[1] Fan Haoxuan, Ren Gang, Li Haojie, Ma Jingfeng, et al. Investigating the factors affecting traffic violations based onelectronic enforcement data: A case study in Shangyu, China [J]. Journal of Southeast University (English Edition), 2021, 37 (2): 227-236. [doi:10.3969/j.issn.1003-7985.2021.02.014]

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Investigating the factors affecting traffic violations based onelectronic enforcement data: A case study in Shangyu, China()

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Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]

Volumn:

37

Issue:

2021 2

Page:

227-236

Research Field:

Traffic and Transportation Engineering

Publishing date:

2021-06-20

Info

Title:

Investigating the factors affecting traffic violations based onelectronic enforcement data: A case study in Shangyu, China

Author(s):

Fan Haoxuan;  Ren Gang;  Li Haojie;  Ma Jingfeng

School of Transportation, Southeast University, Nanjing 211189, China

Keywords:

traffic violations;  road traffic safety;  electronic enforcement data;  multinomial logistic regression;  influencing factors

PACS:

U491.3

DOI:

10.3969/j.issn.1003-7985.2021.02.014

Abstract:

To study the influencing factors of traffic violations, this study investigated the effects of vehicle attribution, day of week, time of day, location of traffic violations, and weather on traffic violations based on the electronic enforcement data and historical weather data obtained in Shangyu, China. Ten categories of traffic violations were determined from the raw data. Then, chi-square tests were used to analyze the relationship between traffic violations and the potential risk factors. Multinomial logistic regression analyses were conducted to further estimate the effects of different risk factors on the likelihood of the occurrence of traffic violations. By analyzing the results of chi-square tests via SPSS, the five factors above were all determined as significant factors associated with traffic violations. The results of the multinomial logistic regression revealed the significant effects of the five factors on the likelihood of the occurrence of corresponding traffic violations. The conclusions are of great significance for the development of effective traffic intervention measures to reduce traffic violations and the improvement of road traffic safety.

References:

[1] World Health Organization. Global status report on road safety 2018[R]. Geneva: WHO, 2018.
[2] National Bureau of Statistics of China. China statistical yearbook[M]. Beijing: China Statistics Press, 2019.(in Chinese)
[3] Traffic Management Research Institute of the Ministry of Public Security. Road accidents white paper[R]. Beijing: Traffic Management Research Institute of the Ministry of Public Security, 2011.(in Chinese)
[4] Rezapour Mashhadi M M, Wulff S S, Ksaibati K. Utilizing crash and violation data to assess unsafe driving actions[J].Journal of Sustainable Development of Transport and Logistics, 2017, 2(2): 35-46. DOI:10.14254/jsdtl.2017.2-2.3.
[5] Zhang G N, Yau K K W, Chen G H. Risk factors associated with traffic violations and accident severity in China[J].Accident Analysis & Prevention, 2013, 59: 18-25. DOI:10.1016/j.aap.2013.05.004.
[6] Peden M M, Scurfield R, Sleet D. World report on road traffic injury prevention[R]. Geneva: World Health Organization, 2004.
[7] Tseng C M. Speeding violations related to a driver’s social-economic demographics and the most frequent driving purpose in Taiwan Province’s male population[J]. Safety Science, 2013, 57: 236-242. DOI:10.1016/j.ssci.2013.02.005.
[8] Oppenheim I, Oron-Gilad T, Parmet Y, et al. Can traffic violations be traced to gender-role, sensation seeking, demographics and driving exposure?[J].Transportation Research Part F: Traffic Psychology and Behaviour, 2016, 43: 387-395. DOI:10.1016/j.trf.2016.06.027.
[9] Zhang G N, Yau K K W, Gong X P. Traffic violations in Guangdong Province of China: Speeding and drunk driving[J].Accident Analysis & Prevention, 2014, 64: 30-40. DOI:10.1016/j.aap.2013.11.002.
[10] Akaateba M A, Amoh-Gyimah R, Amponsah O. Traffic safety violations in relation to drivers’ educational attainment, training and experience in Kumasi, Ghana[J].Safety Science, 2015, 75: 156-162. DOI:10.1016/j.ssci.2015.02.010.
[11] Cheng Z Y, Lu J, Zu Z S, et al. Speeding violation type prediction based on decision tree method: A case study in Wujiang, China[J].Journal of Advanced Transportation, 2019, 2019: 1-10. DOI:10.1155/2019/8650845.
[12] Martínez-Ruíz D M, Fandi�F1;o-Losada A, Ponce de Leon A, et al. Impact evaluation of camera enforcement for traffic violations in Cali, Colombia, 2008—2014[J]. Accident Analysis & Prevention, 2019, 125: 267-274. DOI:10.1016/j.aap.2019.02.002.
[13] Zhang G N, Tan Y, Jou R C. Factors influencing traffic signal violations by car drivers, cyclists, and pedestrians: A case study from Guangdong, China[J]. Transportation Research Part F: Traffic Psychology and Behaviour, 2016, 42: 205-216. DOI:10.1016/j.trf.2016.08.001.
[14] Wang Q, Zhang W, Yang R, et al. Common traffic violations of bus drivers in urban China: An observational study[J]. PLoS One, 2015, 10(9): e0137954. DOI:10.1371/journal.pone.0137954.
[15] Precht L, Keinath A, Krems J F. Identifying the main factors contributing to driving errors and traffic violations—results from naturalistic driving data[J]. Transportation Research Part F: Traffic Psychology and Behaviour, 2017, 49: 49-92. DOI:10.1016/j.trf.2017.06.002.
[16] Fu C Y, Liu H. Investigating influence factors of traffic violations at signalized intersections using data gathered from traffic enforcement camera[J]. PLoS One, 2020, 15(3): e0229653. DOI:10.1371/journal.pone.0229653.
[17] Atombo C, Wu C Z, Zhong M, et al. Investigating the motivational factors influencing drivers intentions to unsafe driving behaviours: Speeding and overtaking violations[J]. Transportation Research Part F: Traffic Psychology and Behaviour, 2016, 43: 104-121. DOI:10.1016/j.trf.2016.09.029.
[18] Tajvar A, Jahangiri M, Aghamolaei T, et al. Investigating self-reported violations of the drivers of Bandar Abbas City and its relation with their knowledge and attitude regarding traffic regulations[J]. Archives of Trauma Research, 2019, 8(4): 219. DOI:10.4103/atr.atr_31_19.
[19] Wang X X, Xu L J, Hao Y P. What factors predict drivers’ self-reported lane change violation behavior at urban intersections? A study in China[J]. PLoS One, 2019, 14(5): e0216751. DOI:10.1371/journal.pone.0216751.
[20] Joewono T B, Susilo Y O. Traffic violations by young motorcyclists on Indonesian urban roads[J].Journal of Transportation Safety & Security, 2017, 9(Sup1): 236-261. DOI:10.1080/19439962.2016.1247123.
[21] Iversen H H, Rundmo T. Changes in Norwegian drivers’ attitudes towards traffic safety and driver behaviour from 2000 to 2008[J]. Transportation Research Part F: Traffic Psychology and Behaviour, 2012, 15(2): 95-100. DOI:10.1016/j.trf.2011.12.006.
[22] Andreuccetti G, Leyton V, Carvalho H B, et al. Drink driving and speeding in Sao Paulo, Brazil: Empirical cross-sectional study(2015—2018)[J]. BMJ Open, 2019, 9(8): e030294. DOI:10.1136/bmjopen-2019-030294.
[23] Tavakoli Kashani A, Amirifar S, Azizi Bondarabadi M. Analysis of driver and vehicle characteristics involved in red-light running crashes: Isfahan, Iran[J]. Iranian Journal of Science and Technology, Transactions of Civil Engineering, 2021, 45(1): 381-387. DOI:10.1007/s40996-020-00453-2.
[24] Al-Atawi A M. Characteristics of red light running violations in urban areas in Tabuk, Kingdom of Saudi Arabia[J]. IATSS Research, 2014, 37(2): 119-123. DOI:10.1016/j.iatssr.2013.08.001.
[25] Zahid M, Chen Y Z, Khan S, et al. Predicting risky and aggressive driving behavior among taxi drivers: Do spatio-temporal attributes matter?[J]. International Journal of Environmental Research and Public Health, 2020, 17(11): 3937. DOI:10.3390/ijerph17113937.
[26] Jin M H, Shriar A J. Exploring the relationship between social capital and individuals’ policy preferences for environmental protection: A multinomial logistic regression analysis[J]. Journal of Environmental Policy & Planning, 2013, 15(3): 427-446. DOI:10.1080/1523908X.2013.769415.
[27] Kwak C, Clayton-Matthews A. Multinomial logistic regression[J].Nursing Research, 2002, 51(6): 404-410. DOI:10.1097/00006199-200211000-00009.
[28] Li X, Zhang M M. SPSS 22.0 statistical analysis from introduction to proficiency[M]. Beijing: Publishing House of Electronics Industry, 2015.(in Chinese)
[29] Wang X S, Yu R J, Zhong C J. A field investigation of red-light-running in Shanghai, China[J].Transportation Research Part F: Traffic Psychology and Behaviour, 2016, 37: 144-153. DOI:10.1016/j.trf.2015.12.010.
[30] Koohpayma J, Tahooni A, Jelokhani-Niaraki M, et al. Spatial analysis of curb-park violations and their relationship with points of interest: A case study of Tehran, Iran[J]. Sustainability, 2019, 11(22): 6336. DOI:10.3390/su11226336.
[31] Nourinejad M, Gandomi A, Roorda M J. Illegal parking and optimal enforcement policies with search friction[J]. Transportation Research Part E: Logistics and Transportation Review, 2020, 141: 102026. DOI:10.1016/j.tre.2020.102026.
[32] Bhalla K, Li Q F, Duan L, et al. The prevalence of speeding and drink driving in two cities in China: A mid project evaluation of ongoing road safety interventions[J]. Injury, 2013, 44: S49-S56. DOI:10.1016/S0020-1383(13)70213-4.
[33] Li Q, He H, Duan L, et al. Prevalence of drink driving and speeding in China: A time series analysis from two cities[J]. Public Health, 2017, 144: S15-S22. DOI:10.1016/j.puhe.2016.11.024.
[34] Ackaah W, Aidoo E N. Modelling risk factors for red light violation in the Kumasi Metropolis, Ghana[J].International Journal of Injury Control and Safety Promotion, 2020, 27(4): 432-437. DOI:10.1080/17457300.2020.1792936.
[35] Li Y X, Abdel-Aty M, Yuan J H, et al. Analyzing traffic violation behavior at urban intersections: A spatio-temporal kernel density estimation approach using automated enforcement system data[J]. Accident Analysis & Prevention, 2020, 141: 105509. DOI:10.1016/j.aap.2020.105509.
[36] Cao Y, Yang Z Z, Zuo Z Y. The effect of curb parking on road capacity and traffic safety[J].European Transport Research Review, 2016, 9(1): 1-10. DOI:10.1007/s12544-016-0219-3.

Memo

Memo:

Biographies: Fan Haoxuan(1997—), male, master; Ren Gang(corresponding author), male, doctor, professor, rengang@seu.edu.cn.
Foundation item: The National Key Research and Development Program of China(No. 2019YFB1600200).
Citation: Fan Haoxuan, Ren Gang, Li Haojie, et al. Investigating the factors affecting traffic violations based on electronic enforcement data: A case study in Shangyu, China[J].Journal of Southeast University(English Edition), 2021, 37(2):227-236.DOI:10.3969/j.issn.1003-7985.2021.02.014.

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