Hazardous traffic scenarios for motorcyclists in Indonesia: a comprehensive insight from police accident data and self-reports

References

• Abdul Manan, M. M. (2014). Motorcycles entering from access points and merging with traffic on primary roads in Malaysia: Behavioral and road environment influence on the occurrence of traffic conflicts. Accident Analysis and Prevention, 70, 301–313. https://doi.org/10.1016/j.aap.2014.04.009
   PubMed Web of Science ®Google Scholar
• Abdul Manan, M. M., Jonsson, T., & Várhelyi, A. (2013). Development of a safety performance function for motorcycle accident fatalities on Malaysian primary roads. Safety Science, 60, 13–20. https://doi.org/10.1016/j.ssci.2013.06.005
   Web of Science ®Google Scholar
• Abdul Manan, M. M., & Várhelyi, A. (2015). Motorcyclists’ road safety related behavior at access points on primary roads in Malaysia – A case study. Safety Science, 77, 80–94. https://doi.org/10.1016/j.ssci.2015.03.012
   Web of Science ®Google Scholar
• Abdul Manan, M. M., Várhelyi, A., Çelik, A. K., & Hashim, H. H. (2018). Road characteristics and environment factors associated with motorcycle fatal crashes in Malaysia. IATSS Research, 42(4), 207–220. https://doi.org/10.1016/j.iatssr.2017.11.001
   Web of Science ®Google Scholar
• Abusini, S., & Ambarwati, L. (2019). Motorcycle accident model for highlands regions by applying Generaliazed Linear Model (GLM). Lowland Technology International, 22(3), 331–339.
   Google Scholar
• Af Wåhlberg, A. E., & Dorn, L. (2015). How reliable are self-report measures of mileage, violations and crashes?. Safety Science, 76, 67–73. https://doi.org/10.1016/j.ssci.2015.02.020
   Web of Science ®Google Scholar
• Ahmed, A., Sadullah, A. F. M., & Yahya, A. S. (2019). Errors in accident data, its types, causes and methods of rectification-analysis of the literature. Accident Analysis and Prevention, 130(February 2017), 3–21. https://doi.org/10.1016/j.aap.2017.07.018
   PubMedGoogle Scholar
• Atalar, D., & Thomas, P. (2019). Powered two-wheeler crash scenario development. Accident Analysis and Prevention, 125(February), 198–206. https://doi.org/10.1016/j.aap.2019.02.001
   PubMedGoogle Scholar
• Ballestar, M. T., Grau-Carles, P., & Sainz, J. (2018). Customer segmentation in e-commerce: Applications to the cashback business model. Journal of Business Research, 88(June 2017), 407–414. https://doi.org/10.1016/j.jbusres.2017.11.047
   Google Scholar
• Blackman, R. A., & Haworth, N. L. (2013). Comparison of moped, scooter and motorcycle crash risk and crash severity. Accident Analysis and Prevention, 57, 1–9. https://doi.org/10.1016/j.aap.2013.03.026
   PubMed Web of Science ®Google Scholar
• Bureau of Statistics Indonesia. (2022). Statistik Indonesia 2022 (Statistical year book of Indonesia 2022).
   Google Scholar
• Chang, H.-L., & Yeh, T.-H. (2007). Motorcyclist accident involvement by age, gender, and risky behaviors in Taipei, Taiwan. Transportation Research Part F: Traffic Psychology and Behaviour, 10(2), 109–122. https://doi.org/10.1016/j.trf.2006.08.001
   Web of Science ®Google Scholar
• Chaturvedi, A., Foods, K., Green, P. E., & Carroll, J. D. (2001). K-modes clustering. Journal of Classification, 18(1), 35–55. https://doi.org/10.1007/s00357-001-0004-3
   Web of Science ®Google Scholar
• Chiu, B. Y. (2022). Does the bus rapid transit reduce motorcycle use? Evidence from the Jakarta metropolitan area, Indonesia. Case Studies on Transport Policy, 10(3), 1767–1774. https://doi.org/10.1016/j.cstp.2022.07.007
   Web of Science ®Google Scholar
• Chung, Y., & Chang, I. (2015). How accurate is accident data in road safety research? An application of vehicle black box data regarding pedestrian-to-taxi accidents in Korea. Accident Analysis and Prevention, 84, 1–8. https://doi.org/10.1016/j.aap.2015.08.001
   PubMed Web of Science ®Google Scholar
• Clabaux, N., Brenac, T., Perrin, C., Magnin, J., Canu, B., & Van Elslande, P. (2012). Motorcyclists’ speed and “looked-but-failed-to-see” accidents. Accident Analysis and Prevention, 49, 73–77. https://doi.org/10.1016/j.aap.2011.07.013
   PubMed Web of Science ®Google Scholar
• Comi, A., Polimeni, A., & Balsamo, C. (2022). Road accident analysis with data mining approach: Evidence from Rome. Transportation Research Procedia, 62(Ewgt 2021), 798–805. https://doi.org/10.1016/j.trpro.2022.02.099
   Google Scholar
• Damani, J., & Vedagiri, P. (2021). Safety of motorised two wheelers in mixed traffic conditions: Literature review of risk factors. Journal of Traffic and Transportation Engineering (English Edition), 8(1), 35–56. https://doi.org/10.1016/j.jtte.2020.12.003
   Google Scholar
• Das, S. (2021). Identifying key patterns in motorcycle crashes: Findings from taxicab correspondence analysis. Transportmetrica A: Transport Science, 17(4), 593–614. https://doi.org/10.1080/23249935.2020.1802362
   Web of Science ®Google Scholar
• De Oña, J., López, G., Mujalli, R., & Calvo, F. J. (2013). Analysis of traffic accidents on rural highways using Latent Class Clustering and Bayesian Networks. Accident Analysis and Prevention, 51, 1–10. https://doi.org/10.1016/j.aap.2012.10.016
   PubMed Web of Science ®Google Scholar
• Depaire, B., Wets, G., & Vanhoof, K. (2008). Traffic accident segmentation by means of latent class clustering. Accident Analysis and Prevention, 40(4), 1257–1266. https://doi.org/10.1016/j.aap.2008.01.007
   PubMed Web of Science ®Google Scholar
• Djoeworo, W. R., Tasono Hadi, D. P., & Darjoko, S. T. (2018). Motorcycle accident injuries are more severe than other land transportation injuries. Universa Medicina, 37(2), 105–114. https://doi.org/10.18051/UnivMed.2018.v37.105-114
   Google Scholar
• Esenturk, E., Turley, D., Wallace, A., Khastgir, S., & Jennings, P. (2022). A data mining approach for traffic accidents, pattern extraction and test scenario generation for autonomous vehicles. International Journal of Transportation Science and Technology, 12(4), 955–972. https://doi.org/10.1016/j.ijtst.2022.10.002
   Google Scholar
• Fattah, M. A., Morshed, S. R., Morshed, S. Y., Hoque, M. M., & Haque, M. N. (2021). The impact of urban street median in pedestrian behavior and traffic flow: Experience from a growing city Khulna, Bangladesh. Transportation Engineering, 6, 100090. https://doi.org/10.1016/j.treng.2021.100090
   Google Scholar
• Feng, S., Li, Z., Ci, Y., & Zhang, G. (2016). Risk factors affecting fatal bus accident severity: Their impact on different types of bus drivers. Accident Analysis and Prevention, 86, 29–39. https://doi.org/10.1016/j.aap.2015.09.025
   PubMed Web of Science ®Google Scholar
• Ferdosian, Z., Morowatisharifabad, M. A., & Rezaeipandari, H. (2015). Unlicensed motorcycling of high school adolescents in Dehaghan county (Isfahan Province of Iran). Accident Analysis and Prevention, 75, 211–216. https://doi.org/10.1016/j.aap.2014.12.002
   PubMed Web of Science ®Google Scholar
• Fetters, M. D., Curry, L. A., & Creswell, J. W. (2013). Achieving integration in mixed methods designs – Principles and practices. Health Services Research, 48(6 Pt 2), 2134–2156. https://doi.org/10.1111/1475-6773.12117
   PubMed Web of Science ®Google Scholar
• Fraenkel, J. R., Wallen, N. E., & Hyun, H. H. (2012). How to design and evaluate research in education (8th ed.). McGraw-Hill Companies.
   Google Scholar
• Government of Republic of Indonesia. (2009). Undang-Undang Republik Indonesia Nomor 22 Tahun 2009 Tentang lalu Lintas dan Angkutan Jalan (Law of the Republic of Indonesia Number 22 Year 2009 on Road Traffic and Transportation). Pemerintah Republik Indonesia.
   Google Scholar
• Guerra, E., Gamble, J., & Taylor, J. (2020). Bus rapid transit in Solo, Indonesia: Lessons from a low ridership system. Case Studies on Transport Policy, 8(2), 492–499. https://doi.org/10.1016/j.cstp.2019.11.002
   Web of Science ®Google Scholar
• Halpern, N., Mwesiumo, D., Budd, T., Suau-Sanchez, P., & Bråthen, S. (2021). Segmentation of passenger preferences for using digital technologies at airports in Norway. Journal of Air Transport Management, 91(December 2020), 102005. https://doi.org/10.1016/j.jairtraman.2020.102005
   Google Scholar
• Harantová, V., Mazanec, J., Štefancová, V., Mašek, J., & Foltýnová, H. B. (2023). Two-step cluster analysis of passenger mobility segmentation during the COVID-19 pandemic. Mathematics, 11(3), 583. https://doi.org/10.3390/math11030583
   Web of Science ®Google Scholar
• Haworth, N. (2012). Powered two wheelers in a changing world – Challenges and opportunities. Accident Analysis and Prevention, 44(1), 12–18. https://doi.org/10.1016/j.aap.2010.10.031
   PubMed Web of Science ®Google Scholar
• Haynes-Brown, T. K., & Fetters, M. D. (2021). Using joint display as an analytic process: An illustration using bar graphs joint displays from a mixed methods study of how beliefs shape secondary school teachers’ use of technology. International Journal of Qualitative Methods, 20, 160940692199328. https://doi.org/10.1177/1609406921993286
   Web of Science ®Google Scholar
• Ilham, M. Y., Surjandari, I., & Laoh, E. (2020). Analyzing highway road accident characteristic using data mining. 2020 International Workshop on Big Data and Information Security (IWBIS), 17–22. https://doi.org/10.1109/IWBIS50925.2020.9255655
   Google Scholar
• Joewono, T. B., & Susilo, Y. O. (2017). Traffic violations by young motorcyclists on Indonesian urban roads. Journal of Transportation Safety & Security, 9(sup1), 236–261. https://doi.org/10.1080/19439962.2016.1247123
   Web of Science ®Google Scholar
• Jusuf, A., Nurprasetio, I. P., & Prihutama, A, Lightweight Structures Research Group, Faculty of Mechanical and Aerospace Engineering, Institut Teknologi Bandung, Jalan Ganesha 10, Bandung 40132, Indonesia. (2017). Macro data analysis of traffic accidents in Indonesia. Journal of Engineering and Technological Sciences, 49(1), 132–143. https://doi.org/10.5614/j.eng.technol.sci.2017.49.1.8
   Google Scholar
• Kamaluddin, N. A., Andersen, C. S., Larsen, M. K., Meltofte, K. R., & Várhelyi, A. (2018). Self-reporting traffic crashes-a systematic literature review. European Transport Research Review, 10(2), 1–18. https://doi.org/10.1186/s12544-018-0301-0
   Web of Science ®Google Scholar
• Kaplan, S., & Prato, C. G. (2013). Cyclist-motorist crash patterns in Denmark: A latent class clustering approach. Traffic Injury Prevention, 14(7), 725–733. https://doi.org/10.1080/15389588.2012.759654
   PubMed Web of Science ®Google Scholar
• Kashani, A. T., Jafari, M., Bondarabadi, M. A., & Dabirinejad, S. (2020). Factors affecting the accident size of motorcycle-involved crashes: A structural equation modeling approach. International Journal of Injury Control and Safety Promotion, 28(1), 16–21. https://doi.org/10.1080/17457300.2020.1833041
   PubMed Web of Science ®Google Scholar
• Kent, P., Jensen, R. K., & Kongsted, A. (2014). A comparison of three clustering methods for finding subgroups in MRI, SMS or clinical data: SPSS twostep cluster analysis, latent gold and SNOB. BMC Medical Research Methodology, 14(1), 113. https://doi.org/10.1186/1471-2288-14-113
   PubMedGoogle Scholar
• King, M. R., Carnegie, J. A., Ewing, R., Carnegie, J. A., & Ewing, R. (2003). Pedestrian safety through a raised median and redesigned intersections. Transportation Research Record: Journal of the Transportation Research Board, 1828(1), 56–66. https://doi.org/10.3141/1828-07
   Google Scholar
• Kumar, S., & Toshniwal, D. (2015). A data mining framework to analyze road accident data. Journal of Big Data, 2(1). https://doi.org/10.1186/s40537-015-0035-y
   PubMedGoogle Scholar
• Kusumastutie, N. S., Patria, B., Kusrohmaniah, S., & Hastjarjo, T. D. (2024). A review of accident data for traffic safety studies in Indonesia. IOP Conference Series: Earth and Environmental Science, 1294(1), 012012. https://doi.org/10.1088/1755-1315/1294/1/012012
   Google Scholar
• Kusumastutie, N. S., & Rusmandani, P. (2019). A brief review: Traffic conflict techniques and the challenges of the studies in Indonesia. MATEC Web of Conferences, 270, 03004. https://doi.org/10.1051/matecconf/201927003004
   Google Scholar
• Kusumastutie, N. S., & Saptandari, E. W. (2023). Sekarang atau nanti? Sebuah studi mixed methods tentang keputusan ibu dari siswa SMP untuk mengizinkan anak berkendara sepeda motor (Now or later? A mixed-methods study on the decisions of mothers of junior high school students to allow their children to riding motorcycles). Jurnal Psikologi, 16(1), 160–178. https://doi.org/10.35760/psi.2023.v16i1.6159
   Google Scholar
• La, Q. N., Duong, D. V., Lee, A. H., & Meuleners, L. B. (2017). Factors underlying bus-related crashes in Hanoi, Vietnam. Transportation Research Part F: Traffic Psychology and Behaviour, 46, 426–437. https://doi.org/10.1016/j.trf.2016.06.023
   Web of Science ®Google Scholar
• Laureshyn, A., & Varhelyi, A. (2018). The Swedish traffic conflict technique observer’s manual. Lund University.
   Google Scholar
• Lin, M. R., & Kraus, J. F. (2009). A review of risk factors and patterns of motorcycle injuries. Accident Analysis and Prevention, 41(4), 710–722. https://doi.org/10.1016/j.aap.2009.03.010
   PubMed Web of Science ®Google Scholar
• Mariana, A. T., & Dewi, F. S. T. (2018). Cedera akibat kecelakaan lalu lintas di Sleman, DIY: Data HDSS 2015 dan 2016 (Injuries due to traffic accidents in Sleman, Yogyakarta: HDSS Data 2015 and 2016). Berita Kedokteran Masyarakat, 34(6), 230–235.
   Google Scholar
• Marquand, A. F., Wolfers, T., Mennes, M., Buitelaar, J., & Beckmann, C. F. (2016). Beyond lumping and splitting: A review of computational approaches for stratifying psychiatric disorders. Biological Psychiatry. Cognitive Neuroscience and Neuroimaging, 1(5), 433–447. https://doi.org/10.1016/j.bpsc.2016.04.002
   PubMedGoogle Scholar
• Naqvi, H. M., & Tiwari, G. (2017). Factors contributing to motorcycle fatal crashes on national highways in India. Transportation Research Procedia, 25, 2084–2097. https://doi.org/10.1016/j.trpro.2017.05.402
   Google Scholar
• Nguyen, M. H., Pojani, D., & Nguyen-Phuoc, D. Q. (2023). What leads underage teenagers to ride motorcycles without a permit? Utility vs parental permissiveness. Journal of Transport & Health, 29(October 2022), 101569. https://doi.org/10.1016/j.jth.2023.101569
   Google Scholar
• Nitsche, P., Thomas, P., Stuetz, R., & Welsh, R. (2017). Pre-crash scenarios at road junctions: A clustering method for car crash data. Accident Analysis and Prevention, 107(March), 137–151. https://doi.org/10.1016/j.aap.2017.07.011
   PubMedGoogle Scholar
• Older, S. J., & Shippey, J. (1977). Traffic conflict studies in the United Kingdom. In F. H. Amundsen & C. Hyden (Eds.), Proceedings of the first workshop on traffic conflicts (pp. 1–15). https://doi.org/10.1016/0001-4575(79)90066-6
   Google Scholar
• Ortiz, M. A., & Bluyssen, P. M. (2022). Profiling office workers based on their self-reported preferences of indoor environmental quality and psychosocial comfort at their workplace during COVID-19. Building and Environment, 211(January), 108742. https://doi.org/10.1016/j.buildenv.2021.108742
   PubMedGoogle Scholar
• Ospina-Mateus, H., Quintana Jiménez, L. A., Lopez-Valdes, F. J., & Salas-Navarro, K. (2019). Bibliometric analysis in motorcycle accident research: A global overview. Scientometrics, 121(2), 793–815. https://doi.org/10.1007/s11192-019-03234-5
   Web of Science ®Google Scholar
• Pai, C. W. (2011). Motorcycle right-of-way accidents – A literature review. Accident Analysis and Prevention, 43(3), 971–982. https://doi.org/10.1016/j.aap.2010.11.024
   PubMed Web of Science ®Google Scholar
• Pang, T. Y., Umar, R. S., Azhar, A. A., Ahmad, M. M., Nasir, M. T., & Harwant, S. (2000). Accident characteristics of injured motorcyclists in Malaysia. Medical Journal of Malaysia, 55(1), 45–50.
   PubMedGoogle Scholar
• Pervez, A., Lee, J., & Huang, H. (2021). Identifying factors contributing to the motorcycle crash severity in Pakistan. Journal of Advanced Transportation, 2021, 1–10. https://doi.org/10.1155/2021/6636130
   Web of Science ®Google Scholar
• Potard, C., & Landais, C. (2021). The use of cluster analysis to identify different burnout profiles among nurses and care assistants for older adults. Geriatric Nursing (New York, N.Y.), 42(5), 1135–1142. https://doi.org/10.1016/j.gerinurse.2021.07.005
   PubMed Web of Science ®Google Scholar
• Pour-Rouholamin, M., Jalayer, M., & Zhou, H. (2017). Modelling single-vehicle, single-rider motorcycle crash injury severity: An ordinal logistic regression approach. International Journal of Urban Sciences, 21(3), 344–363. https://doi.org/10.1080/12265934.2017.1311801
   Web of Science ®Google Scholar
• Pulugurtha, S., Vasudevan, V., Nambisan, S., & Dangeti, M. (2012). Evaluating effectiveness of infrastructure-based countermeasures for pedestrian safety. Transportation Research Record: Journal of the Transportation Research Board, 2299(1), 100–109. https://doi.org/10.3141/2299-11
   Google Scholar
• Radin Umar, R. S. (2006). Motorcycle safety programmes in Malaysia: How effective are they? International Journal of Injury Control and Safety Promotion, 13(2), 71–79. https://doi.org/10.1080/17457300500249632
   PubMedGoogle Scholar
• Rahimi, A., Azimi, G., Asgari, H., & Jin, X. (2019). Clustering approach toward large truck crash analysis. Transportation Research Record: Journal of the Transportation Research Board, 2673(8), 73–85. https://doi.org/10.1177/0361198119839347
   Web of Science ®Google Scholar
• Ramlan, R., Irawan, M. Z., & Munawar, A. (2021). Behavioral factors of motorcyclists in right-turn movements at unsignalized intersections: An insight from Yogyakarta, Indonesia. IATSS Research, 45(1), 116–122. https://doi.org/10.1016/j.iatssr.2020.06.003
   Web of Science ®Google Scholar
• Retting, R. A., Ferguson, S. A., & McCartt, A. T. (2003). A review of evidence-based traffic engineering measures designed to reduce pedestrian–motor vehicle crashes. American Journal of Public Health, 93(9), 1456–1463. http://www.acponline.org/hpp/pospaper/andrulis.htm.Accessed https://doi.org/10.2105/ajph.93.9.1456
   PubMed Web of Science ®Google Scholar
• Rundle-Thiele, S., Kubacki, K., Tkaczynski, A., & Parkinson, J. (2015). Using two-step cluster analysis to identify homogeneous physical activity groups. Marketing Intelligence & Planning, 33(4), 522–537. https://doi.org/10.1108/MIP-03-2014-0050
   Web of Science ®Google Scholar
• Saini, H. K., Chouhan, S. S., & Kathuria, A. (2022). Exclusive motorcycle lanes: A systematic review. IATSS Research, 46(3), 411–426. https://doi.org/10.1016/j.iatssr.2022.05.004
   Web of Science ®Google Scholar
• Santosa, S. P., Mahyuddin, A. I., & Sunoto, F. G. (2017). Anatomy of injury severity and fatality in Indonesian traffic accident. Journal of Engineering and Technological Sciences, 49(3), 412–422. https://doi.org/10.5614/j.eng.technol.sci.2017.49.3.9
   Google Scholar
• Savolainen, P., & Mannering, F. (2007). Probabilistic models of motorcyclists’ injury severities in single- and multi-vehicle crashes. Accident Analysis and Prevention, 39(5), 955–963. https://doi.org/10.1016/j.aap.2006.12.016
   PubMed Web of Science ®Google Scholar
• Schneider, W. H., Savolainen, P. T., & Moore, D. N. (2010). Effects of horizontal curvature on single-vehicle motorcycle crashes along rural two-lane highways. Transportation Research Record: Journal of the Transportation Research Board, 2194(1), 91–98. https://doi.org/10.3141/2194-11
   Web of Science ®Google Scholar
• Shinar, D. (2017). Traffic safety and human behavior. Emerald Publishing.
   Google Scholar
• Sivasankaran, S. K., Rangam, H., & Balasubramanian, V. (2021). Investigation of factors contributing to injury severity in single vehicle motorcycle crashes in India. International Journal of Injury Control and Safety Promotion, 28(2), 243–254. https://doi.org/10.1080/17457300.2021.1908367
   PubMed Web of Science ®Google Scholar
• Soehodho, S. (2017). Public transportation development and traffic accident prevention in Indonesia. IATSS Research, 40(2), 76–80. https://doi.org/10.1016/j.iatssr.2014.06.001
   Web of Science ®Google Scholar
• Sun, M., Sun, X., & Shan, D. (2019). Pedestrian crash analysis with latent class clustering method. Accident Analysis and Prevention, 124(November 2018), 50–57. https://doi.org/10.1016/j.aap.2018.12.016
   PubMedGoogle Scholar
• Susilo, Y. O., Joewono, T. B., & Vandebona, U. (2015). Reasons underlying behaviour of motorcyclists disregarding traffic regulations in urban areas of Indonesia. Accident Analysis and Prevention, 75, 272–284. https://doi.org/10.1016/j.aap.2014.12.016
   PubMed Web of Science ®Google Scholar
• Tjahjono, T., Swantika, B., Kusuma, A., Purnomo, R., & Tambun, G. H. (2021). Determinant contributing variables to severity levels of pedestrian crossed the road crashes in three cities in Indonesia. Traffic Injury Prevention, 22(4), 318–323. https://doi.org/10.1080/15389588.2021.1872065
   PubMed Web of Science ®Google Scholar
• Tkaczynski, A. (2017). Segmentation using two-step cluster analysis. In T. Dietrich, S. Rundle-Thiele, & K. Kubacki (Eds.), Segmentation in social marketing process, methods and application. Springer.
   Google Scholar
• Umniyatun, Y., Nurmansyah, M. I., Farradika, Y., Purnama, T. B., & Hidayat, D. N. (2021). Motorcycle risky behaviours and road accidents among adolescents in Jakarta metropolitan area, Indonesia. International Journal of Injury Control and Safety Promotion, 28(3), 339–346. https://doi.org/10.1080/17457300.2021.1928229
   PubMed Web of Science ®Google Scholar
• Vlahogianni, E. I., Yannis, G., & Golias, J. C. (2012). Overview of critical risk factors in power-two-wheeler safety. Accident Analysis and Prevention, 49, 12–22. https://doi.org/10.1016/j.aap.2012.04.009
   PubMed Web of Science ®Google Scholar
• Wedagama, D. M. P., & Dissanayake, D. (2020). A model of latent class multinomial logit to investigate motorcycle accident injuries. Engineering and Applied Science Research, 47(4), 422–429.
   Google Scholar
• Widyaningrum, A., & Siregar, M. L. (2021). Modelling of pedestrian severity factors in traffic accident in Depok. Journal of Physics: Conference Series, 1858(1), 012066. https://doi.org/10.1088/1742-6596/1858/1/012066
   Google Scholar
• World Health Organization. (2015). Global Status Report on Road Safety 2015.
   Google Scholar
• World Health Organization. (2018). Global Status Report on Road Safety 2018.
   Google Scholar
• Yasin, Y. J., Grivna, M., & Abu-Zidan, F. M. (2022). Motorized 2–3 wheelers death rates over a decade: A global study. World Journal of Emergency Surgery: WJES, 17(1), 7. https://doi.org/10.1186/s13017-022-00412-4
   PubMed Web of Science ®Google Scholar
• Yeh, T. H., & Chang, H. L. (2009). Age and contributing factors to unlicensed teen motorcycling. Safety Science, 47(1), 125–130. https://doi.org/10.1016/j.ssci.2008.02.002
   Web of Science ®Google Scholar
• Zegeer, C. V., & Bushell, M. (2012). Pedestrian crash trends and potential countermeasures from around the world. Accident Analysis and Prevention, 44(1), 3–11. https://doi.org/10.1016/j.aap.2010.12.007
   PubMed Web of Science ®Google Scholar