James Foley

The importance of task duration and related measures in assessing the distraction potential of in-vehicle tasks

The issue of task duration in the assessment of driver distraction has been a controversial topic. In the development of J2364 Navigation and Route Guidance Function Accessibility While Driving, task duration and a related criterion were the most difficult parts of achieving consensus. The current discussion is restricted to a few key criticisms of task duration and duration-related measures of driving performance. We provide data-driven reasons why criticisms of duration-related measures, though important, are not sufficient to negate the value of these measures. Further, we point to naturalistic driving research that indicates it is glances away from the road scene prior to critical events that predominate in real-world crashes and near-misses. Rather than suggesting duration-related measures be abandoned, naturalistic driving research underscores the importance of using driver metrics like total eyes-off-road time as well as single glance durations. Finally, task length is an attribute of a task and HMI design, which can be modified through re-design and therefore will influence duration-related performance. We argue that duration is particularly important as a tool to assess where interventions to limit distraction might be applied.

Creation of the Naturalistic Engagement in Secondary Tasks (NEST) distracted driving dataset

PROBLEM Distracted driving has become a topic of critical importance to driving safety research over the past several decades. Naturalistic driving data offer a unique opportunity to study how drivers engage with secondary tasks in real-world driving; however, the complexities involved with identifying and coding relevant epochs of naturalistic data have limited its accessibility to the general research community. METHOD This project was developed to help address this problem by creating an accessible dataset of driver behavior and situational factors observed during distraction-related safety-critical events and baseline driving epochs, using the Strategic Highway Research Program 2 (SHRP2) naturalistic dataset. The new NEST (Naturalistic Engagement in Secondary Tasks) dataset was created using crashes and near-crashes from the SHRP2 dataset that were identified as including secondary task engagement as a potential contributing factor. Data coding included frame-by-frame video analysis of secondary task and hands-on-wheel activity, as well as summary event information. In addition, information about each secondary task engagement within the trip prior to the crash/near-crash was coded at a higher level. Data were also coded for four baseline epochs and trips per safety-critical event. RESULTS 1,180 events and baseline epochs were coded, and a dataset was constructed. The project team is currently working to determine the most useful way to allow broad public access to the dataset. DISCUSSION We anticipate that the NEST dataset will be extraordinarily useful in allowing qualified researchers access to timely, real-world data concerning how drivers interact with secondary tasks during safety-critical events and baseline driving. PRACTICAL APPLICATIONS The coded dataset developed for this project will allow future researchers to have access to detailed data on driver secondary task engagement in the real world. It will be useful for standalone research, as well as for integration with additional SHRP2 data to enable the conduct of more complex research.

Exploratory factor analysis of adolescent attitudes toward alcohol and risk

This 2-year longitudinal study of 302 high school students in the state of Indiana examined attitudes toward the use of alcohol in 25 potentially hazardous settings, varying from riding in a car, to swimming, to simply drinking at home. Student ratings indicated that they were capable of rationally evaluating alcohol-related risks. Principal components factor analysis identified three factors underlying student responses: propensity/desirability of the behavior, choice/control of the risk, and fear/consequences/likelihood of the risk. Each of these factors was comparable to factors found to be important in past studies of adult risk perception. The finding that self-reported behavioral propensity and desirability were weakly correlated with the measures of perceived risk is of particular interest. Attempts to reduce the use of alcohol by adolescents have traditionally focused on risk awareness. The implication of this study is that intervention programs might be more successful if they focused on modifying perceived value.

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

The effectiveness of an idealized lane departure warning (LDW) was evaluated in an interactive fixed base driving simulator. Thirty-eight older (mean age=77years) and 40 younger drivers (mean age=35years) 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 1.34s on average (95% CI=1.12-1.57s) 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.

Modeling Types of Pedal Applications Using a Driving Simulator

Objective: The aim of this study was to examine variations in drivers’ foot behavior and identify factors associated with pedal misapplications. Background: Few studies have focused on the foot behavior while in the vehicle and the mishaps that a driver can encounter during a potentially hazardous situation. Method: A driving simulation study was used to understand how drivers move their right foot toward the pedals. The study included data from 43 drivers as they responded to a series of rapid traffic signal phase changes. Pedal application types were classified as (a) direct hit, (b) hesitated, (c) corrected trajectory, and (d) pedal errors (incorrect trajectories, misses, slips, or pressed both pedals). A mixed-effects multinomial logit model was used to predict the likelihood of one of these pedal applications, and linear mixed models with repeated measures were used to examine the response time and pedal duration given the various experimental conditions (stimuli color and location). Results: Younger drivers had higher probabilities of direct hits when compared to other age groups. Participants tended to have more pedal errors when responding to a red signal or when the signal appeared to be closer. Traffic signal phases and locations were associated with pedal response time and duration. The response time and pedal duration affected the likelihood of being in one of the four pedal application types. Conclusion and Application: Findings from this study suggest that age-related and situational factors may play a role in pedal errors, and the stimuli locations could affect the type of pedal application.

Automotive user interface research moves into fast lane

This SIG will explore issues related to the design of in-vehicle human-computer interfaces. A modern vehicles human-computer interface often facilitates the basic operation of the vehicle, but also provides more advanced features, such as assistive cruise control and lane keeping. Furthermore, todays drivers and passengers frequently use brought-in devices, in order to access navigation instructions, and use non-driving related types of digital information such as social media. The SIG will explore how in-vehicle interfaces can facilitate safe interactions for all of the occupants of the vehicle, and how they can take advantage of connected vehicle technologies.

The MIT AgeLab n-back: a multi-modal android application implementation

This paper briefly describes the background of the MIT AgeLab implementation of a delayed digit recall or n-back task, and the capabilities of an android application developed to implement a multi-modal version. The MIT AgeLab n-back task is a well-established methodology for inducing graded levels of cognitive workload. It has been adopted for broad use as a multi-modal surrogate demand and calibration task, and recently introduced as a driver and pedestrian distraction education tool.

Get Me to the Dojo: An Experiential Learning Experience

The Toyota Technical Center wanted to implement a companywide safety campaign to discourage the use of cell phones while walking. However, the traditional posters and directives from management did not seem to be working and a new approach was needed. The goal was to create an obstacle course that would be interesting enough to assess situational awareness and be fun for the participant. Thus the “Walking Dojo” was created to demonstrate that cell phones and walking don’t mix. A known measure of workload, the n-back task, was used to provide a consistent surrogate task for texting. The Dojo effectively demonstrates that walking while cognitively loaded significantly increases the time to negotiate the Dojo and increases response time to the n-back task. The lessons of the Dojo can contribute to safe walking whether it is crossing a street or on a factory floor.

Transportation in an Age-Diverse Society

In our rapidly diversifying society the needs of sometimes vastly different populations must be considered. The current population is made up of a greater number of older adults, “Baby Boomers” and younger adults “Millenials” than the current middle aged-adult population. These two generations have consistently forced change on many fronts, and will continue to do so, particularly in the area of transportation. This panel is intended to address transportation research and design needs in our ever-diversifying society, from driver-interface (DVI) design to public transportation needs, from increased safety systems to the integration of technology for our navigation of various forms of transportation. Specifically, needs that might require researchers to consider the design of systems to address the sometimes conflicting abilities, desires, cultural and demographic factors, and personal goals related to age groups separated by anywhere from 20 to 60 years in age. Panelists included have a broad range of expertise working with technology, transportation, and both older and younger adult population groups.