title: Impact of totally and partially predictive alert in distracted and undistracted subjects: An event related potential study.
abstract: Rear-end collisions represent about 30% of all car crashes and generate a significant economic cost for society. Driver inattention has been identified as the most important contributing factor in rear-end collisions. One possible countermeasure is the use of systems that warn drivers of potential collisions. Nevertheless, because of technical constraints, the conception of perfect warning systems is difficult to achieve and technical literature shows that these kinds of systems can be prone to false alerts or misses. The main objective of this study is to assess the impact of such a warning system on the processing of a relevant driving visual cue while taking into account the reliability of the system and the attentional state of the participants. For this, we designed a laboratory experiment during which we recorded behavioral data and brain activity (event related potential, ERP) following the detection of a visual target. Three warning conditions were designed: (1) no alert was presented before the visual target; (2) an auditory alert was presented before each target; (3) an alert was presented before the target in 70% of the trials (15% only had the alert without the target, and 15% only had the target without the alert). In addition, participants had to perform this visual detection task either alone (simple task) or with a concurrent problem-solving task (dual task). Behavioral and electrophysiological data contribute to revealing (1) that there is a behavioral gain induced by the alert and (2) that this gain is at least linked with a time-saving aspect at both the sensory and cognitive stages of neural information processing. Nevertheless, this impact depends on the attentional states of the participant and on the reliability of the alert.
authors: University of Lyon, IFSTTAR, LESCOT, F-69675 Bron, France. alexandra.fort@ifsttar.fr
authors: Alexandra
authors: A
authors: Fort
authors: Boris
authors: B
authors: Collette
authors: Mercedes
authors: M
authors: Bueno
authors: Philippe
authors: P
authors: Deleurence
authors: Arnaud
authors: A
authors: Bonnard
mesh_terms: D000063:Accidents, Traffic / Q000523:psychology*; D000328:Adult; D000704:Analysis of Variance; D001288:Attention / Q000502:physiology*; D003198:Computer Simulation; D003463:Cues; D004569:Electroencephalography; D005071:Evoked Potentials; D006801:Humans; D008297:Male; D012307:Risk Factors