Application and Comparison of Different Methods for Traffic Conflict Analysis – Case Study on 2+1 Roads

Abstract

Safety Performance Functions and Crash Modification Factors are statistically-based prediction methods that require significant efforts and long periods in crash data collection. Traffic conflict studies can mitigate this issue using a short time survey to measure the number and severity of traffic conflicts, which are regarded as surrogate safety measures. Unfortunately, they are empirical studies that can be carried out only after the implementation of a treatment. The overall objective of the present research is to investigate the performance of different methods for conflict detection and classification, considering the observed conflicts on 2+1 roads in Poland. Observations were compared with conflicts detected in simulated environments. The latter include either the Agent-Based Microsimulation (ABM) approach, or the virtual reality simulation using a Driving Simulator (DS). Conflicts were detected and classified based on video recording and analysis of vehicle trajectories in the merging area of 2+1 roads. The studies focused only on lane-changing conflicts. Locations, Post Encroachment Time and Time to Collision values of observed conflicts between vehicles were subsequently identified. Observed conflicts were compared with the ones resulting from ABM and DS, to determine whether there is a correlation between them.

Keywords

• surrogate measures of safety
• road safety
• ssam
• passing lane
• 2+1 road