Multiple Resource Modeling of Task Interference in Vehicle Control, Hazard Awareness and In-vehicle Task Performance

We describe a computational model of multiple task performance used to predict task interference and subsequent decrements in performance, based on the resource demands of a particular task (i.e., the difficulty) as well as the competition between tasks over limited and overlapping resources. We describe the model components, the computational aspects, and further validate it with data from a simulated driving study

Awareness of Performance Decrements Due to Distraction in Younger and Older Drivers

Although many studies have documented the performance decrements associated with driver distractions, few have examined drivers’ awareness of these distraction effects. The current study purports to measure how wellcalibrated drivers are with respect to their own performance when distracted. Forty drivers completed a series of tasks on a hand-held or hands-free cell phone while driving an instrumented vehicle around a closed test track. Subjective estimates of performance decrements were recorded and compared to actual decrements observed on multiple measures of driving performance. Although their driving performance suffered in dual-task conditions, drivers were generally not well-calibrated to the magnitude of the distraction effects (r = -.38 to .16). In some cases, estimates of distraction were opposite of the observed effects (i.e., smaller estimates of distraction corresponded to larger performance deficits). There were some age and gender differences. We discuss the implications of these findings for potential mitigation strategies for distracted driving

Age-Related Differences in Vehicle Control and Eye Movement Patterns at Intersections: Older and Middle-Aged Drivers

Older drivers are at increased risk of intersection crashes. Previous work found that older drivers execute less frequent glances for detecting potential threats at intersections than middle-aged drivers. Yet, earlier work has also shown that an active training program doubled the frequency of these glances among older drivers, suggesting that these effects are not necessarily due to age-related functional declines. In light of findings, the current study sought to explore the ability of older drivers to coordinate their head and eye movements while simultaneously steering the vehicle as well as their glance behavior at intersections. In a driving simulator, older (M = 76 yrs) and middle-aged (M = 58 yrs) drivers completed different driving tasks: (1) travelling straight on a highway while scanning for peripheral information (a visual search task) and (2) navigating intersections with areas potential hazard. The results replicate that the older drivers did not execute glances for potential threats to the sides when turning at intersections as frequently as the middle-aged drivers. Furthermore, the results demonstrate costs of performing two concurrent tasks, highway driving and visual search task on the side displays: the older drivers performed more poorly on the visual search task and needed to correct their steering positions more compared to the middle-aged counterparts. The findings are consistent with the predictions and discussed in terms of a decoupling hypothesis, providing an account for the effects of the active training program

Exploring Driver Responses to Unexpected and Expected Events Using Probabilistic Topic Models

Drivers’ expectations influence their responses to events in complex ways. In particular, covert and sustained hazards, like crosswinds, might require complex vehicle control adaptations. We investigated differences between drivers’ lateral responses in unexpected and expected (repeated) crosswind events using probabilistic topic modeling. First, each driver’s event-based steering wheel movements (angle and rate, 5 Hz) were transformed into symbolic words. Then, probabilistic topic modeling was used to discover patterns in the steering wheel movement data across the event conditions. Results indicate that drivers may make fewer abrupt steering wheel movements when they encounter unexpected crosswinds. On the contrary, drivers are more likely to make continuous faster steering corrections to compensate crosswinds when they are expected. The topic models also classify unexpected and expected crosswind events better than traditional models that use single aggregated values across events (maximum steering wheel angle and rate). These preliminary insights show an advantage for granular, time-series based analysis of driving data, and suggest a viable machinelearning based technique to conduct such investigations

Examination of the Efficacy of Proximity Warning Devices for Young and Older Drivers

OBJECTIVESThe study was conducted to examine the efficacy of uni- and multi-modal proximity warningdevices for forward object collision and side-object detection for young and older adult drivers.METHODSTwo experiments were conducted, each with 20 young (18 to 30 years of age) and 20 older (61to 80 years of age) healthy and high functioning drivers. In each, participants drove a series ofbrief (~ 4 minute) highway scenarios with temporally unpredictable forward and side collisionevents (i.e., other vehicles). The experiments were conducted in a fixed-base Drive Safetysimulator with a 135-degree wrap-around forward field and a 135-degree rear field. Light crosswindswere included in Experiment 1, while heavier crosswinds were introduced in the secondexperiment. A secondary visual read-out task from an in-vehicle LCD display was also includedin the second experiment.In Experiment 1, potential collision events were signaled 2.2 seconds before impact by visual,auditory, auditory+visual or tactile+visual warnings that were spatially mapped to the location ofthe obstacle (left, right or center). A control condition in which subjects drove without anyproximity warning device was also included in the experiment. Experiment 2 included thecontrol, auditory+visual and visual warnings from Experiment 1.A number of dependent measures were collected, including velocity, lane position, steeringwheel movement, brake and accelerator position. However, we will focus on the response time(as measured by steering wheel deflections or removal of the foot from the accelerator) topotential collision events as well as the number of collisions in different experimental conditions.RESULTSIn both Experiments 1 and 2, the auditory+visual warning device produced the most rapidresponse and also resulted in the fewest collisions. The reduction in response time and collisions,relative to the no-warning control condition was larger in Experiment 2 than in Experiment 1, likely as a result to the more challenging driving scenarios (with the higher and unpredictablewinds and introduction of the secondary task) in this experiment.Older adults responded just as quickly as younger adults to the potential collision events in bothof the experiments. This is a very surprising finding given a voluminous laboratory literature,which suggests that older adults display slower responses than younger adults on almost any taskthat has been examined in the laboratory.In an effort to understand the age-equivalent response times to collision events, we asked youngand older participants from the first experiment to take part in an additional experimental sessionin which they made simple and choice responses to visual and auditory events in a soundattenuated subject booth. Older adults were substantially (~ 35%) slower in each of these simpleand choice tasks performed in the laboratory.Older adults displayed the same performance benefits (in terms of speeded response time andreductions in collisions) from the proximity warning devices, and particularly theauditory+visual device, in both of the experiments as younger adults. However, in Experiment 2,older adults displayed these benefits by neglecting the number read-out secondary task.CONCLUSIONSThere are several important conclusions from the present study. First, proximity warningdevices, and particularly auditory+visual devices, can substantially speed response time andreduce potential collisions in simulated driving. This is an important observation that has thepotential to reduce automobile accidents. Second, both younger and older adults benefit from theproximity warning devices. Such a finding suggests, that at least for individuals with normalvision and hearing, these devices might have substantial utility across a wide variety of drivers.Third, quite to our surprise, older adult drivers responded just as quickly, with and without theproximity warning devices, to potential collision events as younger drivers. Interestingly, ageequivalencein response time to potential collisions was not observed in simple and choiceauditory and visual laboratory response time tasks. Such data tentatively suggests that experienceand expertise in driving may act as a moderator of age-related decline in general slowing.Given the unpredictable nature of the potential collision events in our study, older drivers may becapitalizing on high levels of vigilance and attentional focus on driving relevant tasks to maintaintheir ability to rapidly respond to collision events. This hypothesis is supported, in part, by thedecrements in secondary task performed observed for the older but not for the younger adults inExperiment 2.The results from the present study are encouraging both with respect to the utility of proximitywarning devices as a means to enhance driver safety as well as for their potential application todrivers of different ages and experience levels. However, clearly additional research will beneeded to verify these results in more challenging simulator and on the road driving situations

The Long Road Home: Driving Performance and Ocular Measurements of Drowsiness Following Night Shift-Work

Because time-of-day effects on sleepiness interact with duration of prior waking, the commute home following a night shift is an especially vulnerable time for night shift workers. The current study aimed to explore the impact of night shift work on critical driving events as well as to explore physiological indices leading up to these events. Sixteen healthy night shift workers (18-65 years) each participated in two 2-hour driving sessions in an instrumented vehicle on a driving track. A baseline driving session was conducted following a night of rest, while another session was conducted following a night of shift work. Objective physiological measurements of drowsiness were monitored and collected continuously throughout the drive session as well as different measures of driving performance. Following the night-shift, drivers had higher Johns Drowsiness Scores (based on ocular measures) and were more likely to experience lane excursion events and investigator-initiated braking events than following a night’s rest. While they also reported increasing failures in lane keeping ability, the pattern was not always consistent with actual observed data. The implications for countermeasures are discussed

Change in Mental Models of ADAS in Relation to Quantity and Quality of Exposure

69A3551747131Given the importance of mental models towards safe interaction with Advanced Driver Assistance Systems (ADAS) and the various human factors challenges regarding ADAS such as miscalibrated trust and the effect on workload, it is important to understand how different types of driving experiences and exposures affect drivers\u2019 mental models about ADAS. The objective of this study was to examine how the frequency and quality of exposure (exposure defined as driving through events or situations that have some bearing on the functions of the Adaptive Cruise Control (ACC)) affect drivers\u2019 mental models about ACC, their trust, workload, and their use of the systems as measured by their behaviors around disengaging ACC

Vehicle Familiarity and Relative Risk of Fatal Crash Involvement

Lack of familiarity with a vehicle has been associated with increased crash risk independent of overall driving experience (Perel, 1983). This may pose an underappreciated safety risk in the context of complex and rapidly evolving driver assistance technologies and driver-vehicle interfaces, especially when people drive newly purchased, rented, or borrowed vehicles. The current study estimates the relationship between vehicle ownership and responsibility for crashes using data from 231,056 drivers involved in fatal crashes in the United States in years 2008-2017. A driver was considered responsible for the crash if police indicated that the driver’s pre-crash actions contributed to the occurrence of the crash, and non-responsible otherwise. Driver-, vehicle-, and roadway factors that might also influence crash risk were controlled using logistic regression. Drivers of vehicles registered to another person and drivers of rental vehicles had 1.15 and 1.20 times the odds of responsibility for their crashes, respectively, compared with drivers of their own vehicles. If non-responsible drivers approximate a random sample of all drivers present at the times and places of fatal crashes, these results approximate ratios of responsible involvement in fatal crashes per unit of driving exposure. While ownership is an imperfect proxy for familiarity and may be associated with crash risk by other mechanisms unrelated to familiarity, results are consistent with the hypothesis that drivers of unfamiliar vehicles experience elevated crash risk