An Enhanced Network-Level Curve Safety Assessment and Monitoring Using Mobile Devices
A disproportionally high number of serious vehicle crashes (25% of fatal crashes) occur on horizontal curves, even though curves represent only a fraction of the roadway network (5% of highway miles) (1). This is a high-priority problem that has great interest among transportation agencies throughout the nation because their ultimate goal is to reduce serious vehicle crashes on curves. The in-service curve characteristics, including the curve geometry information (curve radius, point of curve, point of tangent, deviation angle, superelevation, and grade), along with traffic speed, vehicle trajectory, and Ball Bank Indicator (BBI) measurements are vitally important for performing curve safety assessment and analysis, for setting up adequate curve advisory speeds, and for studying driving behavior along a curve. The BBI value shows the combined effect of superelevation, driving speed, and the curvature of the driving trajectory. Based on our communication with state DOT engineers, certain geometric properties of the curve, such as superelevation, may change over time because of new pavement resurfacings. Therefore, understanding in-service curve characteristics is vital to assessing and improving curve safety. Transportation agencies, like the Georgia Department of Transportation (GDOT), use the BBI value as a risk factor to proactively identify the curve sites in need of high friction surface treatment (HFST). However, current transportation agencies’ practices use dedicated devices operated by designated engineers to collect and extract the detailed level curve characteristics information for assessing curve safety conditions at the network level. This includes collecting and extracting in-service curve characteristics, acquiring their BBI values, and computing the required advisory speed. The main challenge of current practices is that they are time-consuming, labor-intensive, and costly.
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