Freeing Cognitive "Bottleneck Congestion" in Autonomous Vehicles
In March 2018, Tesla’s second fatal crash involving its autopilot self-steering system happened on highway 101 in Mountain View, California (The Guardian Staff 2018). Collision reports showed that the driver, Apple software engineer Wei Huang, had received both visual and auditory cues from the self-steering system prior to his vehicle crashing into a concrete median, which tragically killed him. Apparently, Huang had 150 meters of the median in view, or five seconds to react and avoid the barrier if he had been paying full attention to the situation at hand.
Although autonomous vehicle systems have saved more lives than shed (Marshall 2017), should we expect more incidents like these to occur during their continued production? What is more, does the fact that accidents still occur in autonomous self-steering systems (which are designed to improve driver safety) necessitate a deeper investigation into the relationship between hazard perception, automated cues, and multi-tasking?
Although they represent an important part of technological advancement, autonomous vehicles still introduce disturbances for drivers, who may otherwise view them as a way to kick back and direct their attention elsewhere. Putting such trust into driver assistance design can introduce drivers to a dangerous amount of risk, instead of making driving easier and safer. According to behavioral science, this increased capacity to multitask behind the wheel may bring further problems for other drivers and road safety in general, as studies show that our cognitive decision-making systems aren’t as sophisticated as we may think.
To mitigate these risks, the autonomous vehicle industry may benefit from these behavioral science insights, and uncover more about the driver’s cognitive architecture and decision-making processes. By understanding when, where, and how drivers most optimally multitask, the industry can help design policies and technological interventions that enhance synchrony in the autonomous transportation realm.
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About the Author
Hanna Haponenko
Hanna obtained her undergraduate degree in Health Sciences before branching off to focus on cognition and perception, and is currently a PhD candidate in Cognitive Psychology at McMaster University. Her current research endeavours involve coding a driving simulator to test the effectiveness of cues while multitasking.
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