1666062 - Analyzing Dilemma Zone Using an Analytical Vehicle Matching Algorithm and High-Resolution Event Data

Physical characterization of the dilemma zone (DZ) in existing studies has been done based on two divergent definitions or approaches: Type I and Type II. Type I definition uses the minimum stopping distance and the maximum clearing distance to quantify the dilemma, whereas Type II approach is based on stopping probability and travel time to the intersection stop line. However, treating the DZ boundary differently—without an integrated empirical assessment of Type I and Type II quantifications—may lead to inaccurate results of DZ-related and subsequent safety analyses at intersections. To this end, we empirically analyzed the two DZ definitions and assessed the dynamic nature of their boundaries with approach velocity and time of day. First, we proposed a novel rule-based matching methodology with 92% accuracy to match actuation events between the advance and stop-bar detectors. This methodology was then applied to process two months of high-resolution events data from an intersection approach, yielding a large sample of 28,700 vehicle arrivals on yellow. Results showed that 13.2% of approaching vehicles fall into an indecision zone or make Type I-contrary stop/run decisions at the yellow onset. Compared to Type I DZ, option zone, and Type II travel time-based DZ, the Type II probabilistic DZ varied by time of day but not by approach velocity. Moreover, the empirical analysis showed that the Type I and Type II DZ boundaries were segregated and did not significantly overlap. Our novel findings indicate a lack of consistency in defining DZ and emphasize a need for data-driven quantification of the DZ boundary and its dynamics.