SAFETYLIT WEEKLY UPDATE

We compile citations and summaries of about 400 new articles every week.
RSS Feed

HELP: Tutorials | FAQ
CONTACT US: Contact info

Search Results

Journal Article

Citation

Pradhan AK, Crossman J, Sypniewski A. Proc. Int. Driv. Symp. Hum. Factors Driv. Assess. Train. Veh. Des. 2019; 2019: 280-286.

Copyright

(Copyright © 2019, University of Iowa Public Policy Center)

DOI

unavailable

PMID

unavailable

Abstract

Advanced technologies such as adaptive cruise control and lane keeping are key components of SAE Level 2 vehicle automation. As such automation becomes widespread, drivers may be less engaged in driving because they assume that vehicles can safely mitigate risks. However, L2 automation cannot handle the full spectrum of driving situations and will require manual control in many situations. Drivers unprepared to take control may make suboptimal, delayed, or dangerous decisions during and after reengaging with the driving task. This highlights the need for efficient ways to help drivers re-engage with driving. This paper describes an evaluation of a conceptual driver engagement system that combined driver data with contextual data to communicate appropriate information during L2 operations. The system was compared to a traditional, staged-alert system that only monitored driver gaze with no contextual information.

RESULTS indicate higher situation awareness, higher levels of trust and satisfaction, no increase in workload, with evidence of improve off-road glance behaviors when driving with the conceptual system. These findings can help inform further development and testing of driver engagement approaches using driver monitoring.

Available:
https://drivingassessment.uiowa.edu/sites/drivingassessment.uiowa.edu/files/da2019_44_anujpradhan2_final.pdf


Language: en

NEW SEARCH


All SafetyLit records are available for automatic download to Zotero & Mendeley
Print