Exploring the usage of supervised driving automation in naturalistic conditions

Exploring the usage of supervised driving automation in naturalistic conditions

Stapel, J.C.J. (TU Delft Intelligent Vehicles)
Happee, R. (TU Delft Intelligent Vehicles)
Christoph, Michiel (Stichting Wetenschappelijk Onderzoek Verkeersveiligheid (SWOV))
van Nes, C.N. (TU Delft Applied Ergonomics and Design; Stichting Wetenschappelijk Onderzoek Verkeersveiligheid (SWOV))
Martens, Marieke (Eindhoven University of Technology; TNO)

2022

This study reports usage of supervised automation and driver attention from longitudinal naturalistic driving observations. Automation inexperienced drivers were provided with instrumented vehicles with adaptive cruise control (ACC) and lane keeping (LK) features (SAE level 2). Data was collected comparing one month of driving without support to two months where drivers were instructed to use automation as desired. On highways, level 2 automation was used respectively 63% and 57% of the time by Tesla and BMW users, with peak usage during slow stop-and-go traffic (0–30 km/h) and higher speeds (>80 km/h). On roads with speed limits below 70 km/h, automation was used less than 8%, and use on urban roads was incidental rather than habitual. Automation usage increased with time in trip, but no clear time of day effects were found. Head pose data could not classify driver attention, and we recommend gaze tracking in future studies. Head pose deviation was selected as alternative indicator for monitoring activity. Comparing among forms of automation usage on the highway, head heading deviation was smallest during ACC use, but did not differ between automation and baseline manual driving. Head heading deviation during manual driving was smaller in the baseline than the experimental phase, which suggests that motives for manual highway driving may be attention related. Automation usage did not change much over the first 12 weeks of the experimental condition, and there were no longitudinal changes in head pose deviation.

Automation use
Driver attention

http://resolver.tudelft.nl/uuid:0d9fabb2-eb4f-46df-8403-de4a9d44d189

https://doi.org/10.1016/j.trf.2022.08.013

1369-8478

Transportation Research. Part F: Traffic Psychology and Behaviour, 90, 397-411

Institutional Repository

journal article

© 2022 J.C.J. Stapel, R. Happee, Michiel Christoph, C.N. van Nes, Marieke Martens