Using Naturalistic Field Operational Test Data to Identify Horizontal Curves

Abstract

Investigations to identify relationships between crashes and road features usually deal with effects of only one or two of the main components of traffic safety, i.e., human, vehicle, and infrastructure performance. There are several contributing factors of the components that together lead to a crash. This study devises an approach to include information from all three components in a system using field operational test (FOT) data. FOT data are recorded from real-life driving that is different from traffic simulations and specific on-site data collection. The study focuses on identifying horizontal curves using FOT and provides access to vehicle and human response data at the exact time when the vehicle drove in a specific location. A method has been developed to derive path radius and to identify start–end points of horizontal curves using FOT data. With this information, vehicle response signals and human behavior data can then be arranged on a common axis referenced to the curve. The approach also identifies lane changing maneuvers on curves that can be used to evaluate potential crash triggers. The application of this method allows for reviewing changes in the regulatory speed limit, curve geometry, or crash history and thus evaluates the design of curves and choosing appropriate countermeasures.