Rail safety research faces challenges as driver decision behavior at highway-rail grade crossings (HRGCs) has changed in counterproductive ways (FRA, 2020). One example of such an undesired shift is the increased percentage of crashes that take place at HRGCs equipped with active warning devices. Instead of eliminating the crashes at such locations, motorists have shifted the type of risky behavior, such as proceeding around the gates. Emerging V2I technologies may improve rail safety by providing adaptive, in-vehicle alerts and applied cognitive research is needed to inform their designs and implementation.
Recent research suggests that some motorists are making these decision errors when under cognitive load or when HRGCs involve adjacent turns (Brabb, Vithani, & Martin, 2017). However, few rail experiments have examined either factor (Read et al., 2021). Our proposed project begins to bridge this gap by conducting three driving simulator experiments to quantify the impact of HRGC configuration (e.g., short storage) and cognitive load on driver attention and decision behavior.
This project builds on earlier research which concluded that HRGC configuration affected driver decision behavior and that motorists attended to different safety information at different HRGCs (c.f., Linja, Lautala, Nelson & Veinott,2020). In the current experiments, we will focus on the interaction between two factors, cognitive load and HRGC configuration, on driver decision behavior (e.g., speed, lane deviations) and attention management and test several new scenarios suggested by past HRGC work. With new in-vehicle intelligent warning capabilities, this research may inform future technology design, implementation or adoption of these technologies. It will also inform future research to evaluate the potential impact on motorist decision behavior under different HRGC conditions.