Calibration of car-following models of human driven vehicles interacting with automated vehicles in mixed traffic
a driving simulator experiment
Nagarjun Reddy (TU Delft - Traffic Systems Engineering)
Serge P. Hoogendoorn (TU Delft - Traffic Systems Engineering)
Haneen Farah (TU Delft - Traffic Systems Engineering)
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Abstract
The deployment of automated vehicles (AVs) on public roads remains limited due to concerns about their interaction with human-driven vehicles (HDVs) in mixed traffic. While previous studies suggest that AVs influence HDV behaviour, the nature of this influence is still not well understood. This study examines how AVs affect HDV car-following behaviour in mixed traffic conditions. Empirical data were collected through a driving simulator experiment in which participants followed a lead vehicle in four scenarios varying in vehicle appearance (AV or HDV) and driving style (AV-like or HDV-like). Car-following behaviour was analysed using the Intelligent Driver Model (IDM) and an extended version (IDM+). The results show that HDVs adapt their behaviour when following AVs, exhibiting smaller jam spacing distances and shorter safe time headways compared to following HDVs. These findings support more accurate assessments of traffic safety and efficiency and contribute to the safe integration of AVs into mixed traffic.
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