Understanding Behavioural Adaptations of Human Drivers interacting with Automated Vehicles

Abstract

Advancements in technology are bringing Automated vehicles (AVs) closer to reality and it is not so far in future when these vehicles will have a significant penetration rate in our existing transport network. However, in the early phases of automation, penetration rate of these vehicles will be very low. This would lead to a mixed traffic situation where AVs will coexist and interact with other human driven vehicles (HDVs). This one to one interaction might lead to change in driving behavior of HDVs when they interact with AVs. Thus it is crucial to understand the behavioral adaptation of HDVs due to their interaction with AVs. A field test was conducted to gain insights about such behavioral adaptation focusing on gap acceptance, car following, and overtaking behavior. Furthermore, learning effet over multiple interactions with AVs, effect of positive and negative information, stress during interaction and trust in AVs were also studies. This research concludes following findings. First, significantly lower critical gaps were accepted during interaction with AVs. Second, significantly lower headways were found at the end of overtaking during interaction with AVs. Third, higher trust was reported in AV scenarios. Fourth, positive information leaded to even closer interactions with AVs in comparison to HDVs. These findings indicate the potential exploitation of AV technology by HDV-drivers.