We investigated engagement in single vs. multiple types of secondary tasks in distraction-affected, safety-critical events (SCEs), i.e., crashes/near-crashes, and baselines reported in the Naturalistic Engagement in Secondary Tasks (NEST) dataset. NEST was created from Second Strategic Highway Research Program (SHRP2) data for studying distractions in detail. Early descriptive analysis on NEST found that most distraction-affected SCE and baseline epochs (10 s long) include more than one type of secondary task, suggesting that a considerable number of drivers may be engaging in multiple secondary activities within a relatively short time frame, potentially being exposed to increased demands brought on by multi-tasking and task-switching. We conducted inferential statistics on NEST focusing on engagement in single vs. multiple types of tasks across SCEs and baselines. A logit model was built to compare the odds of engaging in single vs. multiple types of tasks with the following predictors: event type (SCE, baseline), environmental demand, GPS speed, and driver age. The last three predictors were included to capture the driving demands experienced, which may have impacted drivers’ task engagement behavior. Odds of engagement in multiple types of secondary tasks was higher in SCEs than baselines. Furthermore, with marginal statistical significance, drivers 65 years and over were less likely to engage in multiple types of secondary tasks than younger drivers. Overall, engagement in multiple secondary task types is more prevalent in SCEs. Most crash risk studies to date have reported the effects associated with one type of secondary task. However, it appears that these effects may be confounded by the presence of other secondary tasks.


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    Titel :

    Prevalence of Engagement in Single versus Multiple Types of Secondary Tasks: Results from the Naturalistic Engagement in Secondary Task (NEST) Dataset


    Weitere Titelangaben:

    Transportation Research Record: Journal of the Transportation Research Board


    Beteiligte:
    Risteska, Martina (Autor:in) / Donmez, Birsen (Autor:in) / W. Chen, Huei-Yen (Autor:in) / Modi, Miti (Autor:in)


    Erscheinungsdatum :

    08.08.2018




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch