Mechanical Preference and Handedness of Drivers
Disciplines
Applied Behavior Analysis | Biological Psychology | Cognitive Science | Experimental Analysis of Behavior
Abstract (300 words maximum)
With autonomous vehicles (AV), we can travel efficiently without the risk of human error. Autonomous vehicle, also known as a self-driving car, employs a combination of sensors, cameras, and artificial intelligence to navigate and operate safely in the environment with little or no human intervention. However, this modern technology does come with potential problems. A notable issue with AVs is ‘silent failures,’ where the vehicle does not respond appropriately in a specific circumstance without providing a warning to the driver (Mole et al., 2020). When silent failures appear, the AV may prompt a driver to take over the vehicle by using their hands to steer the wheel and avoid a potential collision (Petermeijer et al., 2017). Therefore, it is important to consider how an individual’s hand dominance may influence a driver’s decision in turning left or right when avoiding a collision. As a result, we analyzed how hand dominance, which refers to an individual’s biomechanical preference while doing specific tasks, contributes to the driver’s takeover performance when faced with a silent failure. Historically, there has been a right-hand preference for performing precision tasks which could further be affected by the forces of gravity (citation). Previous studies found that individuals exert less force to pull down the steering wheel with their dominant hand since the motion of pulling down is assisted by gravitational forces (Sakajiri et al., 2013). Therefore, we hypothesized that participants would turn in the direction that corresponds to their dominant hand. We instructed participants to take over with both hands and analyzed their performance when faced with a silent failure at a T-intersection. We chose the T-intersection as it requires the participants to take-over by either turning left or right to avoid a collision. To test this hypothesis, we used virtual reality (VR) technology and a driving simulator.
Academic department under which the project should be listed
RCHSS - Psychological Science
Primary Investigator (PI) Name
Kyung Jung
Mechanical Preference and Handedness of Drivers
With autonomous vehicles (AV), we can travel efficiently without the risk of human error. Autonomous vehicle, also known as a self-driving car, employs a combination of sensors, cameras, and artificial intelligence to navigate and operate safely in the environment with little or no human intervention. However, this modern technology does come with potential problems. A notable issue with AVs is ‘silent failures,’ where the vehicle does not respond appropriately in a specific circumstance without providing a warning to the driver (Mole et al., 2020). When silent failures appear, the AV may prompt a driver to take over the vehicle by using their hands to steer the wheel and avoid a potential collision (Petermeijer et al., 2017). Therefore, it is important to consider how an individual’s hand dominance may influence a driver’s decision in turning left or right when avoiding a collision. As a result, we analyzed how hand dominance, which refers to an individual’s biomechanical preference while doing specific tasks, contributes to the driver’s takeover performance when faced with a silent failure. Historically, there has been a right-hand preference for performing precision tasks which could further be affected by the forces of gravity (citation). Previous studies found that individuals exert less force to pull down the steering wheel with their dominant hand since the motion of pulling down is assisted by gravitational forces (Sakajiri et al., 2013). Therefore, we hypothesized that participants would turn in the direction that corresponds to their dominant hand. We instructed participants to take over with both hands and analyzed their performance when faced with a silent failure at a T-intersection. We chose the T-intersection as it requires the participants to take-over by either turning left or right to avoid a collision. To test this hypothesis, we used virtual reality (VR) technology and a driving simulator.