Birsen Donmez

The Impact of Distraction Mitigation Strategies on Driving Performance

Objectives: An experiment was conducted to assess the effects of distraction mitigation strategies on drivers? performance and productivity while engaged in an in-vehicle information system task. Background: Previous studies show that in-vehicle tasks undermine driver safety and there is a need to mitigate driver distraction. Method: An advising strategy that alerts drivers to potential dangers and a locking strategy that prevents the driver from continuing the distracting task were presented to 16 middle-aged and 12 older drivers in a driving simulator in two modes (auditory, visual) and two road conditions (curves, braking events). Results: Distraction was a problem for both age groups. Visual distractions were more detrimental than auditory ones for curve negotiation, as depicted by more erratic steering, F(6, 155) = 26.76, p < .05. Drivers did brake more abruptly under auditory distractions, but this effect was mitigated by both the advising, t(155) = 8.37, p < .05, and locking strategies, t(155) = 8.49, p < .05. The locking strategy also resulted in longer minimum time to collision for middle-aged drivers engaged in visual distractions, F(6, 138) = 2.43, p < .05. Conclusions: Adaptive interfaces can reduce abrupt braking on curve entries resulting from auditory distractions and can also improve the braking response for distracted drivers. Application: These strategies can be incorporated into existing in-vehicle systems, thus mitigating the effects of distraction and improving driver performance.

Mitigating driver distraction with retrospective and concurrent feedback.

OBJECTIVES An experiment was conducted to assess the effects of retrospective and combined retrospective and concurrent feedback on driver performance and engagement in distracting activities. BACKGROUND A previous study conducted by the authors showed that concurrent (or real time) feedback can help drivers better modulate their distracting activities. However, research also shows that concurrent feedback can pose additional distractions due to the limited time and resources available during driving. Retrospective feedback, which is presented at the end of a trip (i.e., post-drive), can include additional information on safety critical situations during a trip and help the driver learn safe driving habits. METHOD A driving simulator study was conducted with 48 participants and 3 conditions: retrospective feedback, combined feedback (both retrospective and concurrent), and no feedback (baseline case). RESULTS The feedback conditions (retrospective and combined) resulted in faster response to lead vehicle braking events as depicted by shorter accelerator release times. Moreover, combined feedback also resulted in longer glances to the road. CONCLUSIONS The results suggest that both feedback types have potential to improve immediate driving performance and driver engagement in distractions. APPLICATION Combined feedback holds the most promise for mitigating the effects of distraction from in-vehicle information systems.

Differences in Off-Road Glances: Effects on Young Drivers’ Performance

Young drivers display more risk-taking behavior than other age groups. Performing distracting tasks is one such risky behavior that is observed among young drivers. However, due to inexperience, young drivers may not be able to appropriately compensate for the effects of distractions. A driving simulator study with 53 young drivers (aged 18–21) was conducted to assess the level of engagement with an in-vehicle secondary task. A cluster analysis revealed three groups of drivers that differed based on eye glance behavior and driving performance: drivers with low-risk, moderate-risk, and high-risk behavior. A subset of these drivers was provided with feedback to help modulate their distracting activities with the riskiest group benefitting most from feedback as indicated by enhanced glance behavior and driving performance. The findings have implications for developing better crash countermeasures to mitigate the effects of distraction.

Modeling Workload Impact in Multiple Unmanned Vehicle Supervisory Control

Discrete-event simulations for futuristic unmanned vehicle (UV) systems enable a cost- and time-effective methodology for evaluating various autonomy and human-automation design parameters. Operator mental workload is an important factor to consider in such models. We suggest that the effects of operator workload on system performance can be modeled in such a simulation environment through a quantitative relation between operator attention and utilization, i.e., operator busy time used as a surrogate real-time workload measure. To validate our model, a heterogeneous UV simulation experiment was conducted with 74 participants. Performance-based measures of attention switching delays were incorporated in the discrete-event simulation model by UV wait times due to operator attention inefficiencies (WTAIs). Experimental results showed that WTAI is significantly associated with operator utilization (UT) such that high UT levels correspond to higher wait times. The inclusion of this empirical UT-WTAI relation in the discrete-event simulation model of multiple UV supervisory control resulted in more accurate replications of data, as well as more accurate predictions for alternative UV team structures. These results have implications for the design of future human-UV systems, as well as more general multiple task supervisory control models.

Evaluation criteria for human-automation performance metrics

Previous research has identified broad metric classes for human-automation performance to facilitate metric selection, as well as understanding and comparison of research results. However, there is still lack of an objective method for selecting the most efficient set of metrics. This research identifies and presents a list of evaluation criteria that can help determine the quality of a metric in terms of experimental constraints, comprehensive understanding, construct validity, statistical efficiency, and measurement technique efficiency. Future research will build on these evaluation criteria and existing generic metric classes to develop a cost-benefit analysis approach that can be used for metric selection.

Auditory decision aiding in supervisory control of multiple unmanned aerial vehicles.

Objective: This article is an investigation of the effectiveness of sonifications, which are continuous auditory alerts mapped to the state of a monitored task, in supporting unmanned aerial vehicle (UAV) supervisory control. Background: UAV supervisory control requires monitoring a UAV across multiple tasks (e.g., course maintenance) via a predominantly visual display, which currently is supported with discrete auditory alerts. Sonification has been shown to enhance monitoring performance in domains such as anesthesiology by allowing an operator to immediately determine an entity’s (e.g., patient) current and projected states, and is a promising alternative to discrete alerts in UAV control. However, minimal research compares sonification to discrete alerts, and no research assesses the effectiveness of sonification for monitoring multiple entities (e.g., multiple UAVs). Method: The authors conducted an experiment with 39 military personnel, using a simulated setup. Participants controlled single and multiple UAVs and received sonifications or discrete alerts based on UAV course deviations and late target arrivals. Results: Regardless of the number of UAVs supervised, the course deviation sonification resulted in reactions to course deviations that were 1.9 s faster, a 19% enhancement, compared with discrete alerts. However, course deviation sonifications interfered with the effectiveness of discrete late arrival alerts in general and with operator responses to late arrivals when supervising multiple vehicles. Conclusions: Sonifications can outperform discrete alerts when designed to aid operators to predict future states of monitored tasks. However, sonifications may mask other auditory alerts and interfere with other monitoring tasks that require divided attention. Applications: This research has implications for supervisory control display design.

Impact of age and cognitive demand on lane choice and changing under actual highway conditions

Previous research suggests that drivers change lanes less frequently during periods of heightened cognitive load. However, lane changing behavior of different age groups under varying levels of cognitive demand is not well understood. The majority of studies which have evaluated lane changing behavior under cognitive workload have been conducted in driving simulators. Consequently, it is unclear if the patterns observed in these simulation studies carry over to actual driving. This paper evaluates data from an on-road study to determine the effects of age and cognitive demand on lane choice and lane changing behavior. Three age groups (20-29, 40-49, and 60-69) were monitored in an instrumented vehicle. The 40s age group had 147% higher odds of exhibiting a lane change than the 60s group. In addition, drivers in their 60s were less likely to drive on the leftmost lane compared to drivers in their 20s and 40s. These results could be interpreted as evidence that older adults adopt a more conservative driving style as reflected in being less likely to choose the leftmost lane than the younger groups and less likely to change lanes than drivers in their 40s. Regardless of demand level, cognitive workload reduced the frequency of lane changes for all age groups. This suggests that in general drivers of all ages attempt to regulate their behavior in a risk reducing direction when under added cognitive demand. The extent to which such self-regulation fully compensates for the impact of added cognitive demand remains an open question.

The Iowa Graduated Driver Licensing program: effectiveness in reducing crashes of teenage drivers.

PROBLEM Graduated Driver Licensing (GDL) programs vary in the United States in terms of implementation and restrictions. The State of Iowas GDL program is assessed for its effectiveness in reducing crashes among teenage drivers. METHOD Time series analysis was used to evaluate police documented crashes involving 16-, 17-, and 18-year-old drivers over a 10 year period, with an intervention identified at the point of GDL implementation. RESULTS After controlling for seasonal trends and auto-correlative effects, a significant reduction in the crash rate of and 16- and 17-year-old drivers was observed due to the GDL implementation. However, there were no significant reductions in crash rates for 18-year-old drivers. DISCUSSION The analyses suggest that the Iowa GDL program is effective in reducing the crash rates of 16- and 17-year-old drivers but the effects do not sustain for 18-year-old drivers. IMPACT ON INDUSTRY The results suggest that the program appears to be working, however further analysis is needed to determine what factors are preventing lasting effects for these teenage drivers.

Susceptibility to Driver Distraction Questionnaire: development and relation to relevant self-reported measures

Driver distraction significantly impairs performance and increases the likelihood of vehicle crashes. Understanding the underlying reasons for distraction engagement as well as individuals’ susceptibility to various types of distractions is a necessary step in developing effective solutions for mitigating distraction. This paper describes the development and initial evaluation of a questionnaire, the Susceptibility to Driver Distraction Questionnaire (SDDQ), which investigates distraction involvement by making a distinction between voluntary and involuntary engagement in secondary activities, or distractions, as referred to in this paper. The paper presents the theoretical underpinnings, the questionnaire itself, as well as the results of an online survey that examined the reliability and validity of the newly developed questionnaire. The analyses show moderate to high levels of internal consistency among the questionnaire items; this consistency provides support to the reliability of the SDDQ. The results also suggest that self-reported engagement in driver distraction is correlated with other self-reported, unsafe driving behaviors. As expected, personality is associated with attitudes and beliefs that motivate voluntary engagement in distraction, while susceptibility to involuntary distraction is related to cognitive limitations. These results indicate that the SDDQ can potentially be a useful tool to study driver distraction and the underlying reasons for distraction engagement.

Not All Interruptions are Created Equal: Positive Interruptions in Healthcare

Interruptions were studied extensively in the past but with a focus on their negative effects. Although many types of interruptions result in a break-in-task, in some cases interruptions communicate important information associated with patient’s safety. The majority of previous interruption research use a reductionist approach to minimize or prevent interruptions, and minimal attention has been given to the differentiation between positive and negative interruptions. Through the analysis of relevant healthcare literature, this paper first identifies the inconsistencies in the way interruptions are defined, and then categorizes potential sources of negative and positive interruptions.