Citation

Eriksson A, Petermeijer SM, Zimmermann M, de Winter JCF, Bengler KJ, Stanton NA. IEEE Trans. Hum. Mach. Syst. 2019; 49(1): 20-31.

Copyright

(Copyright © 2019, Institute of Electrical and Electronics Engineers)

DOI

10.1109/THMS.2018.2883862

PMID

unavailable

Abstract

This paper assessed four types of human-machine interfaces (HMIs), classified according to the stages of automation proposed by Parasuraman et al. ["A model for types and levels of human interaction with automation," IEEE Trans. Syst. Man, Cybern. A, Syst. Humans, vol. 30, no. 3, pp. 286-297, May 2000]. We hypothesized that drivers would implement decisions (lane changing or braking) faster and more correctly when receiving support at a higher automation stage during transitions from conditionally automated driving to manual driving. In total, 25 participants with a mean age of 25.7 years (range 19-36 years) drove four trials in a driving simulator, experiencing four HMIs having the following different stages of automation: baseline (information acquisition-low), sphere (information acquisition-high), carpet (information analysis), and arrow (decision selection), presented as visual overlays on the surroundings. The HMIs provided information during two scenarios, namely a lane change and a braking scenario.

RESULTS showed that the HMIs did not significantly affect the drivers' initial reaction to the take-over request. Improvements were found, however, in the decision-making process: When drivers experienced the carpet or arrow interface, an improvement in correct decisions (i.e., to brake or change lane) occurred. It is concluded that visual HMIs can assist drivers in making a correct braking or lane change maneuver in a take-over scenario. Future research could be directed toward misuse, disuse, errors of omission, and errors of commission.

Language: en

Keywords

Augmented reality; automated driving; Automation; automation-to-manual transitions; braking; braking scenario; correct braking; decision making; Decision making; decision selection; decision-making process; driver decision; driver information systems; driver support systems; driving simulator; human factors; human interaction; human performance; human-machine interfaces; information acquisition; information analysis; Information analysis; lane change; man-machine systems; manual driving; road safety; road traffic; road vehicles; Task analysis; traffic engineering computing; transitions of control; Vehicles; visual HMI; Visualization; Wheels