Examining causal factors of traffic conflicts at intersections using vehicle trajectory data

Conflict severity is the outcome of complex interactions between roadway and environmental characteristics, and vehicle motion. Understanding how and to what extent a vehicle is influenced by roadway and surrounding road users during a conflict is helpful in analyzing the causal mechanisms of collisions, thus providing insights into roadway safety improvement countermeasures. This study utilized the NGSIM vehicle trajectory datasets to investigate the causal factors in conflicts at intersections by exploring roadway-to-vehicle and vehicle-to-vehicle interactions. In order to remove the outliers and white noise existing in the raw data, vehicle trajectories were reconstructed by discrete wavelet transform and Kalman filtering. Generalized time-to-collision was adopted to detect and measure the severity of conflicts, by which 1,127 conflict events were extracted. Path analysis models were then established to determine in exactly which ways the roadway-to-vehicle and vehicle-to-vehicle interactions were related to conflict severity. Various roadway and environmental characteristics such as traffic flow average speed, percentage of trucks, and intersection skew angle were included in the models. The results indicate the roadway and environmental characteristics have both direct and indirect effects on conflict severity; in the indirect effects, the conflicting vehicle’s kinematics, such as the average and standard deviation of speed, play an intermediate role in linking roadway factors and conflict outcome. The framework of this study can be applied to assessing roadway readiness for both human-driven and automated vehicles.

• Record URL:
  • https://doi.org/10.1016/j.ijtst.2024.02.011
• Record URL:
  • http://www.sciencedirect.com/science/article/pii/S2046043024000315
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/20460430
• Supplemental Notes:
  • © 2024 Tongji University and Tongji University Press. Publishing Services by Elsevier B.V. Abstract reprinted with permission of Elsevier.
• Authors:
  • Xu, Xiaoyan
  • Wang, Xuesong
  • Shi, Ruolin
• Publication Date: 2025-3

Language

• English

Media Info

• Media Type: Web
• Features: Figures; References; Tables;
• Pagination: pp 79-94
• Serial:
  • International Journal of Transportation Science and Technology
  • Volume: 17
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 2046-0430
  • Serial URL: http://www.sciencedirect.com/science/journal/20460430

Subject/Index Terms

• TRT Terms: Intersections; Kalman filtering; Kinematics; Traffic conflicts; Traffic data; Vehicle trajectories
• Subject Areas: Data and Information Technology; Highways; Operations and Traffic Management; Safety and Human Factors;

Filing Info

• Accession Number: 01915949
• Record Type: Publication
• Files: TRIS
• Created Date: Apr 19 2024 9:38AM