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Trajectory-based indicators to determine the local character of intersection conflicts: A micro-spatial analysis.

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  • 1Austrian Institute of Technology, Giefinggasse 4, Vienna 1210, Austria.

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This study introduces the Mobility Observation Box (MOB) for collecting real-world road user behavior data to assess road safety. It found that while most road users are safer than cars, cyclists in a leading role pose a higher risk, influencing conflict angles.

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Area of Science:

  • Traffic Engineering and Road Safety
  • Transportation Data Analysis
  • Behavioral Analysis in Transportation

Background:

  • Collecting real-world road user behavior data for safety assessment is challenging due to data protection and logistical issues.
  • Existing methods struggle with rapid, portable data collection for road safety research.
  • The Mobility Observation Box (MOB) offers a flexible solution for data collection and video analysis.

Purpose of the Study:

  • To advance road safety research by analyzing naturalistic video data using the MOB.
  • To model the likelihood of critical conflict occurrence using random parameters binary modeling.
  • To identify factors influencing conflict angles in critical situations using Gaussian generalized additive spatial modeling.

Main Methods:

  • Utilized over 51 hours of naturalistic video data from a busy Vienna intersection.
  • Employed object detection and tracking to derive movement trajectories and Surrogate Safety Measures (SSMs) like PET, TCA, and TTC.
  • Applied random parameters binary modeling and Gaussian generalized additive spatial modeling to analyze conflict occurrence and influencing factors.

Main Results:

  • Identified specific speed, acceleration, and road user type effects on conflict likelihood and angles.
  • Cars were found to be the benchmark for safety, with most other road users being less likely to be involved in critical conflicts.
  • Cyclists in a leading role were an exception, showing a higher likelihood of involvement in safety-critical conflicts.
  • Kinematic parameters (speed, acceleration, deceleration), interaction duration, and leading road user position significantly influenced conflict angles.

Conclusions:

  • The MOB system effectively enables the derivation of quantitative road safety indicators from real-world behavior data.
  • Road user type significantly impacts safety-critical conflict involvement, with cars serving as a baseline.
  • Understanding micro-spatial and kinematic factors is crucial for analyzing and mitigating critical conflict angles at intersections.