Do drivers change their manual car-following behaviour after automated car-following?

Louw, Tyron; Gonçalves, Rafael S.; Torrão, Guilhermina; Radhakrishnan, Vishnu; Lv, Wei; Guillen, Pablo Puente; Merat, Natasha · 2020 · OpenAlex-citations

DOI: 10.1007/s10111-020-00658-5

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Summary

This study investigates whether drivers alter their manual car-following behavior after experiencing automated car-following, specifically examining the influence of automation level, system-maintained headway, and resumption conditions. Motivated by evidence that Advanced Driver Assistance Systems (ADAS) like Adaptive Cruise Control can lead to behavioral adaptations such as reduced time headway (THW), the research addresses a gap in understanding how higher levels of automation (SAE Level 2 and Level 3) affect subsequent manual driving performance. The study aims to determine if exposure to specific automated headways or engagement in non-driving-related tasks (NDRTs) during automation influences the safety margins drivers adopt upon resuming control. The experiment utilized a driving simulator with 32 participants divided into two groups: SAE Level 2 (L2), where drivers monitored the road, and SAE Level 3 (L3), where drivers performed a visual NDRT. Participants experienced automated car-following with either a short (0.5 s) or long (1.5 s) THW. They resumed manual control either in the presence of a lead vehicle or without one. All post-automation manual drives were compared to a baseline manual drive recorded prior to automation exposure. Statistical analyses, including mixed ANOVAs, assessed changes in mean THW, while subjective feedback and questionnaires on driver traits (e.g., sensation seeking) were also collected. Results indicated that drivers in both L2 and L3 groups significantly reduced their THW in all post-automation manual drives compared to the baseline. The reduction in THW was more pronounced when drivers resumed control in the presence of a lead vehicle and after experiencing the shorter (0.5 s) automated THW. However, the level of automation (L2 vs. L3) did not significantly influence the change in mean THW. Subjective data revealed that drivers were largely unaware of these behavioral changes but preferred longer THWs during automated driving. The study found no significant correlation between driver traits like sensation seeking and the magnitude of behavioral adaptation. The findings suggest that exposure to automated car-following leads to a persistent reduction in safety margins during subsequent manual driving, particularly when the system maintains short headways or when drivers resume control with a vehicle immediately ahead. This behavioral adaptation poses a safety risk, as drivers may adopt unsafe headways after automation disengagement. The authors conclude that automated driving systems should adopt longer THWs in car-following scenarios to mitigate the risk of drivers adopting dangerously short headways upon resuming manual control. These results highlight the importance of considering long-term behavioral adaptation in the design of automated driving systems, beyond immediate take-over performance.

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Topics

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• following distance
• automation
• automation surprise
• takeover transitions
• behavioral adaptation risk compensation
• manual

Information type

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• Empirical Findings: behavioral performance data
• Theoretical Contribution: computational model