Risk Status Identification of Bus Driving Behavior Based on Clustering Analysis

As the principal part of urban passenger transportation, urban public traffic is closely related to passenger safety. The behavior of bus drivers, who are the most direct participants to bus safety behavior, largely determines the safety level of bus services. It's important to identify risky behavior effectively. This paper extracts seven eigenfactors from four kinds of typical risky behavior (poor driving stability, fatigue driving, poor startup and braking stability, and improper operation at bus station) by analyzing the data provided by the Jinan Public Transportation Company. Risky driving behavior has been identified respectively with the methods of combination clustering analysis and single character clustering analysis. The results show that clustering analysis can effectively identify risky driving behavior and combination analysis has a higher identification rate.


  • English

Media Info

  • Media Type: Web
  • Features: References;
  • Pagination: pp 2576-2585
  • Monograph Title: CICTP 2014: Safe, Smart, and Sustainable Multimodal Transportation Systems

Subject/Index Terms

Filing Info

  • Accession Number: 01531199
  • Record Type: Publication
  • ISBN: 9780784413623
  • Files: TRIS, ASCE
  • Created Date: Jul 2 2014 3:04PM