Exploring factors associated with red-light running: a case study of Hanoi city
Email:
dungchu@utc.edu.vn
Từ khóa:
red-light running, signalized intersections, ordered probit model, motorcycle, traffic crash.
Tóm tắt
Red-light running (RLR) is the most significant factor involved in traffic crashes and injuries at signalized intersections. In Vietnam, little knowledge of factors affecting RLR has been found. This paper applied an ordered probit model to investigate factors associated with RLR using questionnaire data collected in Hanoi. Generally, this paper found that males and motorcyclists have a higher likelihood of RLR than females and car drivers. In addition, the younger and lower-income road users and the ones who are businessmen and who have a commuting trip in off-peak hours are more likely to run the red light. By contrast, the road users who go to school and the people who understand traffic law are less likely to violate the red light. In the future, it is necessary to collect data in different cities to generalize the results. In addition, may need to apply a more powerful method such as the latent class model, which can discover hidden facts among respondents. In the new model, other factors such as weather, waiting time, and countdown signal will be considered to investigate their effects on RLR.Tài liệu tham khảo
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[2]. F. Yan, B. Li, W. Zhang, G. Hu, Red-light running rates at five intersections by road user in Changsha, China: An observational study, Accident Analysis & Prevention, 95 (2016) 381-386. https://doi.org/10.1016/j.aap.2015.06.006
[3]. A. Jensupakarn, K. Kanitpong, Influences of motorcycle rider and driver characteristics and road environment on red light running behavior at signalized intersections, Accident Analysis & Prevention, 113 (2018) 317-324. https://doi.org/10.1016/j.aap.2018.02.007
[4]. R.A. Retting, R.G. Ulmer, A.F. Williams, Prevalence and characteristics of red light running crashes in the United States. Accident Analysis & Prevention, 31 (1999) 687-694. https://doi.org/10.1016/S0001-4575(99)00029-9
[5]. R. A. Retting, A. F. Williams, D. F. Preusser, H. B. Weinstein, Classifying urban crashes for countermeasure development, Accident Analysis and Prevention, 27 (1995) 283–294. https://doi.org/10.1016/0001-4575(94)00068-W
[6]. N. Brittany, B. N. Campbell, J. D. Smith, W. G. Najm, 2004, Analysis of fatal crashes due to signal and stop sign violations, Report No. DOT HS- 809-779, National Highway Traffic Safety Administration, Washington, DC.
[7]. Insurance Institute for Highway Safety, Red light running. https://www.iihs.org/topics/red-light-running, (accessed 13 July 2020).
[8]. World Health Organization, 2018, Global status report on road safety 2018: Summary (No. WHO/NMH/NVI/18.20), World Health Organization.
[9]. General statistics office of Viet Nam, Socio-economic situation in the first 5 months of 2020. https://bit.ly/382A6o5, (accessed 13 July 2020).
[10]. A. M. Al-Atawi, Characteristics of red light running violations in urban areas in Tabuk, Kingdom of Saudi Arabia, IATSS research, 37 (2014) 119-123. https://doi.org/10.1016/j.iatssr.2013.08.001
[11]. X. Wang, R. Yu, C. Zhong, A field investigation of red-light-running in Shanghai, China, Transportation research part F: traffic psychology and behaviour, 37 (2016) 144-153. https://doi.org/10.1016/j.trf.2015.12.010
[12]. P. L. Chen, C. W. Pai, R. C. Jou, W. Saleh, M. S. Kuo, Exploring motorcycle red-light violation in response to pedestrian green signal countdown device, Accident Analysis & Prevention, 75 (2015) 128-136. https://doi.org/10.1016/j.aap.2014.11.016
[13]. C.D. Yang, W.G. Najm, Examining driver behavior using data gathered from red light photo enforcement cameras, Journal of safety research, 38 (2007) 311-321. https://doi.org/10.1016/j.jsr.2007.01.008
[14]. B.E. Porter, T.D. Berry, A nationwide survey of self-reported red light running: measuring prevalence, predictors, and perceived consequences, Accident Analysis & Prevention, 33 (2001) 735-741. https://doi.org/10.1016/S0001-4575(00)00087-7
[15]. P. Chen, G. Yu, X. Wu, Y. Ren, Y. Li, Estimation of red-light running frequency using high-resolution traffic and signal data, Accident Analysis and Prevention, 102 (2017) 235–247. https://doi.org/10.1016/j.aap.2017.03.010
[16]. J.A. Bonneson, K.H. Zimmerman, Effect of yellow-interval timing on the frequency of red-light violations at urban intersections, Transportation Research Record, 1865 (2004) 20-27. https://doi.org/10.3141/1865-04
[17]. R.A. Retting, S.A. Ferguson, C.M. Farmer, Reducing red light running through longer yellow signal timing and red light camera enforcement: results of a field investigation, Accident Analysis & Prevention, 40 (2008) 327-333. https://doi.org/10.1016/j.aap.2007.06.011
[18]. K. Long, L.D. Han, Q. Yang, Effects of countdown timers on driver behavior after the yellow onset at Chinese intersections, Traffic injury prevention, 12 (2011) 538-544. https://doi.org/10.1080/15389588.2011.593010
[19]. X. C. Vuong, R.-F. Mou, H. S. Nguyen, T. T. Vu, Red Light Running of Motorcycles at Signalized Intersections in Vietnam: Influential Factors and Countermeasures, Proceeding of the 2018 International Conference on Building Smart Cities in Vietnam: Vision and Solutions, 2018.
[20]. T. D. Chu, T. A. Bui, A study on red-light running in Hanoi based on questionnaire survey, Proceeding of ICSCE 2020 - The 3rd International Conference on Sustainability in Civil Engineering, 2020.
[21]. V. H. Mai, T. D. Chu, Q. H. Vu, Investigating Signal Violations in Mixed Traffic in Hanoi City, Proceedings of the Eastern Asia Society for Transportation Studies, 2019.
[22]. Q. V. Tran, A. T. Vu, Analysis of traffic accidents at signalized intersections, Proceeding of 7th ATRANS symposium: young researcher’s forum 2014 “Transportation for a Better Life: Towards Better ASEAN Connectivity and Safety”, 2014.
[23]. W. H. Greene, D. A. Hensher, Modeling ordered choices: A primer, Cambridge University Press, 2010.
[24]. O. Torres-Reyna, Getting started in Logit and ordered logit regression, Princeton University, 2010. https://www.princeton.edu/~otorres/Logit.pdf
[25]. D. McFadden, Quantitative Methods for Analyzing Travel Behaviour of Individuals: Some Recent Developments, No 474, Cowles Foundation Discussion Papers, Cowles Foundation for Research in Economics, Yale University, 1977. https://ideas.repec.org/p/cwl/cwldpp/474.html
Tải xuống
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Nhận bài
04/06/2021
Nhận bài sửa
25/08/2021
Chấp nhận đăng
05/09/2021
Xuất bản
15/09/2021
Chuyên mục
Công trình khoa học
Kiểu trích dẫn
Chu Tien, D. (1631638800). Exploring factors associated with red-light running: a case study of Hanoi city. Tạp Chí Khoa Học Giao Thông Vận Tải, 72(7), 800-810. https://doi.org/10.47869/tcsj.72.7.3
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