Clustering pedestrians’ perceptions towards road infrastructure and traffic characteristics

References

• Aceves-González, C., Ekambaram, K., Rey-Galindo, J., & Rizo-Corona, L. (2020). The role of perceived pedestrian safety on designing safer built environments. Traffic Injury Prevention, 21(sup1), S84–S89. https://doi.org/10.1080/15389588.2020.1812062
   PubMedGoogle Scholar
• Al Bargi, W. A., & Daniel, B. D. (2020). Modelling pedestrians’ utilization of crossing facilities along urban streets. Case Studies on Transport Policy, 8(2), 593–598. https://doi.org/10.1016/j.cstp.2019.12.004
   Web of Science ®Google Scholar
• Antonini, G., Bierlaire, M., & Weber, M. (2006). Discrete choice models of pedestrian walking behavior. Transportation Research Part B: Methodological, 40(8), 667–687. https://doi.org/10.1016/j.trb.2005.09.006
   Web of Science ®Google Scholar
• Arifah, S., & Hidayah, R. (2021). Pedestrian perception based on sidewalk level of convenience at Pemuda Street. IOP Conference Series: Earth and Environmental Science, 832(1), 1–10. https://doi.org/10.1088/1755-1315/832/1/012004
   Google Scholar
• Azık, D., Solmazer, G., Ersan, Ö., Kaçan, B., Fındık, G., Üzümcüoğlu, Y., Özkan, T., Lajunen, T., Öz, B., Pashkevich, A., Pashkevich, M., Danelli-Mylona, V., Georgogianni, D., Berisha Krasniqi, E., Krasniqi, M., Makris, E., Shubenkova, K., & Xheladini, G. (2021). Road users’ evaluations and perceptions of road infrastructure, trip characteristics, and daily trip experiences across countries. Transportation Research Interdisciplinary Perspectives, 11, 100412. https://doi.org/10.1016/j.trip.2021.100412
   Google Scholar
• Basu, N., Haque, M. M., King, M., Kamruzzaman, M., & Oviedo-Trespalacios, O. (2021, July). The unequal gender effects of the suburban built environment on perceptions of security. Journal of Transport & Health, 23, 101243. https://doi.org/10.1016/j.jth.2021.101243
   Web of Science ®Google Scholar
• Bivina, G. R., & Parida, M. (2019). Modelling perceived pedestrian level of service of sidewalks: A structural equation approach. Transport, 34(3), 339–350. https://doi.org/10.3846/transport.2019.9819
   Web of Science ®Google Scholar
• Bruening, D. A., Baird, A. R., Weaver, K. J., & Rasmussen, A. T. (2020, August 8). Whole body kinematic sex differences persist across non-dimensional gait speeds. Plos One, 15(8), e0237449. https://doi.org/10.1371/journal.pone.0237449
   PubMed Web of Science ®Google Scholar
• Cantillo, V., Arellana, J., & Rolong, M. (2015). Modelling pedestrian crossing behaviour in urban roads: A latent variable approach. Transportation Research Part F: Traffic Psychology and Behaviour, 32, 56–67. https://doi.org/10.1016/j.trf.2015.04.008
   Web of Science ®Google Scholar
• Chandrappa, A. K., Bhattacharyya, K., & Maitra, B. (2021). Measures for improving pedestrian crossing facilities based on perceptions of urban commuters: An experience in Kolkata. Case Studies on Transport Policy, 9(2), 965–973. https://doi.org/10.1016/j.cstp.2021.04.017
   Web of Science ®Google Scholar
• Che, M., Wong, Y. D., Lum, K. M., & Wang, X. (2021, September). Interaction behaviour of active mobility users in shared space. Transportation Research Part A: Policy and Practice, 153, 52–65. https://doi.org/10.1016/j.tra.2021.08.017
   Web of Science ®Google Scholar
• Cherry, C., Donlon, B., Yan, X., Moore, S. E., & Xiong, J. (2012). Illegal mid-block pedestrian crossings in China: Gap acceptance, conflict and crossing path analysis. International Journal of Injury Control and Safety Promotion, 19(4), 320–330. https://doi.org/10.1080/17457300.2011.628751
   PubMed Web of Science ®Google Scholar
• Coppola, P., & Silvestri, F. (2020). Assessing travelers’ safety and security perception in railway stations. Case Studies on Transport Policy, 8(4), 1127–1136. https://doi.org/10.1016/j.cstp.2020.05.006
   Web of Science ®Google Scholar
• Davis, S. J., Barton, B. K., Pugliese, B. J., & Lopez, G. (2021). The influences of listening and speaking on pedestrians’ assessments of approaching vehicles. Transportation Research Part F: Traffic Psychology and Behaviour, 82, 348–358. https://doi.org/10.1016/j.trf.2021.09.002
   Web of Science ®Google Scholar
• Eliou, N., Galanis, A., & Proios, A. (2010, April). Pedestrian risk perception in signalized street crossings. WIT Transactions on the Built Environment, 111, 103–111. https://doi.org/10.2495/UT100101
   Google Scholar
• Ezugwu, A. E., Ikotun, A. M., Oyelade, O. O., Abualigah, L., Agushaka, J. O., Eke, C. I., & Akinyelu, A. A. (2022). A comprehensive survey of clustering algorithms: State-of-the-art machine learning applications, taxonomy, challenges, and future research prospects. Engineering Applications of Artificial Intelligence, 110, 104743. https://doi.org/10.1016/j.engappai.2022.104743
   Web of Science ®Google Scholar
• Filomena, G., Manley, E., & Verstegen, J. A. (2020). Perception of urban subdivisions in pedestrian movement simulation. Plos One, 15(12), e0244099–27. https://doi.org/10.1371/journal.pone.0244099
   PubMed Web of Science ®Google Scholar
• Fumagalli, L. A. W., Rezende, D. A., & Guimarães, T. A. (2021). Challenges for public transportation: Consequences and possible alternatives for the Covid-19 pandemic through strategic digital city application. Journal of Urban Management, 10(2), 97–109. https://doi.org/10.1016/j.jum.2021.04.002
   Web of Science ®Google Scholar
• Greene, M., & Ortúzar, J. d D. (2020). Pedestrian safety perception and urban street settings: A comment. International Journal of Sustainable Transportation, 14(12), 914–916. https://doi.org/10.1080/15568318.2019.1668514
   Web of Science ®Google Scholar
• Guo, H., Zhao, F., Wang, W., Zhou, Y., Zhang, Y., & Wets, G. (2014). Modeling the perceptions and preferences of pedestrians on crossing facilities. Discrete Dynamics in Nature and Society, 2014, 1–8. https://doi.org/10.1155/2014/949475
   Web of Science ®Google Scholar
• Gupta, A., Choudhary, P., & Parida, M. (2021, February). Understanding and modelling risky driving behaviour on high-speed corridors. Transportation Research Part F: Traffic Psychology and Behaviour, 82, 359–377. https://doi.org/10.1016/j.trf.2021.09.009
   Web of Science ®Google Scholar
• Han, W., & Zhao, J. (2020). Driver behaviour and traffic accident involvement among professional urban bus drivers in China. Transportation Research Part F: Traffic Psychology and Behaviour, 74, 184–197. https://doi.org/10.1016/j.trf.2020.08.007
   Web of Science ®Google Scholar
• Herrmann-Lunecke, M. G., Mora, R., & Vejares, P. (2021). Perception of the built environment and walking in pericentral neighbourhoods in Santiago, Chile. Travel Behaviour and Society, 23, 192–206. https://doi.org/10.1016/j.tbs.2021.01.002
   Web of Science ®Google Scholar
• Hidayati, I., Tan, W., & Yamu, C. (2020). How gender differences and perceptions of safety shape urban mobility in Southeast Asia. Transportation Research Part F: Traffic Psychology and Behaviour, 73, 155–173. https://doi.org/10.1016/j.trf.2020.06.014
   Web of Science ®Google Scholar
• Jahan, M. I., Mazumdar, A. A. B., Hadiuzzaman, M., Mashrur, S. M., & Murshed, M. N. (2020). Analyzing service quality of pedestrian sidewalks under mixed traffic condition considering latent variables. Journal of Urban Planning and Development, 146(2), 04020011. https://doi.org/10.1061/(ASCE)UP.1943-5444.0000563
   Web of Science ®Google Scholar
• Jolliffe, I. T., & Cadima, J. (2016). Principal component analysis: A review and recent developments. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 374(2065), 20150202. https://doi.org/10.1098/rsta.2015.0202
   PubMed Web of Science ®Google Scholar
• Kadali, B. R., & Vedagiri, P. (2020). Evaluation of pedestrian crossing speed change patterns at unprotected mid-block crosswalks in India. Journal of Traffic and Transportation Engineering (English Edition), 7(6), 832–842. https://doi.org/10.1016/j.jtte.2018.10.010
   Google Scholar
• Kayri, M. (2007). Two-step clustering analysis in researches: A case study. Egitim Arastirmalari-Eurasian Journal of Educational Research, 7(28), 89–99.
   Web of Science ®Google Scholar
• Lambert, J., & Poisson, F. (2001). Valuing benefits of a road traffic noise abatement programme: A contingent valuation survey [Paper presentation]. Proceedings of the 17th International Congress on Acoustics, ICA, Rome, Italy.
   Google Scholar
• Ledesma, R. D., Ferrando, P. J., Trógolo, M. A., Poó, F. M., Tosi, J. D., & Castro, C. (2021). Exploratory factor analysis in transportation research: Current practices and recommendations. Transportation Research Part F: Traffic Psychology and Behaviour, 78, 340–352. https://doi.org/10.1016/j.trf.2021.02.021
   Web of Science ®Google Scholar
• Lee, S., Han, M., Rhee, K., & Bae, B. (2021). Identification of factors affecting pedestrian satisfaction toward land use and street type. Sustainability (Switzerland), 13(19), 10725–10714. https://doi.org/10.3390/su131910725
   Web of Science ®Google Scholar
• Lee, M., Lee, H., Hwang, S., & Choi, M. (2021, July). Understanding the impact of the walking environment on pedestrian perception and comprehension of the situation. Journal of Transport & Health, 23, 101267. https://doi.org/10.1016/j.jth.2021.101267
   Web of Science ®Google Scholar
• Li, G., & Sun, L. (2018). Characterizing heterogeneity in drivers’ merging maneuvers using two-step cluster analysis. Journal of Advanced Transportation, 2018, 1–15. https://doi.org/10.1155/2018/5604375
   Google Scholar
• Majumdar, B. B., Sahu, P. K., Patil, M., & Vendotti, N. (2021). Pedestrian satisfaction-based methodology for prioritization of critical sidewalk and crosswalk attributes influencing walkability. Journal of Urban Planning and Development, 147(3), 04021032. https://doi.org/10.1061/(ASCE)UP.1943-5444.0000718
   Google Scholar
• Marisamynathan, S., & Vedagiri, P. (2019). Pedestrian perception-based level-of-service model at signalized intersection crosswalks. Journal of Modern Transportation, 27(4), 266–281. https://doi.org/10.1007/s40534-019-00196-5
   Web of Science ®Google Scholar
• Maskey, R., Fei, J., & Nguyen, H. O. (2018). Use of exploratory factor analysis in maritime research. The Asian Journal of Shipping and Logistics, 34(2), 91–111. https://doi.org/10.1016/j.ajsl.2018.06.006
   Web of Science ®Google Scholar
• Mateo-Babiano, I. (2016). Pedestrian’s needs matters: Examining Manila’s walking environment. Transport Policy, 45, 107–115. https://doi.org/10.1016/j.tranpol.2015.09.008
   Web of Science ®Google Scholar
• Mavrin, V., Makarova, I., & Prikhodko, A. (2018). Assessment of the influence of the noise level of road transport on the state of the environment. Transportation Research Procedia, 36, 514–519. https://doi.org/10.1016/j.trpro.2018.12.138
   Google Scholar
• Menon, S., Tomy, D., & Kumar, A. (2019). Female work and labor force participation in India: A meta study. United Nations Development Program.
   Google Scholar
• Mishra, S., Sarkar, U., Taraphder, S., Datta, S., Swain, D., Saikhom, R., Panda, S., & Laishram, M. (2017). Multivariate statistical data analysis- principal component analysis (PCA). International Journal of Livestock Research, 7(5), 1. https://doi.org/10.5455/ijlr.20170415115235
   Google Scholar
• Mukherjee, D., & Mitra, S. (2019). Evaluation of pedestrian satisfaction level at signalized intersections in perspective of pedestrian fatality risk: An experience in Kolkata City. India. Journal of the Eastern Asia Society for Transportation Studies, 13(2012), 2049–2072. https://doi.org/10.11175/easts.13.2049
   Google Scholar
• Mukherjee, D., & Mitra, S. (2020). A comprehensive study on factors influencing pedestrian signal violation behaviour: Experience from Kolkata City, India. Safety Science, 124, 104610. https://doi.org/10.1016/j.ssci.2020.104610
   Web of Science ®Google Scholar
• Mukherjee, D., & Mitra, S. (2021, November). Investigating the fatal pedestrian crash occurrence in urban setup in a developing country using multiple-risk source model. Accident; Analysis and Prevention, 163, 106469. https://doi.org/10.1016/j.aap.2021.106469
   PubMed Web of Science ®Google Scholar
• Nag, D., Bhaduri, E., Kumar, G. P., & Goswami, A. K. (2020, September). Assessment of relationships between user satisfaction, physical environment, and user behaviour in pedestrian infrastructure. Transportation Research Procedia, 48, 2343–2363. https://doi.org/10.1016/j.trpro.2020.08.284
   Google Scholar
• Ni, Y., Cao, Y., & Li, K. (2017). Pedestrians’ safety perception at signalized intersections in Shanghai. Transportation Research Procedia, 25, 1955–1963. https://doi.org/10.1016/j.trpro.2017.05.222
   Google Scholar
• Peng, Z., Zhang, H., & Wang, Y. (2021). Work-related factors, fatigue, risky behaviours and traffic accidents among taxi drivers: A comparative analysis among age groups. International Journal of Injury Control and Safety Promotion, 28(1), 58–67. https://doi.org/10.1080/17457300.2020.1837885
   PubMed Web of Science ®Google Scholar
• Pollard, T. M., & Wagnild, J. M. (2017). Gender differences in walking (for leisure, transport and in total) across adult life: A systematic review. BMC Public Health, 17(1), 1–11. https://doi.org/10.1186/s12889-017-4253-4
   PubMedGoogle Scholar
• Rankavat, S., & Tiwari, G. (2016). Pedestrians perceptions for utilization of pedestrian facilities – Delhi, India. Transportation Research Part F: Traffic Psychology and Behaviour, 42, 495–499. https://doi.org/10.1016/j.trf.2016.02.005
   Web of Science ®Google Scholar
• Rossoni, L., Engelbert, R., & Bellegard, N. L. (2016). Normal science and its tools: Reviewing the effects of factor analysis in management. Revista de Administração, 51(2), 198–211. https://doi.org/10.5700/rausp1234
   Google Scholar
• Saxena, A. (2022). Is street design and infrastructure perceived differently by persons of different ages, genders, and hierarchy of street ? Innovative Infrastructure Solutions, 7(4), 278. https://doi.org/10.1007/s41062-022-00880-2
   Google Scholar
• Saxena, A., Gupta, V., & Shrivastava, B. (2021). An assessment of public transport accessibility levels for slums in Bhopal. International Journal of Engineering and Advanced Technology, 10(5), 252–258. https://doi.org/10.35940/ijeat.E2786.0610521
   Google Scholar
• Schneider, A., Krueger, E., Vollenwyder, B., Thurau, J., & Elfering, A. (2021, May). Understanding the relations between crowd density, safety perception and risk-taking behavior on train station platforms: A case study from Switzerland. Transportation Research Interdisciplinary Perspectives, 10, 100390. https://doi.org/10.1016/j.trip.2021.100390
   Google Scholar
• Shahapure, K. R., & Nicholas, C. (2020). Cluster quality analysis using silhouette score [Paper presentation]. Proceedings - 2020 IEEE 7th International Conference on Data Science and Advanced Analytics, DSAA 2020 (pp. 747–748). https://doi.org/10.1109/DSAA49011.2020.00096
   Google Scholar
• Sheykhfard, A., Haghighi, F., Papadimitriou, E., & Van Gelder, P. (2021). Review and assessment of different perspectives of vehicle-pedestrian conflicts and crashes: Passive and active analysis approaches. Journal of Traffic and Transportation Engineering (English Edition), 8(5), 681–702. https://doi.org/10.1016/j.jtte.2021.08.001
   Google Scholar
• Singh, N., Parida, P., Advani, M., & Gujar, R. (2016). Human ellipse of Indian pedestrians. Transportation Research Procedia, 15, 150–160. https://doi.org/10.1016/j.trpro.2016.06.013
   Google Scholar
• Sisiopiku, V. P., & Akin, D. (2003). Pedestrian behaviors at and perceptions towards various pedestrian facilities: An examination based on observation and survey data. Transportation Research Part F: Traffic Psychology and Behaviour, 6(4), 249–274. https://doi.org/10.1016/j.trf.2003.06.001
   Google Scholar
• Soares, F., Silva, E., Pereira, F., Silva, C., Sousa, E., & Freitas, E. (2021). To cross or not to cross: Impact of visual and auditory cues on pedestrians’ crossing decision-making. Transportation Research Part F: Traffic Psychology and Behaviour, 82, 202–220. https://doi.org/10.1016/j.trf.2021.08.014
   Web of Science ®Google Scholar
• Soman, A., Kaur, H., & Ganesan, K. (2019). How urban India moves: Sustainable mobility and citizen preferences. Council on Energy, Environment and Water.
   Google Scholar
• Susanto, T. D., Diani, M. M., & Hafidz, I. (2017). User acceptance of e-government citizen report system (a case study of city113 app). Procedia Computer Science, 124, 560–568. https://doi.org/10.1016/j.procs.2017.12.190
   Google Scholar
• Swärdh, J. E., & Genell, A. (2020). Marginal costs of road noise: Estimation, differentiation and policy implications. Transport Policy, 88, 24–32. https://doi.org/10.1016/j.tranpol.2020.01.009
   Web of Science ®Google Scholar
• Taber, K. S. (2018). The use of Cronbach’s alpha when developing and reporting research instruments in science education. Research in Science Education, 48(6), 1273–1296. https://doi.org/10.1007/s11165-016-9602-2
   Web of Science ®Google Scholar
• Tiwari, G., & Nishant. (2018). Travel to work in India: Current patterns and future concerns. Transportation research and Injury Prevention Programme (TRIPP).
   Google Scholar
• Transport Research Wing, Ministry of Road Transport and Highways, & Government of India. (2020). Road accidents in India 2019. https://morth.nic.in/sites/default/files/RA_Uploading.pdf
   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
• Vallejo-Borda, J. A., Cantillo, V., & Rodriguez-Valencia, A. (2020). A perception-based cognitive map of the pedestrian perceived quality of service on urban sidewalks. Transportation Research Part F: Traffic Psychology and Behaviour, 73, 107–118. https://doi.org/10.1016/j.trf.2020.06.013
   Web of Science ®Google Scholar
• Venkatramanan, S., Prasanna, M. V., & Chung, S. Y. (2019, October). GIS and geostatistical techniques for groundwater science. Elsevier, pp. 1–371. https://doi.org/10.1016/C2017-0-02667-8
   Google Scholar
• Wang, D., Liu, Q., Ma, L., Zhang, Y., & Cong, H. (2019). Road traffic accident severity analysis: A census-based study in China. Journal of Safety Research, 70, 135–147. https://doi.org/10.1016/j.jsr.2019.06.002
   PubMed Web of Science ®Google Scholar
• Wedagama, D. M. P., Bennett, S., & Dissanayake, D. (2020). Analyzing pedestrian perceptions towards traffic safety using discrete choice models. International Journal on Advanced Science, Engineering and Information Technology, 10(6), 2394–2401. https://doi.org/10.18517/ijaseit.10.6.12662
   Google Scholar
• Yahoodik, S., & Yamani, Y. (2021, July). Effectiveness of risk awareness perception training in dynamic simulator scenarios involving salient distractors. Transportation Research Part F: Traffic Psychology and Behaviour, 81, 295–305. https://doi.org/10.1016/j.trf.2021.06.009
   Web of Science ®Google Scholar
• Yilmaz, S., Chambers, J., Cozza, S., & Patel, M. K. (2019). Exploratory study on clustering methods to identify electricity use patterns in building sector. Journal of Physics: Conference Series, 1343(1), 012044–012046. https://doi.org/10.1088/1742-6596/1343/1/012044
   Google Scholar
• Yokoya, Y., & Soma, H. (2021). Visual information of vehicle velocity acquired by pedestrians involved in road crossing accidents. Accident; Analysis and Prevention, 151, 105912. https://doi.org/10.1016/j.aap.2020.105912
   PubMed Web of Science ®Google Scholar
• Zacharias, J. (2001). Pedestrian behavior and perception in urban walking environments. Journal of Planning Literature, 16(1), 3–18. https://doi.org/10.1177/08854120122093249
   Web of Science ®Google Scholar
• Zhou, Z. P., Liu, Y. S., Wang, W., & Zhang, Y. (2013). Multinomial logit model of pedestrian crossing behaviors at signalized intersections. Discrete Dynamics in Nature and Society, 2013, 1–8. https://doi.org/10.1155/2013/172726
   Web of Science ®Google Scholar