Investigation of surrogate measures for safety assessment of two-way stop controlled intersections.
thesisposted on 08.06.2021, 10:41 by Adrian Lorion
Crash prediction models used to estimate safety at intersections, road, and highway segments are traditionally developed using various traffic volume measures. There are issues with this approach and surrogate safety measures such as conflicts and delays can overcome them. This study investigates the relationships between crash frequencies and traffic volume, intersection delay, and conflicts to explore the viability of these models for estimating safety at two-way stop controlled intersections. The database used includes 78 three leg and 55 four leg intersections within the Greater Toronto Area. Crash prediction models were developed and evaluated based on goodness-of-fit measures and CURE plots. Two conflict estimation techniques are compared in order to determine which is best suited for two-way stop controlled intersection simulations. This study also investigates the use of the models for estimating the safety impact of implementing a left turn lane on a major approach of a three leg intersection.