Skip to main content

A Study to Prediction Modeling of the Number of Traffic Accidents

  • Conference paper
  • First Online:
Multimedia and Ubiquitous Engineering

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 240))

  • 875 Accesses

Abstract

Traffic accidents are one of the big problems of modern society. The social damage caused by the traffic accidents are increasing. So, there have been a variety of research analyses to predict the traffic accidents. But there are few studies to predict the frequency of traffic accidents. In this paper, the modeling proposes applying the Markov chain modeling to predict the traffic accidents. In this paper, it is expected that the proposed traffic accident prediction modeling to predict the number of traffic accidents.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 259.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 329.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 329.99
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

  1. Traffic accident statistics. http://taas.koroad.or.kr/index.jsp

  2. Shim K-B (2009) The determination of risk group and severity by traffic accidents types—focusing on Seoul City. J Korea Soc Road Eng 11(2):195–203

    Google Scholar 

  3. Choi Y-H, Oh YT, Choi K, Lee CK, Yun I (2012) Traffic crash prediction models for expressway ramps. J Korea Soc Road Eng 14(5):133–143

    Google Scholar 

  4. Sin G-H, Song Y-J, You Y-G (2011) Ridge road surface frost prediction and monitoring system. J Korea Contents Assoc 11(11):42–48

    Article  Google Scholar 

  5. Grinstead CM (1997) Introduction to probability, 2nd revised edn. American Mathematical Society, Providence, pp 405–406 (in press)

    Google Scholar 

  6. Kim Y-G, Baek Y, Peter In H, Baik D-K (2006) A probabilistic model of damage propagation based on the Markov process. J KIISE 33(8):524–535

    Google Scholar 

  7. Kim Y-J, Park C-S (2008) Prediction of occupant’s presence in residential apartment buildings using Markov chain. Korea Institute of Architectural Sustainable Environment and building System. 2008 autumn conference, pp 116–121

    Google Scholar 

  8. Ha C-S, Han S-Y (2004) Reliability evaluation of AGT vehicle system using Markov chains. 2003 autumn conference and annual meeting of the Korean society for railway, pp 91–96

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Koo-Rock Park .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer Science+Business Media Dordrecht(Outside the USA)

About this paper

Cite this paper

Chung, YS., Kim, JM., Kim, DH., Park, KR. (2013). A Study to Prediction Modeling of the Number of Traffic Accidents. In: Park, J., Ng, JY., Jeong, HY., Waluyo, B. (eds) Multimedia and Ubiquitous Engineering. Lecture Notes in Electrical Engineering, vol 240. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-6738-6_77

Download citation

  • DOI: https://doi.org/10.1007/978-94-007-6738-6_77

  • Published:

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-94-007-6737-9

  • Online ISBN: 978-94-007-6738-6

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics