Conflict angle analysis at multilane roundabouts using naturalistic vehicle trajectory data from UAVs

Roundabouts are crucial for improving traffic safety by reducing crashes, driving speeds, and conflict points during navigation. In Greece, the growing number of modern roundabouts necessitates a comprehensive assessment of their safety performance. This study aims to enhance current knowledge by employing Surrogate Safety Measures (SSMs) to investigate conflict angles at modern multilane roundabouts in Greece using naturalistic vehicle trajectory data. To the extent of the authors' knowledge, this is the first study that explicitly analyzes conflict angle as the response variable using naturalistic UAV data.

Detailed vehicle trajectory data from four modern multilane roundabouts were collected through Unmanned Aerial Vehicle (UAV) video recordings and processed using vehicle tracking software. The SSM Post-Encroachment Time (PET) was calculated, and a dataset incorporating driving behavior variables was developed. A mixed-effects Beta-regression Model (BRM) with site-varying random intercepts was applied to model conflict angles and identify the geometric and vehicular parameters influencing them.

The modeling results revealed that the location of conflicts within the roundabout significantly affects the conflict angle. Furthermore, site-specific characteristics were found to have a substantial impact, emphasizing that roundabout safety performance can vary by location.

The findings provide new insights into the factors affecting conflict angles at multilane roundabouts. These insights have important implications for both vehicle dynamics and infrastructure design, supporting policymakers and engineers in developing targeted strategies to further improve safety at modern roundabouts.