Driver behaviour and driver experience of partial and fully automated truck platooning \u2013 a simulator study

Magnus Hjälmdahl,Birgitta Thorslund,Stas Krupenia

doi:10.1007/s12544-017-0222-3

Magnus Hjälmdahl, Birgitta Thorslund + Show 1 more

Open Access

https://doi.org/10.1007/s12544-017-0222-3

Copy DOI

Abstract

IntroductionThis paper builds our knowledge of truck driver behaviour in and experience of automated truck platooning, focusing on the effect of partially and fully automated truck platoons on driver workload, trust, acceptance, performance, and sleepiness.MethodsTwenty-four male drivers experienced three conditions in a truck driving simulator, i.e., baseline, partial automation, and full automation: the baseline condition was driving with standard cruise control; partial automation was automated longitudinal control ten metres behind the truck in front, with the driver having to steer; and full automation was automated longitudinal and lateral control. Each condition was simulated in three situations: light traffic, heavy traffic, and heavy traffic plus fog.ResultsThe experiment demonstrated that automation affects workload. For all workload measures, partial automation produced higher workload than did the full-automation or baseline condition. The two measures capturing trust, i.e., the Human Trust in Automated Systems Scale (HTASS) and Cooper–Harper Scales of Workload, Temporal Load, Situation Awareness, and Trust, were consistent and indicated that trust was highest under the baseline condition, with little difference between partial and full automation. Driver acceptance of both levels of automation was lower than acceptance of baseline. Drivers rated their situation awareness higher for both partial and full automation than for baseline, although both levels of automation led to higher sleepiness.ConclusionsWorkload was higher for partial than for full automation or the baseline condition. Trust and acceptance were generally highest in the baseline condition, and did not differ between partial and full automation. Drivers may believe that they have more situation awareness during automated driving than they actually do. Both levels of automation led to a higher degree of sleepiness than in the baseline condition. The challenge when implementing truck platooning is to develop a system, including human–machine interaction (HMI), that does not overburden the driver, properly addresses driver sleepiness, and satisfies current legislation. The system also must be trusted and accepted by drivers. To achieve this, the development of well-designed HMI will be crucial.

Highlights

This paper builds our knowledge of truck driver behaviour in and experience of automated truck platooning, focusing on the effect of partially and fully automated truck platoons on driver workload, trust, acceptance, performance, and sleepiness
Looking at the effect of automation level on workload measured by ASWAT and Driver Activity Load Index (DALI), the results indicate that automation significantly affected DALI, i.e., F(2, 36) = 9.57, p < 0.01, η2 = 0.35
Post-hoc tests for the ASWAT indicated marginally higher responses in the partially automated than baseline condition (p = 0.08), no significant difference between responses in the baseline and fully automated conditions (p = 0.96), and

Summary

Introduction

This paper builds our knowledge of truck driver behaviour in and experience of automated truck platooning, focusing on the effect of partially and fully automated truck platoons on driver workload, trust, acceptance, performance, and sleepiness. Methods Twenty-four male drivers experienced three conditions in a truck driving simulator, i.e., baseline, partial automation, and full automation: the baseline condition was driving with standard cruise control; partial automation was automated longitudinal control ten metres behind the truck in front, with the driver having to steer; and full automation was automated longitudinal and lateral control. Each condition was simulated in three situations: light traffic, heavy traffic, and heavy traffic plus fog. While the technical issues are being researched and prototypes are being prepared for on-road evaluations, we still lack knowledge of the effects of these technologies on the driver, vehicle, and driver–vehicle interaction.

Methods

Results

Discussion

Conclusion