Effects of mental demands on situation awareness during platooning: A driving simulator study

Abstract

Previous research shows that drivers of automated vehicles are likely to engage in visually demanding tasks, causing impaired situation awareness. How mental task demands affect situation awareness is less clear. In a driving simulator experiment, 33 participants completed three 40-min runs in an automated platoon, each run with a different level of mental task demands. Results showed that high task demands (i.e., performing a 2-back task, a working memory task in which participants had to recall a letter, presented two letters ago) induced high self-reported mental demands (71% on the NASA Task Load Index), while participants reported low levels of self-reported task engagement (measured with the Dundee Stress State Questionnaire) in all three task conditions in comparison to the pre-task measurement. Participants' situation awareness, as measured using a thinkout-loud protocol, was affected by mental task demands, with participants being more involved with the mental task itself (i.e., to remember letters) and less likely to comment on situational features (e.g., car, looking, overtaking) when task demands increased. Furthermore, our results shed light on temporal effects, with heart rate decreasing and self-constructed mental models of automation growing in complexity, with run number. It is concluded that mental task demands reduce situation awareness, and that not only type-of-task, but also time-on-task, should be considered in Human Factors research of automated driving.

Acclimatizing to automation: Driver workload and stress during partially automated car following in real traffic

“…Fig. 8 provides a comparison between the results of the current on-road study and two previous driving simulator studies (Heikoop et al, 2017;Heikoop, De Winter, Van Arem, & Stanton, 2018). The two simulator studies are similar to the current study as all three studies involved car following in an automated car, drives of 30-40 min duration, identical ECG equipment, and a secondary button-pressing task (detecting bridges in the present on-road study, detecting red cars in the simulator studies).…”

Driving Style: How Should an Automated Vehicle Behave?

“…People tend to produce highly different mental models of AVs (not always correct or comprehensive), and gradually add concepts and links as they experience journeys [84]. It is possible to design procedures that encourage appropriate trust, for example, communicating to users the system capabilities and limitations beforehand [12].…”

Driving with and without automation on the motorway – an observational study

“…Jenness et al (2008) in a survey among early adopters of in-vehicle technology found that system owners often do not understand the limitations of the systems and manufacturers' warnings. Heikoop et al (2018) concluded that mental models ' … are not self-correcting, but rather become increasingly complex with time', suggesting that if drivers don't receive prior information or training on the automated driving system they use, they could retain an inaccurate mental model. 3.…”

“…Based on a review of earlier studies, Stanton et al (2001) conclude that 'loss of situational awareness is correlated with poor system performance' and 'people who have lost situational awareness may be slower to detect problems with the system they are controlling as well as requiring additional time to diagnose problems and conduct remedial activities when they are finally detected ' (p.199). Heikoop et al (2018) in a driving simulator study, investigated the impact of a mental secondary task on driver situation awareness during platoon driving and found that mental demand impaired situation awareness. Based on a meta-analysis and narrative review of simulator and on-road studies, de Winter et al (2014) concluded that highly automated driving can improve situation awareness compared to manual driving if drivers are motivated or instructed to detect objects in the environment.…”

“…The impact of peripheral visual information in alleviating motion sickness when engaging in nondriving tasks in fully automated driving (Karjanto et al, 2018) Driver response when experiencing a safety critical take-over request (Blommer et al, 2017;Merat et al, 2014b;Shen & Neyens, 2017;Vogelpohl et al, 2018;Zeeb et al, 2015); Necessary time for drivers to achieve situation awareness (Agrawal et al, 2017;Vlakveld et al, 2018); How situation awareness in transfer of control is affected by driver fatigue, stress, (Neubauer et al, 2012); by workload (de Winter et al, 2014); by mental task demands (Heikoop et al, 2018); by alert cue specificity (Forster et al, 2017;Wright et al, 2017); and by driver experience (Wright et al, 2016b); Resuming control from the automation (Bueno et al, 2016;Clark & Jing Feng 2017;Gold et al, 2015;Merat & Lee, 2012;Merat et al, 2014;Merat et al, 2014b;Naujoks et al, 2018;Navarro et al, 2016;Petermeijer et al, 2017;Payre et al, 2017;Radlmayr et al, 2014;Zeeb et al, 2017;Zhang et al, 2018); Post-transition driving performance (Berthelon & Gineyt, 2014;Miller et al, 2015;Mok et al, 2015;Naujoks et al, 2015;Naujoks, Purucker, et al 2017;Radlmayr et al, 2018;Strand et al, 2014;…”