Does the Conspicuity of Automated Vehicles with Visible Sensor Stacks Influence the Car-Following Behavior of Human Drivers? A Pilot Study

Abstract

As autonomous vehicles (AVs) become more prevalent in traffic systems and human drivers are beginning to interact with them, understanding how the presence of AVs affects traffic dynamics and safety is becoming more important. This study investigates the impact of AVs on the behavior of human-driven vehicles (HDVs) in mixed traffic environments. One key question is whether the conspicuity of an AV influences HDV car-following behavior. Using data from a naturalistic driving study conducted in Ohio, U.S., for different road types, this research compares interactions with two types of advanced driver assistance system (ADAS)-equipped vehicle: readily identifiable (RI) with visible sensor arrays, and discreet (DI) with concealed sensors. Using statistical tests such as the Kolmogorov-Smirnov test and the Mann-Whitney U test, the analysis of key metrics—including following distances, gaps, speed differences, acceleration, braking patterns, and lateral distances during overtaking events—revealed notable differences in following behavior when trailing an RI vehicle. Specifically, drivers tended to maintain greater distances and adjust their speed and acceleration patterns more when following RI vehicles than when following DI vehicles. The results also indicated that drivers braked more aggressively on freeways and non-divided roads when following RI vehicles, and they maintained greater distances when overtaking on freeways. Assessing surrogate measures of safety, such as time-to-collision and deceleration required to avoid crash, further confirmed what appears to be safer driving behavior when following RI vehicles. This suggests that human drivers interact differently around AVs depending on their visibility. These findings underscore the need to consider the visibility of AV features in traffic management and vehicle design to optimize traffic flow and enhance road safety.

Keywords

advanced driver assistance systems (ADAS)driver behavior car-following model naturalistic driving data surrogate measures of safety (SMS)

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