Analysis of Intersection Site-Specific Characteristics for Type II Dilemma Zone Determination

Abstract

Dilemma zone could be an effective surrogate safety measure of a signalized intersection because its length and location are significantly correlated with right-angle and rear-end conflicts and vary from one site to another. Two popular methods, Zegeer’s method and time-temperature indicator (TTI) based method, are available in transportation literature to quantify Type II dilemma zones. The existing methods, however, have limitations to quantify the dilemma zone because the former requires extensive data collection and analysis efforts, and the latter is solely dependent on a single variable (i.e., speed). The objective of the present study is to develop effective methods of quantifying Type II dilemma zones using important site-specific characteristics of signalized intersections (e.g., the operating speed, the approach grade, and the amount of truck traffic). The present study also seeks to address the methodological shortcoming of the TTI-based method. Driver behavior at 46 high-speed signalized intersection approaches where the posted speed limit is 80.47 km/h (50 mi/h) or higher was analyzed to see if there is a relationship between the dilemma zone and the intersection site-specific characteristics. The results show that the approach grade, the operating speed, and the amount of truck traffic at the signalized intersection have strong correlations with the dilemma zone. It was also found that the dilemma zone length is longer, and its location is farther from the stop bar if the approach grade is the steeper (toward negative values), if the operating speed is higher, or if more truck traffic operates at the intersection approach. The developed models were compared with the TTI-based method, which uses 2.5 and 5.5 s of the travel time to the intersection stop bar (TTI) to determine the dilemma zone start and endpoints. The analysis showed that the developed site-specific dilemma zone models outperform the TTI-based method and well fit the observed data with pseudo R2≥0.9 and p value ≤0.05.