Behavioural changes in drivers experiencing highly-automated vehicle control in varying traffic conditions

Jamson, A. Hamish; Merat, Natasha; Carsten, Oliver; Lai, Frank · 2013 · OpenAlex-citations

DOI: 10.1016/j.trc.2013.02.008

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Summary

This study investigates how driver behavior changes when using highly-automated vehicle control systems under varying traffic conditions. The research addresses the "ironies of automation," where high levels of automation can reduce driver situation awareness and induce underload, potentially compromising safety. The authors hypothesized that allowing drivers to engage in voluntary secondary tasks, such as in-vehicle entertainment, might alleviate underload and create a more engaging driving experience without significantly impacting safety, provided drivers maintain adequate supervisory attention. The experiment utilized a high-fidelity driving simulator with a motion platform to provide realistic inertial cues. Forty-nine high-mileage drivers participated in a repeated-measures design manipulating two independent variables: Automation Level (manual vs. highly-automated) and Traffic Density (light vs. heavy). The highly-automated system combined Adaptive Cruise Control and Lane Keeping System functionalities. Drivers were permitted to freely engage with secondary tasks, including watching DVDs, listening to the radio, or using handheld games. Data collection included eye-tracking to measure visual attention and fatigue (via PERCLOS), as well as driving metrics such as lane choice and time-to-collision. Results indicated that drivers using automation significantly reduced their engagement in overtaking maneuvers, preferring to remain in slower lanes rather than disengaging the system to overtake, which increased journey times. Automation improved safety margins in car-following scenarios, but this benefit was restricted to light traffic conditions; in heavy traffic, automated longitudinal control performed similarly to manual driving. Drivers engaged significantly more with secondary tasks during automated driving, particularly watching DVDs, which led to a substantial decrease in visual attention to the road center. However, drivers demonstrated increased visual attention to the roadway in heavy traffic conditions compared to light traffic, suggesting they adjusted their supervisory effort based on environmental demand. Additionally, while automation increased signs of fatigue (higher PERCLOS), heavy traffic conditions mitigated this effect. The findings suggest that drivers are willing to trade supervisory responsibilities for entertainment when using automated systems, yet they retain the ability to increase attention when traffic density rises. This implies that drivers can manage supervisory demands dynamically, potentially alleviating concerns about automation-induced underload. The study concludes that well-designed automation, combined with positive system feedback, can support a safer and more engaging driving environment, provided drivers understand their supervisory obligations.

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Topics

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• automation
• automation surprise
• automation complacency bias
• situational awareness
• manual
• takeover transitions

Information type

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• Empirical Findings: behavioral performance data
• Theoretical Contribution: theory or model, conceptual framework