Individual differences in cognitive functioning predict effectiveness of a heads-up lane departure warning for younger and older drivers

Abstract

The effectiveness of an idealized lane departure warning (LDW) was evaluated in an interactive fixed base driving simulator. Thirty-eight older (mean age = 77 years) and 40 younger drivers (mean age = 35 years) took four different drives/routes similar in road culture composition and hazards encountered with and without LDW. The four drives were administered over visits separated approximately by two weeks to examine changes in long-term effectiveness of LDW. Performance metrics were number of LDW activations and average correction time to each LDW. LDW reduced correction time to re-center the vehicle by 1.34 seconds on average (95% CI = 1.12–1.57 seconds) but did not reduce the number of times the drivers drifted enough in their lanes to activate the system (LDW activations). The magnitude of reductions in average correction RT was similar for older and younger drivers and did not change with repeated exposures across visits. The contribution of individual differences in basic visual and motor function, as well as cognitive function to safety gains from LDW was also examined. Cognitive speed of processing predicted lane keeping performance for older and younger drivers. Differences in memory, visuospatial construction, and executive function tended to predict performance differences among older but not younger drivers. Cognitive functioning did not predict changes in the magnitude of safety benefits from LDW over time. Implications are discussed with respect to real-world safety systems.

Right-lateralised lane keeping in young and older British drivers

“…The ability to quickly and accurately process, and act upon, spatial information is an essential component of safe driving in young and older adults alike. Research surrounding the use of in-car automatic lane departure warning software has identified that lane-departure warnings are generally activated more often in older adults than in young [ 39 ]. However, spatial asymmetries are difficult to study in driving behaviour due to the potential confound of learned behaviour associated with left- or right-lane driving experience.…”

Smart In-Vehicle Technologies and Older Drivers: A Scoping Review

“…Sample sizes ranged from 11 to 257 participants. Studies were conducted in nine countries including the United States ( n = 14) (Aksan et al, 2017; Aksan et al, 2015; Becic, Manser, Drucker, & Donath, 2013; Brown, He, Roe, & Schnell, 2010; Kidd & Buonarosa, 2017; Kramer, Cassavaugh, Horrey, Becic, & Mayhugh, 2007; Lester et al, 2015; D. C. Marshall, Wallace, Torner, & Birt-Leeds, 2010, 2011; Mok, Johns, Gowda, Sibi, & Ju, 2016; Oh, Ko, & Ji, 2016; Reimer, Mehler, & Coughlin, 2016; Strayer, Cooper, Turrill, Coleman, & Hopman, 2016; Sullivan, Tsimhoni, & Bogard, 2008), Netherlands ( n = 4) (Davidse, Hagenzieker, van Wolffelaar, & Brouwer, 2009; Dotzauer, Caljouw, de Waard, & Brouwer, 2013, 2015; Dotzauer, de Waard, et al, 2015), Germany ( n = 3) (Gelau, Sirek, & Dahmen-Zimmer, 2011; Haberstroh, Klingender, Ramakers, & Henning, 2010; Kazazi, Winkler, & Vollrath, 2015), Japan ( n = 2) (Hibino, Kobayashi, Daimon, & Oda, 2013; Saito & Raksincharoensak, 2016), Canada ( n = 1) (Caird, Chisholm, & Lockhart, 2008), United Kingdom ( n = 1) (Guo, Blythe, Edwards, Pavkova, & Brennan, 2015), France ( n = 1) (Bruyas & Simões, 2010), Australia ( n = 1) (Yi, Lee, Parsons, & Falkmer, 2014), and Czech Republic ( n = 1) (Novotny & Bouchner, 2011).…”

“…Sample sizes ranged from 11 to 257 participants. Studies were conducted in nine countries including the United States (n = 14)(Aksan et al, 2017;Aksan et al, 2015;Becic, Manser, Drucker, & Donath, 2013;Brown, He, Roe, & Schnell, 2010;Kidd & Buonarosa, 2017;…”

Regression and boosting methods to inform precisionized treatment rules using data from crossover studies

“…These estimates are based on a best-case scenario where all drivers "react ideally to the warnings issued by the system" (Kuehn et al, 2009). In practice, the actual observed safety impact of ADAS is dependent on "human factor issues" such as driving behavior and capabilities (Aksan et al, 2017 andKuehn et al, 2009). Individual driving factors must be adequately accounted for in order to more accurately quantify the safety potential of ADAS (Kuehn et al, 2009).…”

“…Determining the population specific safety improvement of ADAS would be relevant to several industries. There is preliminary evidence to suggest ADAS may not benefit all drivers or may need to be altered for certain populations (Aksan et al, 2015, Aksan et al, 2016, and Aksan et al, 2017. Vehicle manufacturers and insurance providers could use the information to tailor safety warnings to individual drivers.…”