano, N., Leonardi, S. and Consoli, F. (2019). Drivers’ Preferences for Road Roundabouts: A Study based on Stated Preference Survey in Italy. KSCE Journal of Civil Engineering, 23(11), 4864-4874.
• [12] Distefano, N., Leonardi, S. and Pulvirenti, G. (2019). Home-school Travel: Analysis of Factors Affecting Italian Parents’ Mode Choice. Civil Engineering and Architecture, 7(3), 75-87.
• [13] Dunbar, G., Holland, C. A., & Maylor, E. A. (2004). Older pedestrians: a critical review of the literature. Road Safety Research Report.
• [14] Eluru, N., Bhat, C. R. and Hensher, D. A. (2008). A mixed generalized ordered response model for examining pedestrian and bicyclist injury severity level in traffic crashes. Accident Analysis & Prevention, 40(3), 1033-1054.
• [15] Fontaine, H. and Gourlet, Y. (1997). Fatal pedestrian accidents in France: A typological analysis. Accident Analysis & Prevention, 29(3), 303-312.
• [16] Fraley, C. and Raftery, A. E. (2002). Model-Based Clustering, Discriminant Analysis, and Density Estimation. Journal of the American Statistical Association, 97(458), 611-631.
• [17] Ghasemlou, K., Aydın, M., and Yıldırım, M. S. (2015). Prediction of pedal cyclists and pedestrian fatalities from total monthly accidents and registered private car numbers. Archives of Transport, 34, 29-35.
• [18] Giuffrida, N., Ignaccolo, M., Inturri, G., Rofè, Y. and Calabrò, G. (2017). Investigating the Correlation between Transportation Social Need and Accessibility: The Case of Catania. Transportation Research Procedia, 27, 816-823.
• [19] Giuffrida, N., Inturri, G., Caprì, S., Spica, S., Ignaccolo, M. (2017). The impact of a bus rapid transit line on spatial accessibility and transport equity: The case of Catania, in Proceedings of the AIIT International Congress on Transport Infrastructure and Systems, 753-758.
• [20] Gruden, C., Campisi, T., Canale, A., Tesoriere, G. and Sraml, M. (2019). A cross-study on video data gathering and microsimulation techniques to estimate pedestrian safety level in a confined space. IOP Conference Series: Materials Science and Engineering, 603(4), 042008.
• [21] Hair, J. F., Anderson, R. E., Tatham, R. L. and Black, W. C. (1998). Multivariate data analysis. (5th ed.). Englewood Cliffs, Prentice Hall.
• [22] Ignaccolo, M., Inturri, G., Giuffrida, N., Le Pira, M., Torrisi, V. (2019). Public Engagement for Designing New Transport Services: Investigating Citizen Preferences from a Multiple Criteria Perspective. Transportation Research Procedia, 37, 91–98.
• [23] Ketcham, C. J. and Stelmach, G. E. (2001). Age-Related Declines in Motor Control, in Handbook of the Psychology of Aging.
• [24] Kim, M., Kho, S.-Y. and Kim, D.-K. (2017). Hierarchical ordered model for injury severity of pedestrian crashes in South Korea. Journal of Safety Research, 61, 33-40.
• [25] Leonardi, S., Distefano, N., and Pulvirenti, G. (2019). Multiple Correspondence Analysis (MCA) for the evaluation of risk perception of roundabouts for young people. European Transport/Trasporti Europei, 72, 1-23.
• [26] Leonardi, S., Distefano, N. and Pulvirenti, G. (2020). Italians’ public opinion on road rounda-bouts: A web based survey. Transportation Research Procedia, 45, 293-300.
• [27] Lin, X. and Xu, J. (2020). Road network partitioning method based on Canopy-Kmeans clustering algorithm. Archives of Transport, 54, 95-106.
• [28] Martin, A. J., Hand, E. B., Trace, F. and O’Neill, D. (2010). Pedestrian Fatalities and Injuries Involving Irish Older People. Gerontology, 56(3), 266-271.
• [29] Montella, A., Aria, M., D’Ambrosio, A. and Mauriello, F. (2011). Data-Mining Techniques for Exploratory Analysis of Pedestrian Crashes. Transportation Research Record: Journal of the Transportation Research Board, 2237(1), pp. 107-16.
• [30] Mrak, I., Campisi, T., Tesoriere, G., Canale, A., Cindrić, M. (2019). The role of urban and social factors in the accessibility of urban areas for people with motor and visual disabilities’, in. AIP Conference Proceedings 2186, 160008.
• [31] ONU, World Population Ageing (2015). New York, Department of Economic and Social Affairs, Population Division, United Nations.
• [32] Oxley, J., Fildes, B., Ihsen, E., Charlton, J. and Day, R. (1997). Differences in traffic judgements between young and old adult pedestrians. Accident Analysis & Prevention, 29(6), 839-847.
• [33] PIN Flash Report 38 (2020). European Transport Safety Council, Brussels.
• [34] Pour-Rouholamin, M., and Zhou, H. (2016). Investigating the risk factors associated with pedestrian injury severity in Illinois. Journal of Safety Research, 57, 9-17.
• [35] Pulvirenti, G., Distefano, N. and Leonardi, S. (2020). Elderly Perception of Critical Issues of Pedestrian Paths. Civil Engineering and Architecture, 8(1), 26-37.
• [36] Retting, R. A. (1993). A study of fatal crashes involving pedestrians and trucks in four cities. Journal of Safety Research, 24(4), 195-203.
• [37] Road Safety Research Report (2004). Department for Transport.
• [38] Shumway-Cook, A. and Woollacott, M. H. (2001). Motor Control: Theory and Practical Applications (2nd ed.), Baltimore.
• [39] Sivasankaran, S. K. and Balasubramanian, V. (2020). Exploring the severity of bicycle-vehicle crashes using latent class clustering approach in India. Journal of Safety Research, 72, 127-138.
• [40] Sklar, D. P., Demarest, G. B. and McFeeley, P. (1989). Increased pedestrian mortality among the elderly. The American Journal of Emergency Medicine, 7(4), 387-390.
• [41] Staplin, L., Lococo, K., Byington, S., Harkey, D. (2001). Guidelines and recommendations to accommodate older drivers and pedestrians, FHWA-RD-01-051. U.S. Department of Transportation.
• [42] Thakur, S., Biswas, S. (2019). Assessment of pedestrian-vehicle interaction on urban roads: a critical review. Archives of Transport, 51(3), 49-63.
• [43] Tollazzi, T., Renčelj, M., Rodošek, V. and Zalar, B. (2010). Traffic Safety of Older Drivers in Various Types of Road Intersections. PROMET - Traffic&Transportation, 22(3), 193-201.
• [44] Vorko-Jović, A., Kern, J. and Biloglav, Z. (2006). Risk factors in urban road traffic accidents. Journal of Safety Research, 37(1), 93-98.
• [45] Wang, Y., Haque, Md. M. and Chin, H.-C. (2017). Elderly pedestrian injuries in Singapore’, Journal of Transportation Safety & Security, 9(3), 273-300.
• [46] West, R. (2001). The transient nature of executive control processes in younger and older adults. European Journal of Cognitive Psychology, 13(1-2), 91-105.
• [47] Wilson D. G. and Grayson G. B. (1980). Agerelated differences in the road crossing behaviour of adult pedestrians. TRRL Report 933.
• [48] Xu, R. and Wunsch, D. (2005). Survey of Clustering Algorithms. IEEE Transactions on Neural Networks, 16(3), 645-678.
• [49] Yee, W. Y. (2006). Road traffic injuries in the elderly. Emergency Medicine Journal, 23(1), 42-46.
• [50] Zhou, M. and Lyles, R. W. (1997). Mobility Pat-terns of the Next Generation of Older Persons. Transportation Research Record: Journal of the Transportation Research Board, 1573(1), 99-104.
• [51] Zivotofsky, A. Z., Eldror, E., Mandel, R. and Rosenbloom, T. (2012). Misjudging Their Own Steps: Why Elderly People Have Trouble Crossing the Road. Human Factors: The Journal of the Human Factors and Ergonomics Society, 54(4), 600-607.

Uwagi

The article has been presented on 13th International BRD GAMBIT 2020 Conference. Co-funded by the Science Excellence programme of the Ministry of Science and Higher Education.