Behaviour Analysis of Left-Turning Mopeds at Signal Controlled Intersections – A Case Study in Yancheng City

  • Lingxiang Wei Yancheng Institute of Technology, School of Materials Science and Engineering
  • Pengfei Zhao Beijing University of Civil Engineering and Architecture https://orcid.org/0000-0001-7443-5857
  • Yuxuan Li Beijing University of Technology, Beijing Key Laboratory of Traffic Engineering
  • Yinjia Chen Yancheng Institute of Technology, School of Materials Science and Engineering
  • Mingjun Liao Yancheng Institute of Technology, School of Materials Science and Engineering
Keywords: traffic engineering, riding behaviour, left-turning moped traffic flow, signal-controlled intersection

Abstract

Mopeds (electric bicycles and light motorcycles) are commonly used as a personal transportation mode in China. However, the understanding of characteristics of left-turning mopeds at signal-controlled intersections has been relatively limited. To bridge this gap, firstly, this paper proposed a video conversion method of moped movement data acquisition. Then, a method of data accuracy verification was introduced by comparing the results between the field experiment and the video conversion method. Secondly, the ideal traffic space for left-turn mopeds from different entrances was defined to analyse the characteristics of the left-turning mopeds at intersections. Further, three indicators, namely, transverse distance, the proportion of left-turning mopeds with crossing behaviour, and the average number of avoidance behaviour, were proposed and used to analyse the asymmetrical characteristics behaviour, crossing behaviour, and avoidance behaviour. Finally, based on empirical data collected from five signal-controlled intersections, the proposed methods and behaviours were analysed. This paper provides both a valid method of obtaining the position data of mopeds and a reliable basis for improving the safety of left-turning moped riders at urban signal-controlled intersections.

Author Biography

Pengfei Zhao, Beijing University of Civil Engineering and Architecture

Pengfei Zhao received the B.S. degree at Shandong Jiaotong University, Jinan, China, in 2014, and the M.S. and Ph.D. degrees in transportation engineering at Beijing University of Technology, Beijing, China, in 2017 and 2020, respectively. He is currently a postdoctoral research fellow at Beijing University of Civil Engineering and Architecture. His research interests include traffic safety, urban parking, and complex system modeling and optimization.

References

Tal I, Ciubotaru B, Muntean GM. Vehicular-communications-based speed advisory system for electric bicycles. IEEE Transactions on Vehicular Technology. 2016;65(6): 4129-4143. DOI: 10.1109/TVT.2015.2442338

Wei L, et al. Comparison study on travel characteristics between two kinds of electric bike. Procedia - Social and Behavioral Sciences. 2013;96: 1603-1610. DOI: 10.1016/j.sbspro.2013.08.182

Shen JJ, Wang Q, Cao ZM. Correlation model between speed and density of electric bicycles at signalized intersections. Applied Mechanics & Materials. 2015; 744-746: 1803-1807. DOI: 10.4028/www.scientific.net/amm.744-746.1803

Muetze A, Tan Y. Electric bicycles - A performance evaluation. Industry Applications Magazine IEEE. 2007;13(4): 12-21. DOI: 10.1109/mia.2007.4283505

Yan X, et al. Electric bicycle cost calculation models and analysis based on the social perspective in China. Environmental Science & Pollution Research. 2018;25(20): 20193-20205. DOI: 10.1007/s11356-018-2150-8

Jones T, Harms L, Heinen E. Motives perceptions and experiences of electric bicycle owners and implications for health, wellbeing and mobility. Journal of Transport Geography. 2016;53: 41-49. DOI: 10.1016/j.jtrangeo.2016.04.006

Tiefang Z, et al. Injury source and correlation analysis of riders in car-electric bicycle accidents. Applied Bionics and Biomechanics. 2018;(2018): 1-15. DOI: 10.1155/2018/3674858

Petzoldt T, et al. Traffic conflicts and their contextual factors when riding conventional vs. electric bicycles. Transportation Research Part F: Traffic Psychology and Behaviour. 2017;46: 477-490. DOI: 10.1016/j.trf.2016.06.010

Feng Z, et al. Electric-bicycle-related injury: A rising traffic injury burden in China. Injury Prevention Journal of the International Society for Child & Adolescent Injury Prevention. 2010;16(6): 417-419. DOI: 10.1136/ip.2009.024646

Chodur J, Ostrowski K, Tracz M. Variability of capacity and traffic performance at urban and rural signalised intersections. Transportation Research Procedia. 2016;15: 87-99. DOI: 10.1016/j.trpro.2016.06.008

Castillo-Manzano JI, Castronuño M, Fageda X. Exploring the relationship between truck load capacity and traffic accidents in the European Union. Transportation Research Part E. 2016;88: 94-109. DOI: 10.1016/j.tre.2016.02.003

Zwahlen D, Jackowski C, Pfäffli M. Sleepiness, driving, and motorcycle accidents: A questionnaire-based survey. Journal of Forensic & Legal Medicine. 2016;44: 183-187. DOI: 10.1016/j.jflm.2016.10.014

Yang Q, et al. Analytical evaluation of the use of left-turn phasing for single left-turn lane only. Transportation Research Part B: Methodological. 2018;111: 266-303. DOI: 10.1016/j.trb.2018.03.013

Borrell B. The bicycle problem that nearly broke mathematics. Nature. 2016;535(7612): 338-341. DOI: 10.1038/535338a

Bai L, et al. Comparative analysis of risky behaviours of electric bicycles at signalized intersections. Journal of Crash Prevention & Injury Control. 2015;16(4): 424-428. DOI: 10.1080/15389588.2014.952724

Rubin G, et al. Upper extremity open fractures in hospitalized road traffic accident patients: Adult versus pediatric cases. Journal of Orthopaedic Surgery & Research. 2017;12(1): 1-5. DOI: 10.1186/s13018-017-0657-1

Mellino S, et al. A life cycle assessment of lithium battery and hydrogen-FC powered electric bicycles: Searching for cleaner solutions to urban mobility. International Journal of Hydrogen Energy. 2017;42(3): 1830-1840. DOI: 10.1016/j.ijhydene.2016.10.146

Kerdsup B, Fuengwarodsakul NH. Performance and cost comparison of reluctance motors used for electric bicycles. Electrical Engineering. 2017;99(2): 475-486. DOI: 10.1007/s00202-016-0373-6

Duan LL, Ye PP, Wang LH. Future challenges and solutions for safety in China: China CDC’s exploration of injury prevention strategies. Global Health Journal. 2018;2(2): 14-23. DOI: 10.1016/s2414-6447(19)30135-6

Gao W, et al. A study on cyclist head injuries based on an electric-bicycle to car accident reconstruction. Traffic Injury Prevention. 2020;21(8): 563-568. DOI: 10.1080/15389588.2020.1821882

Leo C, et al. Analysis of Swedish and Dutch accident data on cyclist injuries in cyclist-car collisions. Traffic Injury Prevention. 2019;20(2): 1-3. DOI: 10.1080/15389588.2019.1679551

Heylen D, et al. Ticks and tick-borne diseases in the city: Role of landscape connectivity and green space characteristics in a metropolitan area. The Science of the Total Environment. 2019;670(20): 941-949. DOI: 10.1016/j.scitotenv.2019.03.235

Juremalani J, Chauhan KA. Urbanization challenges in emerging economies. Energy and water infrastructure, transportation infrastructure, and planning and financing. ASCE India Conference, 12-14 December 2017, New Delhi, India. American Society of Civil Engineers; 2018. p. 688-696. Available from: https://searchworks.stanford.edu/view/13091641

Wang Y, et al. Research on non-motorcycle traffic space optimization at signal control intersections. The 3rd IEEE International Conference on Control Science and Systems Engineering (ICCSSE), 17-19 August 2017, Beijing, China. China Agricultural University; 2017. p. 766-769.

Damsere-Derry J, Bawa S. Bicyclists' accident pattern in Northern Ghana. IATSS Research. 2017;42(3): 1-5. DOI: 10.1016/j.iatssr.2017.10.002

Lee H, et al. A study on cyclist accident analysis on Korea roads with typology of iGLAD. Journal of Auto-vehicle Safety Association. 2018;10(1): 27-31.

Otte D, Facius T. Accident typology comparisons between pedelecs and conventional bicycles. Journal of Transportation Safety & Security. 2020;12(1): 116-135.

Ou H, et al. Electric bicycle management and control at a signalized intersection. Physica A: Statistical Mechanics and its Applications. 2018;512: 1000-1008. DOI: 10.1016/j.physa.2018.06.116

Liu M, Liu Y. Analyses and improvement options on road safety issues in Beijing. 2018 International Conference on Transportation & Logistics, Information & Communication, Smart City (TLICSC 2018), 30-31 October 2018, Chengdu City, China. Wuhan University of Technology; 2018. p. 382-386.

Cherry C, Cervero R. Use characteristics and mode choice behaviour of electric bike users in China. Transport Policy. 2007;14(3): 247-257. DOI: 10.1016/j.tranpol.2007.02.005

Fishman E, Cherry C. E-bikes in the Mainstream: Reviewing a Decade of Research. Transport Reviews. 2016;36(1): 72-91. DOI: 10.1080/01441647.2015.1069907

Rose G. E-bikes and urban transportation: Emerging issues and unresolved questions. Transportation. 2011;39(1): 81-96. DOI: 10.1007/s11116-011-9328-y

Wells P, Lin X. Spontaneous emergence versus technology management in sustainable mobility transitions: Electric bicycles in China. Transportation Research Part A. 2015;78: 371-383. DOI: 10.1016/j.tra.2015.05.022

Kuhnert PM, Do KA. Mcclure R. Combining non-parametric models with logistic regression: An application to motorcycle injury data. Computational Statistics & Data Analysis. 2000;34(3): 371-386. DOI: 10.1016/S0167-9473(99)00099-7

Yao L, Wu C. Traffic safety for electric bike riders in China: Attitudes, risk perception, and aberrant riding behaviours. Transportation Research Record: Journal of the Transportation Research Board. 2012;2314(1): 49-56. DOI: 10.3141/2314-07

Dozza M, Fernandez A. Understanding bicycle dynamics and cyclist behaviour from naturalistic field data (November 2012). IEEE Transactions on Intelligent Transportation Systems. 2014;15(1): 376-384. DOI: 10.1109/TITS.2013.2279687

Jin S, et al. Estimating cycleway capacity and bicycle equivalent unit for electric bicycles. Transportation Research Part A: Policy and Practice. 2015;77: 225-248. DOI: 10.1016/j.tra.2015.04.013

Wang XR, Han BR. Logistic regression analysis and nursing interventions for high-risk factors for pressure sores in patients in a surgical intensive care unit. Chinese Nursing Research. 2015;2(2-3): 51-54. DOI: 10.1016/j.cnre.2015.04.004

Han P. Multiply robust estimation in regression analysis with missing data. Journal of the American Statistical Association. 2014;109(507): 1159-1173. DOI: 10.1080/01621459.2014.880058

Tang K, et al. Behavior of Riders of Electric Bicycles at Onset of Green and Yellow at Signalized Intersections in China. Transportation Research Record: Journal of the Transportation Research Board. 2012;2317(1): 85-96. DOI: 10.3141/2317-11

Popovich N, et al. Experiences of electric bicycle users in the Sacramento, California area. Travel Behaviour & Society. 2014;1(2): 37-44. DOI: 10.1016/j.tbs.2013.10.006

Published
2021-08-05
How to Cite
1.
Wei L, Zhao P, Li Y, Chen Y, Liao M. Behaviour Analysis of Left-Turning Mopeds at Signal Controlled Intersections – A Case Study in Yancheng City. Promet - Traffic&Transportation. 2021;33(4):609-20. DOI: 10.7307/ptt.v33i4.3740
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Articles