Keeping the driver in the loop through semi-automated or manual lane changes in conditionally automated driving

J Dillmann,R.J.R Den Hartigh,C.M Kurpiers,J Pelzer,F.K Raisch,R.F.A Cox,D De Waard

doi:10.1016/j.aap.2021.106397

J Dillmann, R.J.R Den Hartigh + Show 5 more

Open Access

https://doi.org/10.1016/j.aap.2021.106397

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Abstract

In the current study we investigated if drivers of conditionally automated vehicles can be kept in the loop through lane change maneuvers. More specifically, we examined whether involving drivers in lane-changes during a conditionally automated ride can influence critical take-over behavior and keep drivers’ gaze on the road. In a repeated measures driving simulator study (n = 85), drivers drove the same route three times, each trial containing four lane changes that were all either (1) automated, (2) semi-automated or (3) manual. Each ride ended with a critical take-over situation that could be solved by braking and/or steering. Critical take-over reactions were analyzed with a linear mixed model and parametric accelerated failure time survival analysis. As expected, semi-automated and manual lane changes throughout the ride led to 13.5% and 17.0% faster maximum deceleration compared to automated lane changes. Additionally, semi-automated and manual lane changes improved the quality of the take-over by significantly decreasing standard deviation of the steering wheel angle. Unexpectedly, drivers in the semi-automated condition were slowest to start the braking maneuver. This may have been caused by the drivers’ confusion as to how the semi-automated system would react. Additionally, the percentage gaze off-the-road was significantly decreased by the semi-automated (6.0%) and manual (6.6%) lane changes. Taken together, the results suggest that semi-automated and manual transitions may be an alarm-free instrument which developers could use to help maintain drivers’ perception–action loop and improve automated driving safety.

Highlights

The safe interaction of the human with the automated vehicle will likely remain a relevant road safety objective for the coming decades (Chan, 2017; Fagnant & Kockelman, 2015; Parasuraman & Wickens, 2008)
Satisfaction was scored highest in the automated condition when contrasted to a linear combination of the semi-automated and manual lane change conditions, b = -0.20, t(1 3 0) = − 8.24, p < .001, but satisfaction was higher in the semi-automated than the manual lane change condition, b = -0.16, t(1 3 0) = − 3.66, p
We found the same pattern: The automated lane change condition scored higher than the semiautomated and manual lane change conditions, b = -0.26, t(1 3 0) = -9.45, p < .001, and the semi-automated lane change was perceived as

Summary

Introduction

The safe interaction of the human with the automated vehicle will likely remain a relevant road safety objective for the coming decades (Chan, 2017; Fagnant & Kockelman, 2015; Parasuraman & Wickens, 2008). The quality of drivers’ reactions in safety critical take-over situations has been shown to be lower if the driver has been driving with automation (de Waard et al, 1999; Gold et al, 2013; Louw et al, 2017b) This performance decrement has been linked to drivers’ reduction of physical control of the vehicle and perception of the driving scene, which is reflective of the driver being out-of-the-loop (Merat et al, 2018). To counteract this safety critical out-of-the-loop problem it is of interest how motor-perceptual mapping and gaze patterns can be maintained while driving with automation (Mole et al, 2019)

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