Skip to main content
SpringerLink
Log in

Injury Severity Analysis in Vehicle-Pedestrian Crashes

  • Conference paper
  • First Online:
Advances in Human Aspects of Transportation (AHFE 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 597))

Included in the following conference series:

  • 4750 Accesses

Abstract

Since traffic accident data has been typically collected by the police who record accident information based on estimation through the engineering methods and statements of accident-involved people and witnesses in the vicinity of an accident, accident data recorded by the police may inevitably include errors. However, the technological progression of in-vehicle driving recording devices such as event data recorder, vehicle black box (VBB), and various sensors using in naturalistic driving study tackles the change of methodological paradigms in traffic safety research. The objective of this study is to analyze injury severity in taxi-pedestrian crashes using more accurate crash data by VBBs such as time-to-collision, crash speed, crash angle, and crash region of vehicle and pedestrian. To carry out this study, VBB data for two years (2010–2011) collected by taxies operating in Incheon, Korea are used. Then, the ordered probit model is applied to analyze injury severity in taxi-pedestrian crashes.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 349.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 449.99
Price excludes VAT (USA)
  • Compact, lightweight 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

  1. Chung, Y., et al.: Injury severity in delivery-motorcycle to vehicle crashes in the Seoul metropolitan area. Accid. Anal. Prev. 62, 79–86 (2014)

    Article  Google Scholar 

  2. Loo, B.P.Y.: Validating crash locations for quantitative spatial analysis: a GIS-based approach. Accid. Anal. Prev. 38, 879–886 (2006)

    Article  Google Scholar 

  3. Moes, D.J.A.R.: Optimizing immunosuppression with mTOR inhibitors in renal transplant recipients. Ph.D., Faculty of Science, Leiden University (2014)

    Google Scholar 

  4. Koo, J., et al.: Multithreading embedded multimedia application for vehicle blackbox. In: Gaol, F.L. (ed.) Recent Progress in Data Engineering and Internet Technology, vol. 156, pp. 379–384. Springer, Berlin (2013)

    Chapter  Google Scholar 

  5. Michalaki, P., et al.: A time-series analysis of motorway collisions in England considering road infrastructure, socio-demographics, traffic and weather characteristics. J. Transp. Health 3, 9–20 (2016)

    Article  Google Scholar 

  6. Savolainen, P.T., et al.: The statistical analysis of highway crash-injury severities: a review and assessment of methodological alternatives. Accid. Anal. Prev. 43, 1666–1676 (2011)

    Article  Google Scholar 

  7. Imprialou, M., Quddus, M.: Crash data quality for road safety research: current state and future directions. Accid. Anal. Prev. (In Press)

    Google Scholar 

  8. Chung, Y., Chang, I.: How accurate is accident data in road safety research? An application of vehicle black box data regarding pedestrian-to-taxi accidents in Korea. Accid. Anal. Prev. 84, 1–8 (2015)

    Article  Google Scholar 

  9. Zegeer, C.V., et al.: Analysis of elderly pedestrian accidents and recommended countermeasures. Transp. Res. Rec. 1405, 56–63 (1993)

    Google Scholar 

  10. Fontaine, H., Gourlet, Y.: Fatal pedestrian accidents in France: a typological analysis. Accid. Anal. Prev. 29, 303–312 (1997)

    Article  Google Scholar 

  11. Jensen, S.: Pedestrian safety in Denmark. Transp. Res. Rec. J. Transp. Res. Board 1674, 61–69 (1999)

    Article  Google Scholar 

  12. Kim, J.-K., et al.: Age and pedestrian injury severity in motor-vehicle crashes: a heteroskedastic logit analysis. Accid. Anal. Prev. 40, 1695–1702 (2008)

    Article  Google Scholar 

  13. Damsere-Derry, J., et al.: Pedestrians’ injury patterns in Ghana. Accid. Anal. Prev. 42, 1080–1088 (2010)

    Article  Google Scholar 

  14. Kim, J.-K., et al.: A note on modeling pedestrian-injury severity in motor-vehicle crashes with the mixed logit model. Accid. Anal. Prev. 42, 1751–1758 (2010)

    Article  Google Scholar 

  15. Moudon, A.V., et al.: The risk of pedestrian injury and fatality in collisions with motor vehicles, a social ecological study of state routes and city streets in King County, Washington. Accid. Anal. Prev. 43, 11–24 (2011)

    Article  Google Scholar 

  16. Aziz, H.M.A., et al.: Exploring the determinants of pedestrian–vehicle crash severity in New York City. Accid. Anal. Prev. 50, 1298–1309 (2013)

    Article  Google Scholar 

  17. Mohamed, M.G., et al.: A clustering regression approach: a comprehensive injury severity analysis of pedestrian–vehicle crashes in New York, US and Montreal, Canada. Saf. Sci. 54, 27–37 (2013)

    Article  Google Scholar 

  18. Zhang, G., et al.: Analyzing fault and severity in pedestrian–motor vehicle accidents in China. Accid. Anal. Prev. 73, 141–150 (2014)

    Article  Google Scholar 

  19. Yasmin, S., et al.: Alternative ordered response frameworks for examining pedestrian injury severity in New York City. J. Transp. Saf. Secur. 6, 275–300 (2014). (2014/10/02 )

    Article  Google Scholar 

  20. Koopmans, J.M., et al.: Urban crash-related child pedestrian injury incidence and characteristics associated with injury severity. Accid. Anal. Prev. 77, 127–136 (2015)

    Article  Google Scholar 

  21. Haleem, K., et al.: Analyzing pedestrian crash injury severity at signalized and non-signalized locations. Accid. Anal. Prev. 81, 14–23 (2015)

    Article  Google Scholar 

  22. Oikawa, S., et al.: Relation between vehicle travel velocity and pedestrian injury risk in different age groups for the design of a pedestrian detection system. Saf. Sci. 82, 361–367 (2016)

    Article  Google Scholar 

  23. Pour-Rouholamin, M., Zhou, H.: Investigating the risk factors associated with pedestrian injury severity in Illinois. J. Saf. Res. 57, 9–17 (2016)

    Article  Google Scholar 

  24. Prato, C.G., et al.: Considering built environment and spatial correlation in modelling injury severity for pedestrian crashes. In: 96th Annual Meeting of the Transportation Research Board, Washington D.C. (2017)

    Google Scholar 

  25. Tulu, G.S., et al.: Injury severity of pedestrians involved in road traffic crashes in Addis Ababa, Ethiopia. J. Transp. Saf. Secur. 9, 47–66 (2017). (2017/03/30)

    Article  Google Scholar 

  26. Song, T.-J., et al.: Exploring the vehicle-pedestrian crash severity factors based on the in-car black box recording data. In: 96th Annual Meeting of the Transportation Research Board, Washington D.C. (2017)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Yeungnam University, Gyeongsan, 38541, South Korea

    Younshik Chung

  2. Korea Transport Institute, Sejong, 30147, South Korea

    Tai-Jin Song & Juyoung Kim

Authors
  1. Younshik Chung
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Tai-Jin Song
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Juyoung Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Younshik Chung .

Editor information

Editors and Affiliations

  1. Human Factors Engineering, Transportation Research Group, Boldrewood Innovation Campus, University of Southampton, Southampton, United Kingdom

    Neville A Stanton

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG

About this paper

Cite this paper

Chung, Y., Song, TJ., Kim, J. (2018). Injury Severity Analysis in Vehicle-Pedestrian Crashes. In: Stanton, N. (eds) Advances in Human Aspects of Transportation. AHFE 2017. Advances in Intelligent Systems and Computing, vol 597. Springer, Cham. https://doi.org/10.1007/978-3-319-60441-1_85

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-60441-1_85

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-60440-4

  • Online ISBN: 978-3-319-60441-1

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation