A Reference Model for Driver Attention in Automation: Glance Behavior Changes During Lateral and Longitudinal Assistance
Artikel i vetenskaplig tidskrift, 2019

This paper introduces a reference model of glance behavior for driving safety assessment. This model can improve the design of automated and assistive systems. Technological limitations have previously hindered the use of unobtrusive eye trackers to measure glance behavior in naturalistic conditions. This paper presents a comprehensive analysis of eye-tracking data collected in a naturalistic field operation test, using an eye tracker that proved to be robust in real-world driving scenarios. We describe a post-processing technique to enhance the quality of naturalistic eye-tracker data, propose a data-analysis procedure that captures the important features of glance behavior, and develop a model of glance behavior (based on distribution fitting), which was lacking in the literature. The model and its metrics capture key defining characteristics of, and differences between, on- and off-path glance distributions, and during manual driving and driving with adaptive cruise control and lane keeping aid active. The results show that drivers' visual response is tightly coupled to the driving context (vehicle automation, car-following, and illumination).


Alberto Morando

Chalmers, Mekanik och maritima vetenskaper, Fordonssäkerhet

Trent Victor

Chalmers, Mekanik och maritima vetenskaper, Fordonssäkerhet

Marco Dozza

Chalmers, Mekanik och maritima vetenskaper, Fordonssäkerhet

IEEE Transactions on Intelligent Transportation Systems

1524-9050 (ISSN) 1558-0016 (eISSN)

Vol. 20 8 2999-3009 8482505

Human Factors of Automated Driving (HFAUTO)

Europeiska kommissionen (EU) (EC/FP7/605817), 2013-11-01 -- 2017-10-31.

Quantitative Driver Behaviour Modelling for Active Safety Assessment Expansion (QUADRAE)

VINNOVA (2015-04863), 2016-01-01 -- 2019-12-31.




Transportteknik och logistik

Övrig annan teknik




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