Behaviour Analysis of Left-Turning Mopeds at Signal Controlled Intersections – A Case Study in Yancheng City
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.
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
Copyright (c) 2021 Lingxiang Wei, Pengfei Zhao, Yuxuan Li, Yinjia Chen, Mingjun Liao
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).