IDEAS home Printed from https://ideas.repec.org/p/cdl/itsrrp/qt6sg5c0ng.html
   My bibliography  Save this paper

Experimental Evaluation of the Continuous Risk Profile (CRP) Approach to the Current Caltrans Methodology for High Collision Concentration Location Identification

Author

Listed:
  • Grembek, Offer
  • Kim, Kwangho
  • Kwon, Oh Hoon
  • Lee, Jinwoo
  • Liu, Haotian
  • Park, Min Ju
  • Washington, Simon
  • Ragland, David
  • Madanat, Samer M.

Abstract

This report evaluates the performance of Continuous Risk Profile (CRP) compared with the Sliding Window Method (SWM) and Peak Searching (PS) methods. These three network screening methods all require the same inputs: traffic collision data and Safety Performance Functions (SPFs), however, depending on how these input parameters are analyzed at the network screening level, the result of the analysis can vary significantly. Findings indicated that the CRP method produced far fewer false positives than SWM and PS. The false negative rates for CRP, SWM and PS were comparable. These findings indicate that by using the CRP method, California Department of Transportation (Caltrans) can significantly reduce the resources spent on investigating falsely identified locations and better utilize the resources in improving high collision concentration locations. It will also help Caltrans in reducing the backlog in Caltrans Table C.

Suggested Citation

  • Grembek, Offer & Kim, Kwangho & Kwon, Oh Hoon & Lee, Jinwoo & Liu, Haotian & Park, Min Ju & Washington, Simon & Ragland, David & Madanat, Samer M., 2012. "Experimental Evaluation of the Continuous Risk Profile (CRP) Approach to the Current Caltrans Methodology for High Collision Concentration Location Identification," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt6sg5c0ng, Institute of Transportation Studies, UC Berkeley.
    • Handle: RePEc:cdl:itsrrp:qt6sg5c0ng
    as

    Download full text from publisher

    File URL: https://www.escholarship.org/uc/item/6sg5c0ng.pdf;origin=repeccitec
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Koohong Chung & David R. Ragland, 2009. "The Continuous Risk Profile Approach for the Identification of High Collision Concentration Locations on Congested Highways," Springer Books, in: William H. K. Lam & S. C. Wong & Hong K. Lo (ed.), Transportation and Traffic Theory 2009: Golden Jubilee, chapter 0, pages 463-480, Springer.
    2. Chung, Koohong & Ragland, David R. & Madanat, Samer & Oh, Soon Mi, 2009. "The Continuous Risk Profile Approach for the Identification of High Collision Concentration Locations on Congested Highways," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt24m8j57d, Institute of Transportation Studies, UC Berkeley.
    3. Chung, Koohong & Jang, Kitae & Madanat, Samer & Washington, Simon, 2011. "Proactive detection of high collision concentration locations on highways," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(9), pages 927-934, November.
    4. Chung, Koohong & Rudjanakanoknad, Jittichai & Cassidy, Michael J., 2007. "Relation between traffic density and capacity drop at three freeway bottlenecks," Transportation Research Part B: Methodological, Elsevier, vol. 41(1), pages 82-95, January.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Eui-Jin Kim & Oh Hoon Kwon & Shin Hyoung Park & Dong-Kyu Kim & Koohong Chung, 2021. "Application of naïve Bayesian approach in detecting reproducible fatal collision locations on freeway," PLOS ONE, Public Library of Science, vol. 16(5), pages 1-21, May.
    2. Chung, Koohong & Jang, Kitae & Madanat, Samer & Washington, Simon, 2011. "Proactive detection of high collision concentration locations on highways," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(9), pages 927-934, November.
    3. Medury, Aditya & Grembek, Offer, 2014. "Dynamic Programming-based Pedestrian Hotspot Identification Approach," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt10d0x1z7, Institute of Transportation Studies, UC Berkeley.
    4. Elyasi, Mohammad Reza & Saffarzade, Mahmoud & Boroujerdian, Amin Mirza, 2016. "A novel dynamic segmentation model for identification and prioritization of black spots based on the pattern of potential for safety improvement," Transportation Research Part A: Policy and Practice, Elsevier, vol. 91(C), pages 346-357.
    5. Herrera, Juan C. & Bayen, Alexandre M., 2010. "Incorporation of Lagrangian measurements in freeway traffic state estimation," Transportation Research Part B: Methodological, Elsevier, vol. 44(4), pages 460-481, May.
    6. Richard Andrášik & Michal Bíl, 2016. "Efficient road geometry identification from digital vector data," Journal of Geographical Systems, Springer, vol. 18(3), pages 249-264, July.
    7. Chen, Danjue & Ahn, Soyoung, 2018. "Capacity-drop at extended bottlenecks: Merge, diverge, and weave," Transportation Research Part B: Methodological, Elsevier, vol. 108(C), pages 1-20.
    8. Richard Arnott & Anatolii Kokoza & Mehdi Naji, 2015. "A Model of Rush-Hour Traffic in an Isotropic Downtown Area," Working Papers 201511, University of California at Riverside, Department of Economics.
    9. Ancuta Fedorca & Mihai Fedorca & Ovidiu Ionescu & Ramon Jurj & Georgeta Ionescu & Marius Popa, 2021. "Sustainable Landscape Planning to Mitigate Wildlife–Vehicle Collisions," Land, MDPI, vol. 10(7), pages 1-13, July.
    10. Cassidy, Michael J. & Daganzo, Carlos F. & Jang, Kitae & Chung, Koohong, 2006. "Empirical Reassessment of Traffic Operations: Freeway Bottlenecks and the Case for HOV Lanes," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt31h8z81t, Institute of Transportation Studies, UC Berkeley.
    11. Oh, Simon & Yeo, Hwasoo, 2015. "Impact of stop-and-go waves and lane changes on discharge rate in recovery flow," Transportation Research Part B: Methodological, Elsevier, vol. 77(C), pages 88-102.
    12. Liu, Wei & Yin, Yafeng & Yang, Hai, 2015. "Effectiveness of variable speed limits considering commuters’ long-term response," Transportation Research Part B: Methodological, Elsevier, vol. 81(P2), pages 498-519.
    13. Huang, Zichao & Wu, Qing & Ma, Jie & Fan, Shiqi, 2016. "An APF and MPC combined collaborative driving controller using vehicular communication technologies," Chaos, Solitons & Fractals, Elsevier, vol. 89(C), pages 232-242.
    14. Yeo, Hwasoo, 2008. "Asymmetric Microscopic Driving Behavior Theory," University of California Transportation Center, Working Papers qt1tn1m968, University of California Transportation Center.
    15. Faryal Ali & Zawar Hussain Khan & Khurram Shehzad Khattak & Thomas Aaron Gulliver & Akhtar Nawaz Khan, 2022. "A Microscopic Heterogeneous Traffic Flow Model Considering Distance Headway," Mathematics, MDPI, vol. 11(1), pages 1-20, December.
    16. Jin, Wen-Long, 2013. "A multi-commodity Lighthill–Whitham–Richards model of lane-changing traffic flow," Transportation Research Part B: Methodological, Elsevier, vol. 57(C), pages 361-377.
    17. Xing-jian Xue & Feng Shi & Qun Chen, 2014. "Capacity Estimation for On-Ramp Merging Section of Urban Expressway Based on Time Headway Loss," Discrete Dynamics in Nature and Society, Hindawi, vol. 2014, pages 1-9, February.
    18. Nima Dadashzadeh & Murat Ergun, 2019. "An Integrated Variable Speed Limit and ALINEA Ramp Metering Model in the Presence of High Bus Volume," Sustainability, MDPI, vol. 11(22), pages 1-26, November.
    19. Zheng, Shi-Teng & Jiang, Rui & Tian, Jun-Fang & Zhang, H.M. & Li, Zhen-Hua & Gao, Lan-Da & Jia, Bin, 2021. "Experimental study on properties of lightly congested flow," Transportation Research Part B: Methodological, Elsevier, vol. 149(C), pages 1-19.
    20. Jin, Wen-Long, 2017. "A first-order behavioral model of capacity drop," Transportation Research Part B: Methodological, Elsevier, vol. 105(C), pages 438-457.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:cdl:itsrrp:qt6sg5c0ng. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Lisa Schiff (email available below). General contact details of provider: https://edirc.repec.org/data/itucbus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.