A Path towards Sustainable Vehicle Automation: Willingness to Engage in Level 3 Automated Driving

Tomasevic, Nebojsa; Young, Kristie L.; Horberry, Tim; Fildes, Brian · 2022 · Crossref

DOI: 10.3390/su14084602

archive: archived pipeline: cataloged verified

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Summary

This study investigates the factors influencing driver willingness to engage (WTE) in Level 3 automated driving and willingness to resume control (WTRC), addressing a critical gap in understanding human factors for sustainable vehicle automation. As Level 3 automation approaches commercial viability, understanding driver acceptance is essential for successful integration into transport systems. The research specifically examines how perceived situation complexity, trust in automation, and driving enjoyment affect these willingness metrics during everyday, non-critical driving scenarios. The researchers employed a 2 × 2 × 2 factorial experimental design using a purpose-built driving simulator. Forty participants (mean age 40.35 years) were exposed to driving situations varying by speed (low/high), driving mode (manual/automated), and situation complexity (low/high). Low complexity was represented by free driving, while high complexity included four distinct events: rain and fog, oncoming cars, give-way intersections, and vehicle following. The study utilized a "simulation freeze" technique, pausing the simulation to collect self-reported data on WTE, WTRC, and perception of safety (POS). This method allowed for the measurement of subjective responses at specific moments within the driving task without significantly affecting overall task performance. The results demonstrated a strong negative effect of perceived situation complexity on willingness to engage in automated driving. As driving situations became more complex, drivers were significantly less likely to engage the automation system. Conversely, higher situation complexity positively influenced the willingness to resume control. Other significant determinants of WTE included trust in automation and driving enjoyment. The study confirmed that drivers perceive automated driving as less safe in complex situations, which directly correlates with their reluctance to engage the system. These findings highlight that driver behavior is not static but dynamically adjusts based on the perceived demands of the driving environment. The significance of this research lies in its identification of perceived situation complexity as a primary barrier to the uptake of Level 3 automation. The findings suggest that the sustainability and adoption of automated vehicles can be improved through external interventions, including technological enhancements, regulatory frameworks, and publicity campaigns that address driver concerns in complex scenarios. By understanding that drivers disengage automation in response to perceived complexity, manufacturers and policymakers can better design systems and regulations that support safe and efficient human-machine interaction, ultimately facilitating the transition toward sustainable automated transport.

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Summary generated by qwen3.6-27b-prismaquant on 2026-06-09; verification: verified.

Topics

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• acceptance adoption
• automation
• trust calibration
• automation surprise
• situational awareness
• automation complacency bias

Information type

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• Empirical Findings: self report data
• Theoretical Contribution: conceptual framework, computational model