Driving performance impairments due to hypovigilance on monotonous roads

Centre for Accident Research and Road Safety - Queensland, Queensland University of Technology, 130 Victoria Park Road, Kelvin Grove 4059, Queensland, Australia.
Accident; analysis and prevention (Impact Factor: 1.65). 11/2011; 43(6):2037-46. DOI: 10.1016/j.aap.2011.05.023
Source: PubMed


Drivers' ability to react to unpredictable events deteriorates when exposed to highly predictable and uneventful driving tasks. Highway design reduces the driving task mainly to a lane-keeping manoeuvre. Such a task is monotonous, providing little stimulation and this contributes to crashes due to inattention. Research has shown that driver's hypovigilance can be assessed with EEG measurements and that driving performance is impaired during prolonged monotonous driving tasks. This paper aims to show that two dimensions of monotony - namely road design and road side variability - decrease vigilance and impair driving performance. This is the first study correlating hypovigilance and driver performance in varied monotonous conditions, particularly on a short time scale (a few seconds). We induced vigilance decrement as assessed with an EEG during a monotonous driving simulator experiment. Road monotony was varied through both road design and road side variability. The driver's decrease in vigilance occurred due to both road design and road scenery monotony and almost independently of the driver's sensation seeking level. Such impairment was also correlated to observable measurements from the driver, the car and the environment. During periods of hypovigilance, the driving performance impairment affected lane positioning, time to lane crossing, blink frequency, heart rate variability and non-specific electrodermal response rates. This work lays the foundation for the development of an in-vehicle device preventing hypovigilance crashes on monotonous roads.


Available from: Gregoire S. Larue, Feb 05, 2015
  • Source
    • "The authors claim the monotonous environment of a highway drive and the long time-on-task as causes for the decrement. Other researchers [16] found similar detrimental effects of monotony on lane positioning, time to lane crossing, blink frequency, heart rate variability and non-specific electro-dermal response rates in a driving simulator study. Hence, passive fatigue seems to be a relevant cause for impaired driving performance. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Besides resource depletion caused by being actively engaged in a task, there are several signs that passive monitoring, monotony and passive fatigue can also induce vigilance decrement. Partially automated driving represents such a passive situation as the driver's only task is to monitor the system. In this work, we investigate the decrement of vigilance during a partially automated highway drive in a driving simulator. Indicators used to assess the vigilance state was a reaction time task, passive fatigue was measured by eye tracking and a mind wandering questionnaire. 20 participants drove in a driving simulator for 42.5 min on a six-lane highway with partial automation activated. We found no significant effects of time-on-task on the reaction times, but significant effects on eye tracking parameters (blink frequency, blink duration, pupil diameter) and increased mind wandering. The results show that fatigue can occur without active task engagement, but future studies have to clarify the consequences in terms of reactions to critical events.
    12/2015; 3:2403-2409. DOI:10.1016/j.promfg.2015.07.499
    • "Task monotony is considered as a factor encouraging drowsiness at the wheel, alongside, notably, age, whether medication is being taken and the temperature inside the vehicle (Dunn and Williamson, 2011; Larue et al., 2011; Sallinen et al., 2004). Several authors found that an exposure of 20 to 40 minutes is enough to induce drowsiness (Thiffault and Bergeron, 2003; Hefner et al., 2009). "

    6th International Conference on Applied Human Factors and Ergonomics, Las Vegas, Nevada; 07/2015
    • "Previous analyses focused on analyzing the evolution of alertness on monotonous roads and its effects on surrogate measures. They showed that, during low alertness levels, both heart rate and non-specific electrodermal activity decreased, eye activity was impaired, (as evidenced by increased blink frequency and eye closure) and driving performance was impaired as shown by lower standard deviation of lane position and reduced time to line crossing [3]. We aimed in this paper to model and predict alertness decrement before it impacts on driver behavior. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Impaired driver alertness increases the likelihood of a driver making mistakes and reacting too late to unexpected events. This is a particular concern on monotonous roads, where a drivers attention can decrease rapidly. Although effective countermeasures dont currently exist, the development of in-vehicle sensors opens avenues for monitoring driving behavior in real time. The aim of this study is to predict driver alertness levels using surrogate measures collected from in-vehicle sensors. Electroencephalographic activity is used as a reference to evaluate alertness. Based on a sample of 25 drivers, the authors collected data in a driving simulator instrumented with an eye-tracking system, a heart-rate monitor, and an electrodermal activity device. They tested various classification models, from linear regressions to Bayesians and data mining techniques. Results indicate that neural networks were the most efficient model for detecting lapses in alertness. Findings also show that reduced alertness can be predicted up to five minutes in advance with 90 percent accuracy using surrogate measures such as time to line crossing, blink frequency, and skin conductance level. Such a method could be used to warn drivers of their alertness levels through the development of an in-vehicle device that monitors, in real time, driver behavior on highways.
    IEEE Pervasive Computing 04/2015; 14(2):78-85. DOI:10.1109/MPRV.2015.38 · 1.55 Impact Factor
Show more