Skip to main content
SpringerLink
Log in

Overloading Among Crash-Involved Vehicles in China: Identification of Factors Associated with Overloading and Crash Severity

  • Chapter
  • First Online:
Road Safety in China

  • 147 Accesses

Abstract

Objective Motor vehicle overloading is correlated with the possibility of road crash occurrence and severity. Although overloading of motor vehicles is pervasive in developing nations, few empirical analyses have been performed on factors that might influence the occurrence of overloading. This study aims to address this shortcoming by seeking evidence from several years of crash data from Guangdong province, China. Methods Data on overloading and other factors are extracted for crash-involved vehicles from traffic crash records for 2006–2010 provided by the Traffic Management Bureau in Guangdong province. Logistic regression is applied to identify risk factors for overloading in crash-involved vehicles and within these crashes to identify factors contributing to greater crash severity. Driver, vehicle, road and environmental characteristics and violation types are considered in the regression models. In addition to the basic logistic models, association analysis is employed to identify the potential interactions among different risk factors during fitting the logistic models of overloading and severity. Results Crash-involved vehicles driven by males from rural households and in an unsafe condition are more likely to be overloaded and to be involved in higher severity overloaded vehicle crashes. If overloaded vehicles speed, the risk of severe traffic crash casualties increases. Young drivers (aged under 25 years) in mountainous areas are more likely to be involved in higher severity overloaded vehicle crashes. Conclusions This study identifies several factors associated with overloading in crash-involved vehicles and with higher severity overloading crashes and provides an important reference for future research on those specific risk factors.

Reproduced from [Injury Prevention, Zhang, G., Li, Y., King, M. J., & Zhong, Q., 25(1), 36–46, 2019] with permission from BMJ Publishing Group Ltd.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
eBook
USD 16.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 139.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 139.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Agrawal R, Srikant S (1994) Fast algorithms for mining association rules. In: Proceedings of the ACM SIGMOD conference on management of data, pp 487–499

    Google Scholar 

  • Al-Ghamdi AS (2002) Using logistic regression to estimate the influence of accident factors on accident severity. Accid Anal Prev 34:729–741

    Article  Google Scholar 

  • Chang LY, Mannering F (1999) Analysis of injury severity and vehicle occupancy in truck- and non-truck-involved accidents. Accid Anal Prev 31:579–592

    Article  Google Scholar 

  • Changchien SW, Lu T-C (2001) Mining association rules procedure to support on-line recommendation by customers and products fragmentation. Expert Syst Appl 20:325–335

    Article  Google Scholar 

  • Changpetch P, Lin DKJ (2013a) Model selection for logistic regression via association rules analysis. J Stat Comput Simul 83:1415–1428

    Article  Google Scholar 

  • Changpetch P, Lin DKJ (2013b) Selection of multinomial logit models via association rules analysis. Wiley Interdiscip Rev Comput Stat 5:68–77

    Article  Google Scholar 

  • Chen Y, Li Y, King M et al (2016) Identification methods of key contributing factors in crashes with high numbers of fatalities and injuries in China. Traffic Inj Prev 17:878–883

    Article  Google Scholar 

  • Haadi A (2014) Identification of factors that cause severity of road accidents in Ghana: a case study of the Northern Region. Int J Appl Sci Technol 4:242–249

    Google Scholar 

  • Hedman K, Carlsson G (1990) A systematic approach to road safety in developing countries. World Bank, Washington, DC

    Google Scholar 

  • Hijar M, Carrillo C, Flores M et al (2000) Risk factors in highway traffic accidents: a case control study. Accid Anal Prev 32:703–709

    Article  Google Scholar 

  • Hosmer DW Jr, Lemeshow S, Sturdivant RX (2013) Applied logistic regression. Wiley, Hoboken

    Book  Google Scholar 

  • Jacob B, Feypell-de La Beaumelle V (2010) Improving truck safety: potential of weigh-in-motion technology. IATSS Res 34:9–15

    Google Scholar 

  • Jayatilleke AU, Poudel KC, Dharmaratne SD et al (2015) Factors associated with RTCs among for-hire three-wheeler drivers in Sri Lanka: a case-control study. Inj Prev 21:374–380

    Article  Google Scholar 

  • Jun H, Xu H, Pei Y et al (2009) Influencing factors contributing to rear-end collisions on highways: PCA based investigation and findings. In: Proceedings of the ninth international conference of Chinese transportation professionals: American Society of Civil Engineers, pp 1–6

    Google Scholar 

  • Kamei Y, Monden A, Morisaki S et al (2008) A hybrid faulty module prediction using association rule mining and logistic regression analysis. In: Proceedings of the Proceedings of the second ACM-IEEE international symposium on Empirical software engineering and measurement, pp 279–281

    Google Scholar 

  • Karim MR, Ibrahim NI, Saifizul AA et al (2014) Effectiveness of vehicle weight enforcement in a developing country using weigh-in-motion sorting system considering vehicle by-pass and enforcement capability. IATSS Res 37:124–129

    Article  Google Scholar 

  • Khattak A, Schneider R, Targa F (2003) Risk factors in large truck rollovers and injury severity: analysis of single vehicle collisions. TRB 2003 Annual Meeting CD-ROM, Transportation Research Board, National Research Council

    Google Scholar 

  • Khorashadi A, Niemeier D, Shankar V et al (2005) Differences in rural and urban driver-injury severities in accidents involving large-trucks: an exploratory analysis. Accid Anal Prev 37:910–921

    Article  Google Scholar 

  • Laapotti S, Keskinen E (1998) Differences in fatal loss-of-control accidents between young male and female drivers. Accid Anal Prev 30:435–442

    Article  Google Scholar 

  • Li X, Zheng F (2007) Causes for highway overload and analysis of regulatory costs. J Guangxi Univ Nationalities 3:24

    Google Scholar 

  • Lötter H (2001) Road safety performance indicators for developing countries: the case of South Africa. In: Proceedings of the first road transportation technology transfer conference in Africa, pp 256–267

    Google Scholar 

  • MacLeod KE, Griswold JB, Arnold LS et al (2012) Factors associated with hit-and-run pedestrian fatalities and driver identification. Accid Anal Prev 45:366–372

    Article  Google Scholar 

  • Montella A, Aria M, D’Ambrosio A et al (2011) Data-mining techniques for exploratory analysis of pedestrian crashes. Transp Res Rec 2237:107–116

    Article  Google Scholar 

  • Nafukho M (2001) The forgotten workers: the case of public service vehicle drivers in Eldoret Town, Kenya. Organization for Social Science Research in Eastern and Southern Africa, Addis Ababa, Ethiopia

    Google Scholar 

  • Nantulya V, Muli-Musiime F (2001) Kenya: uncovering the social determinants of road traffic accidents. Challenging inequities in health: from ethics to action, Oxford University Press, Oxford [England] and New York, pp 210–225

    Google Scholar 

  • Pande A, Abdel-Aty M (2009) Market basket analysis of crash data from large jurisdictions and its potential as a decision support tool. Saf Sci 47:145–154

    Article  Google Scholar 

  • Pinard MI (2010) Guidelines on vehicle overload control in Eastern and Southern Africa. The World Bank, Sub-Saharan Africa Transport Policy Program, Washington, DC

    Google Scholar 

  • Ponnaluri RV (2012) Road traffic crashes and risk groups in India: analysis, interpretations, and prevention strategies. IATSS Res 35:104–110

    Article  Google Scholar 

  • Raynor NJ, Mirzoev T (2014) Understanding road safety in Kenya: views of matatu drivers. Int Health 6:242–248

    Article  Google Scholar 

  • Shaharanee I, Hadzic F, Dillon T (2009) Interestingness of association rules using symmetrical tau and logistic regression. In: Proceedings of the Australasian joint conference on Artificial Intelligence, pp 422–431

    Google Scholar 

  • Shankar V, Mannering F (1996) An exploratory multinomial logit analysis of single-vehicle motorcycle accident severity. J Safety Res 27:183–194

    Article  Google Scholar 

  • Shinar D, Compton R (2004) Aggressive driving: an observational study of driver, vehicle, and situational variables. Accid Anal Prev 36:429–437

    Article  Google Scholar 

  • Sze NN, Wong SC (2007) Diagnostic analysis of the logistic model for pedestrian injury severity in traffic crashes. Accid Anal Prev 39:1267–1278

    Article  Google Scholar 

  • Taylor B, Bergan A, Lindgren N et al (2000) Heavyweight safety: overweight commercial vehicles are a safety hazard to other motorists and have an inordinate impact on infrastructure. Traffic Technology International: The International Review of Advanced Traffic Management. International Press, Dorking UK, pp 234–237

    Google Scholar 

  • The National People’s Congress of the People’s Republic of China (NPC of PRC) (2014) Law of the People’s Republic of China on Road Traffic Safety, Chinese edn. China Labor and Social Security Publishing House

    Google Scholar 

  • Traffic Management Bureau, Ministry of Public Security, PRC (2013) China road traffic accidents annual statistical report

    Google Scholar 

  • Turner D, Nicholson L (2009) A synthesis of safety implications of oversize/overweight commercial vehicles, 1st edn. University Transportation Center for Alabama Report (07115)

    Google Scholar 

  • Ulfarsson GF, Mannering FL (2004) Differences in male and female injury severities in sport-utility vehicle, minivan, pickup and passenger car accidents. Accid Anal Prev 36:135–147

    Article  Google Scholar 

  • Wang Y, Hasselberg M, Wu Z et al (2008) Distribution and characteristics of road traffic crashes in the Chaoyang District of Beijing. China Accid Anal Prev 40:334–340

    Article  Google Scholar 

  • Watson A, Watson B, Vallmuur K (2015) Estimating under-reporting of road crash injuries to police using multiple linked data collections. Accid Anal Prev 83:18–25

    Article  Google Scholar 

  • Wu W, Zhang Y, Huang M et al (2008) Analysis of risk factors in road traffic injury among motor vehicle drivers. Chinese J Public Health 24:723–724

    Google Scholar 

  • Yakovlev P, Inden M (2010) Mind the weather a panel data analysis of time-invariant factors and traffic fatalities. Econ Bull 30:2685–2696

    Google Scholar 

  • Yang S, Li S, Lu Y (2010) Investigation on dynamical interaction between a heavy vehicle and road pavement. Veh Syst Dyn 48:923–944

    Article  Google Scholar 

  • Zhang G, Yau KK, Chen G (2013) Risk factors associated with traffic violations and accident severity in China. Accid Anal Prev 59:18–25

    Article  Google Scholar 

  • Zhang G, Yau KK, Gong X (2014) Traffic violations in Guangdong Province of China: speeding and drunk driving. Accid Anal Prev 64:30–40

    Article  Google Scholar 

  • Zhang G, Yau KK, Zhang X et al (2016) Traffic accidents involving fatigue driving and their extent of casualties. Accid Anal Prev 87:34–42

    Article  Google Scholar 

  • Zhang H, Wang W (2004) Safety analysis of over-size and over-load in road transport. J Highw Transp Res Dev 3:132–136

    Google Scholar 

  • Zhu X, Srinivasan S (2011) A comprehensive analysis of factors influencing the injury severity of large-truck crashes. Accid Anal Prev 43:49–57

    Article  Google Scholar 

Download references

Funding

This research was supported in part by the National Natural Science Foundation of China grant 71573286. YL received financial support from China Scholarship Council (CSC) for financial support.

Author information

Authors and Affiliations

  1. Center for Studies of Hong Kong, Macao and Pearl River Delta, Institute of Guangdong, Hong Kong and Macao Development Studies, Sun Yat-sen University, Guangzhou, China

    Guangnan Zhang & Qiaoting Zhong

  2. Department of Civil Engineering, Nagoya University, Nagoya, Japan

    Yanyan Li

  3. Queensland University of Technology, Brisbane, QLD, Australia

    Mark J. King

Authors
  1. Guangnan Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yanyan Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Mark J. King
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Qiaoting Zhong
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Qiaoting Zhong .

Editor information

Editors and Affiliations

  1. Center for Studies of Hong Kong, Macao and Pearl River Delta, Institute of Guangdong, Hong Kong and Macao Development Studies, Sun Yat-sen University, Guangzhou, China

    Guangnan Zhang

  2. Center for Studies of Hong Kong, Macao and Pearl River Delta, Institute of Guangdong, Hong Kong and Macao Development Studies, Sun Yat-sen University, Guangzhou, China

    Qiaoting Zhong

Rights and permissions

Reprints and permissions

Copyright information

© 2021 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Zhang, G., Li, Y., King, M.J., Zhong, Q. (2021). Overloading Among Crash-Involved Vehicles in China: Identification of Factors Associated with Overloading and Crash Severity. In: Zhang, G., Zhong, Q. (eds) Road Safety in China. Springer, Singapore. https://doi.org/10.1007/978-981-16-0701-1_7

Download citation

  • DOI: https://doi.org/10.1007/978-981-16-0701-1_7

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-16-0700-4

  • Online ISBN: 978-981-16-0701-1

  • eBook Packages: Social SciencesSocial Sciences (R0)

Publish with us

Policies and ethics

Search

Navigation