Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/24326
Title: Measuring working memory load effects on electrophysiological markers of attention orienting during a simulated drive
Authors: ROSS, Veerle 
Vossen, A.
Smulders, F.
RUITER, Rob 
BRIJS, Tom 
BRIJS, Kris 
WETS, Geert 
JONGEN, Ellen 
Issue Date: 2018
Source: ERGONOMICS, 61 (3), pp. 429-443
Abstract: Intersection accidents result in a significant proportion of road fatalities, and attention allocation likely plays a role. Attention allocation may depend on (limited) working memory (WM) capacity. Driving is often combined with tasks increasing WM load, consequently impairing attention orienting. This study (n = 22) investigated WM load effects on event-related potentials (ERPs) related to attention orienting. A simulated driving environment allowed continuous lane-keeping measurement. Participants were asked to orient attention covertly towards the side indicated by an arrow, and to respond only to moving cars appearing on the attended side by pressing a button. WM load was manipulated using a concurrent memory task. ERPs showed typical attentional modulation (cue: contralateral negativity, LDAP; car: N1, P1, SN and P3) under low and high load conditions. With increased WM load, lane-keeping performance improved, while dual task performance degraded (memory task: increased error rate; orienting task: increased false alarms, smaller P3). Practitioner Summary: Intersection driver-support systems aim to improve traffic safety and flow. However, in-vehicle systems induce WM load, increasing the tendency to yield. Traffic flow reduces if drivers stop at inappropriate times, reducing the effectiveness of systems. Consequently, driver-support systems could include WM load measurement during driving in the development phase.
Notes: Ross, V (reprint author), Hasselt Univ, Transportat Res Inst IMOB, Sch Mobil Sci, Diepenbeek, Belgium. veerle.ross@uhasselt.be
Keywords: attention orienting; working memory load; event-related potentials; driving simulation
Document URI: http://hdl.handle.net/1942/24326
ISSN: 0014-0139
e-ISSN: 1366-5847
DOI: 10.1080/00140139.2017.1353708
ISI #: 000423595800008
Rights: © 2017 Informa UK Limited, trading as Taylor & Francis Group
Category: A1
Type: Journal Contribution
Validations: ecoom 2019
Appears in Collections:Research publications

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