Artificial test environments have become indispensable for modeling human behavior in traffic because they provide more control of experimental factors and fewer ethical concerns than a real traffic environment. These advantages are particularly critical for research on interactions involving vulnerable road users such as cyclists and drivers of motorized vehicles. However, previous research comparing test environments has predominantly focused on car-to-car interaction scenarios. This study investigated a cyclist-overtaking scenario in three different environments: a driving simulator (SIM: N = 25), a test track (TT: N = 18), and a hybrid “driver-vehicle-in-the-loop” environment (DVIL: N = 33) in which the participants drove a real vehicle on a test track while wearing a virtual-reality headset, so they could only see the virtual environment. Overall, the results verified that the direction of the main factors affecting overtaking strategy and performance was similar across all environments. In presence of a close oncoming vehicle, drivers in all environments preferred the more cautious accelerative (waiting behind the cyclist) over flying (passing the cyclist while facing the oncoming vehicle) overtaking strategy, and this effect was strongest in SIM. Metrics related to safety margins to the cyclist followed a similar trend in all environments in the presence of oncoming traffic; however, the TT environment had the smallest overall safety margins, suggesting that virtual visual cues induce safer behavior. Because overtaking maneuvers depend on depth estimation, the visual resolution of the virtual environment may be more important than the environment itself in explaining the results.
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Rasch et al. (2024) studied this question.
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