Aggressiveness Propensity Index for Driving Behavior at Signalized Intersections
This paper develops a quantitative intersection aggressiveness propensity index (API) intended to capture a signalized intersection’s overall propensity to experience aggressive driving. The index is a latent quantity that can be estimated from observed environmental, situational and driving behavior variables using structural equations modeling techniques. An empirical study of ten major signalized intersections in the greater Washington DC metropolitan area is conducted to illustrate the approach. The API is shown to provide (a) an approach for capturing and quantifying aggressive driving behavior given certain measurements taken at a particular intersection, (b) understanding of the factors and intersection characteristics that may affect aggressiveness, and (c) an index for the cross comparison of different traffic areas with different features, as well as to support safety policy analysis and decision-making.
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Corporate Authors:
500 Fifth Street, NW
Washington, DC United States 20001 -
Authors:
- Hamdar, Samer
- Mahmassani, Hani S
- Chen, Roger B
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Conference:
- Transportation Research Board 86th Annual Meeting
- Location: Washington DC, United States
- Date: 2007-1-21 to 2007-1-25
- Date: 2007
Language
- English
Media Info
- Media Type: CD-ROM
- Features: Figures; References; Tables;
- Pagination: 23p
- Monograph Title: TRB 86th Annual Meeting Compendium of Papers CD-ROM
Subject/Index Terms
- TRT Terms: Aggression; Behavior; Decision making; Highway operations; Operations; Policy analysis; Signalized intersections
- Geographic Terms: Washington (District of Columbia)
- Subject Areas: Administration and Management; Highways; Operations and Traffic Management; Planning and Forecasting; Policy; Safety and Human Factors; I72: Traffic and Transport Planning; I83: Accidents and the Human Factor;
Filing Info
- Accession Number: 01049297
- Record Type: Publication
- Report/Paper Numbers: 07-1995
- Files: TRIS, TRB
- Created Date: Feb 8 2007 6:42PM