A Methodology for Freeway Incident Duration Prediction Using Computerized Historical Database

This paper collected incident data from Ning-Tong (NT) freeway in Jiangsu province of China, and divided them into two categories: one was traffic accident data, the other was vehicle assistance data. Distribution estimation results indicated that traffic accident data obeyed log-normal distribution and log-logistic distribution, and vehicle assistance data obeyed logistic distribution after a Box-Cox transformation. A linear model was then constructed for traffic accident data by a stepwise regression approach. The obtained linear model could provide a preliminary prediction of incident duration when limited information about the incident is known. A methodology using historical incident database was then proposed to give updated predictions as the incident lasts. Two models, the linear one and the proposed one, were compared by case studies. It reveals that the former one provides rough and static predictions while the latter one gives more precise and dynamic predictions.

• Record URL:
  https://doi.org/10.1061/9780784412442.351
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/isbn/9780784412442
• Supplemental Notes:
  • © 2012 American Society of Civil Engineers.
• Corporate Authors:

  American Society of Civil Engineers

  1801 Alexander Bell Drive
  Reston, VA  United States  20191-4400
• Authors:
  • Yu, Bin
  • Xia, Zhengfeng
• Conference:
  • Twelfth COTA International Conference of Transportation Professionals
  • Location: Beijing , China
  • Date: 2012-8-3 to 2012-8-6
• Publication Date: 2012-8

Language

• English

Media Info

• Media Type: Web
• Features: Figures; References; Tables;
• Pagination: pp 3463-3474
• Monograph Title: CICTP 2012: Multimodal Transportation Systems—Convenient, Safe, Cost-Effective, Efficient

Subject/Index Terms

• TRT Terms: Data analysis; Freeway operations; Incident management; Mathematical prediction; Time duration; Traffic incidents
• Geographic Terms: Jiangsu Province (China)
• Subject Areas: Data and Information Technology; Highways; Operations and Traffic Management; Planning and Forecasting; I72: Traffic and Transport Planning;

Filing Info

• Accession Number: 01521723
• Record Type: Publication
• ISBN: 9780784412442
• Files: TRIS, ASCE
• Created Date: Apr 8 2014 9:01AM