Expectations and Understanding of Advanced Driver Assistance Systems Among Drivers, Pedestrians, Bicyclists, and Public Transit Riders
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2021-06-01
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Abstract:Vehicle technology has progressed significantly over the past 20 years to the point where automated systems can now take on different aspects of a vehicle’s control. While drivers play a central role in the effective and appropriate use of these technologies, these systems do not affect the drivers of such vehicles alone. Other road users must interact with these vehicles safely and, as such, it is important to examine the perceptions, understanding, and expectations concerning these systems. The current study sought to examine whether drivers and non-drivers differ in their perceptions and understanding of advanced driver assistance system (ADAS) technology (i.e., SAE Levels 1 and 2), in their trust and expectations of ADAS technology in specific use cases, and in their outlook of the future of automated vehicle technology. A total of 1,531 participants responded to an online survey and were subsequently identified as belonging to different road-user groups (predominantly in the categories of drivers, bicyclists, pedestrians, public transit riders). The results revealed differences across road-user groups in terms of their understanding, expectations, behaviors, trust, and perceptions of risk. Importantly, differences in perceived expectations and trust were not always associated with changes in perceived risk and behavioral responses. In some cases, non-drivers’ responses revealed that they had false expectations of the technology, or that they intended to interact with partially-automated driving systems in the same manner as they interact with conventional vehicles, which might increase their risk. Collectively, the current outcomes underscore the need to better understand all road users’ expectations regarding new vehicle technology, as well as their behaviors when interacting with these vehicles. Knowledge of how information and sources influence understanding and accuracy of user’s mental models of technology might lend itself to individualized or targeted approaches appropriate for different road-user groups.
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