Passenger-Driver Distinguishing Test for Pokémon Go

Khanade, Kunal; Sasangohar, Farzan · 2017 · Crossref

DOI: 10.1177/2327857917061002

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Summary

This study addresses the safety hazard of distracted driving caused by augmented reality (AR) games, specifically *Pokémon Go*. While existing countermeasures restrict gameplay based on speed or location, these methods often inconvenience passengers who pose no safety risk. The authors propose a "passenger-driver distinguishing test" that leverages cognitive load to differentiate between drivers and passengers. The core hypothesis is that the cognitive burden required to simultaneously drive and complete a secondary visual memory task exceeds human visual short-term memory (VSTM) capacity, thereby reducing driving vigilance and increasing crash risk for drivers, while remaining manageable for passengers. To test this feasibility, the researchers conducted an experiment using a driving simulator (STISIM Drive® M100) with ten university students holding valid driver’s licenses. Participants performed two conditions: a standalone memory test and a simultaneous driving and memory test. The memory task required participants to recall specific numbers from a four-item sequence displayed for 2–3 seconds, with a 2–3.5 second window to answer. This design was chosen because VSTM capacity is estimated at four items. In the driving condition, participants navigated a suburban route with stop signs and surprise events (pedestrians, dogs) while completing the memory test. Performance was measured by the number of consecutive correct answers in a series, as well as driving violations and crashes. The results indicated a statistically significant difference in performance between the two conditions. Participants achieved a mean of 4.7 correct answers in the standalone memory test, compared to a mean of 3.4 correct answers when driving simultaneously (t-test p-value = 0.061). The study found that the cognitive demand of the memory task pulled attention away from driving, leading to increased speed limit violations (occurring in over 80% of cases) and heightened crash risk. The authors noted that the specific formatting of the numbers (e.g., four two-digit numbers vs. three three-digit numbers) affected perceived difficulty, suggesting that chunking influences cognitive load. The study concludes that such identification tests show promise for distinguishing drivers from passengers by exploiting the limits of divided attention and VSTM. By imposing a cognitive burden that makes simultaneous driving and gaming difficult, the test acts as a safety lock that deters drivers from playing while driving without restricting passengers. The authors suggest these tests could also be applied to other contexts requiring focused attention or vigilance. However, they acknowledge limitations, including the small sample size, the controlled laboratory environment, and the potential for passenger frustration, noting that further research is needed to optimize test parameters for broader applicability.

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Summary generated by qwen3.6-27b-prismaquant on 2026-06-10; verification: verified.

Topics

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• visual
• temporal
• distraction detection algorithms
• external distraction
• cognitive
• cognitive capacity variation

Information type

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• Empirical Findings: behavioral performance data
• Methodological Resource: measurement protocol
• Theoretical Contribution: theory or model