Driver behavior and workload in an on-road automated vehicle

Jork Stapel, Freddy Mullakkal Babu, Riender Happee

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

166 Downloads (Pure)


Driver mental underload is an important concern in the operational safety of automated driving. In this study, workload was evaluated subjectively (NASA RTLX) and objectively (auditory detection-response task) on Dutch public highways (~150km) in a Tesla Model S comparing manual and supervised automated driving with moderators automation experience and traffic complexity. Participants (N=16) were either automationinexperienced drivers or automation-experienced Tesla owners. Complexity ranged from an engaging environment with a road geometry stimulating continuous traffic interaction, and a monotonic environment with lower traffic density and a simple road geometry. Perceived and objective workload increased with traffic complexity. Automation use reduced perceived workload in both environments for automation-experienced drivers, but not for inexperienced drivers. However, the DRT did not reveal a reduced attentional demand with automation. This suggests that attentive monitoring requires a similar attentional demand as manual driving. The findings highlight the relevance of using system-experienced participants and the relevance of on-road testing for behavioral validity.
Original languageEnglish
Title of host publicationProceedings Road Safety & Simulation International Conference 2017
Number of pages10
Publication statusPublished - 2017
EventRSS2017: Road Safety and Simulation International Conference 2017 - Grand Hotel Amrâth Kurhaus, The Hague, Netherlands
Duration: 17 Oct 201719 Oct 2017


ConferenceRSS2017: Road Safety and Simulation International Conference 2017
Abbreviated titleRSS 2017
CityThe Hague
OtherThe Road Safety and Simulation conference series was established in Rome in 2007, and has since then provided a bi-annual platform for researchers and professionals from various disciplines to share their expertise and latest insights in the field of road safety and simulation. Delft University of Technology (TU Delft) is delighted to host the 2017 Road Safety and Simulation (RSS) international conference. RSS2017 will be organised in collaboration with the Dutch Institute for Road Safety Research (SWOV). The RSS2017 conference covers a wide area of topics. Furthermore we introduce a special theme focusing on advancing the safety of all road users with special attention for vulnerable road users. Especially, in the upcoming era of advanced technologies and vehicle automation new safety challenges have emerged. The road infrastructure design plays a critical role in accommodating these challenges.
Internet address

Bibliographical note

Paper no. 284


  • Automated Driving
  • On-road
  • Workload
  • Experience
  • Underload


Dive into the research topics of 'Driver behavior and workload in an on-road automated vehicle'. Together they form a unique fingerprint.

Cite this