An integrated VISSIM-SSAM approach to predicting and mitigating pedestrian crashes and severity along urban crossings

Abstract

Crash and crash severity is a growing problem along India's roadways. In 2019, pedestrian share in road deaths in India stood at 18%. The availability of good quality data for statistically significant analysis of pedestrian crashes is scarce, especially for developing and under-developed countries. As such, simulation techniques are being increasingly employed by researchers. This study develops a three-step methodology to proactively predict pedestrian conflicts at urban crossings under mixed-traffic conditions: (a) Development and calibration of on-street conditions in VISSIM and identifying vehicle–pedestrian conflicts using the time to collision (TTC) and post encroachment time (PET), (b) Calibrating the TTC and PET thresholds using pedestrian-vehicle conflict analysis (PVCA), and (c) Predicting impact of mitigation measure on pedestrian conflict frequency and network-flow. The study area, an urban arterial in Kolkata, India, which has reported the highest number of pedestrian crashes in previous years, was successfully simulated using a VISSIM-SSAM-based model (VISSIM-Surrogate Safety Assessment Model). The model predicted the frequency of pedestrian conflicts with more than 90 percent accuracy. Subsequently, mitigation strategies along the urban arterial corridor, which contained five intersections, was simulated. The model predicted a decrease in the frequency of vehicle–pedestrian conflicts, both at major and minor intersections, from anywhere between 26 and 51%.