The Impact of Motion Prediction Methods on Surrogate Safety Analysis: A Case Study of Left-Turn and Opposite-Direction Interactions at a Signalized Intersection in Montreal

Surrogate safety analysis is a proactive approach that relies on the observation of traffic events without a collision. To measure the proximity to collision, several safety indicators have been proposed in the literature. Most indicators like time to collision (TTC) rely on the choice of a motion prediction method such as the rarely justified prediction at constant velocity. Moreover, most current interpretations of continuous safety indicators use only a single value to qualify the whole interaction, for example, the minimum TTC. The objective of this article is to investigate the impact of motion prediction methods on safety indicators and the interpretation methods of these indicators for safety diagnosis. A framework is proposed to predict road users’ future positions depending on different extrapolation hypotheses: kinematic methods such as constant velocity and motion pattern matching learnt from the observed trajectories. Two interpretation approaches of safety indicators are presented: (a) aggregated safety indicator distributions and (b) indicator profile classification. The framework is applied to the safety diagnosis of left-turn and opposite-direction interactions at a signalized intersection in Montreal, Canada. The results show that motion pattern matching is able to compute the safety indicators earlier and to provide a larger number of measurements.

• Record URL:
  • https://doi.org/10.1080/19439962.2016.1255690
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/19439962
• Supplemental Notes:
  • © 2018 Taylor & Francis Group, LLC and The University of Tennessee 2018.
• Authors:
  • Saunier, Nicolas
  • Mohamed, Mohamed Gomaa
• Publication Date: 2018-7

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: pp 265-287
• Serial:
  • Journal of Transportation Safety & Security
  • Volume: 10
  • Issue Number: 4
  • Publisher: Taylor & Francis
  • ISSN: 1943-9962
  • EISSN: 1943-9970
  • Serial URL: http://www.tandfonline.com/loi/utss20#.U2qTJPldWCm

Subject/Index Terms

• TRT Terms: Highway safety; Mathematical prediction; Pattern recognition systems; Signalized intersections; Vehicle trajectories
• Uncontrolled Terms: Time to collision
• Geographic Terms: Montreal (Canada)
• Subject Areas: Highways; Safety and Human Factors;

Filing Info

• Accession Number: 01677526
• Record Type: Publication
• Files: TRIS
• Created Date: Aug 8 2018 9:07AM