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Deciding to be Distracted
Get PDFThis project investigated the decision process involved in a driver’s willingness to engage in various technology-related and non-technology tasks. The project included focus groups and an on-road study, both employing participants who used in-vehicle technologies to at least some degree, from four age groups: teen, young, middle, and older. The focus groups discussed the perceptions, motivations, attitudes, and decision factors that underlie driver choices. The on-road study had two phases: an on-road drive and a take-home booklet. Participants drove their own vehicles over a specified route. They did not actually engage in in-vehicle tasks, but at specified points they rated their willingness to engage in some specific task at that time and place. Eighty-one different situations (combination of in-vehicle task and driving circumstances) were included. Further information was collected in the take-home booklet regarding the participant’s familiarity with various in-vehicle technologies, additional situations for willingness and risk ratings, stated reasons underlying ratings, and self-ratings of certain aspects of driving behavior and decisionmaking style. Together, the focus groups and on-road study provided complementary findings about how drivers decide when to engage in potentially distracting tasks. Driver willingness to engage in various in-vehicle tasks was related to technology type, specific task attributes, driving conditions, personal motivations, driving style, and decision style. Specific project findings were related to potential countermeasure approaches, including public education; driver or device user training; user interface design; needs for warnings and information; criteria for function lock-outs; and driver assist system criteria
Driver Performance While Interacting with the 511 Travel Information System in Urban and Rural Traffic
Get PDFThe national “511” highway information system is heavily used by drivers, especially during inclement weather, to plan and replan their trips. Few studies have explored the safety and usability of the 511 user interface, especially in the context of a mobile phone user who has the added workload of driving a vehicle. In this study, 36 drivers were divided into three groups (hand-held cell phone, hands-free cell phone, and control group) and drove a series of urban and rural scenarios in a high fidelity driving simulator. Drivers in the cell phone groups interacted with the Montana 511 travel information system to obtain road information on a segment of highway. Performance on the primary driving task (e.g., lanekeeping and speed control) was not affected by use of the 511 traveler information system. Driving tasks that required urgent attention (e.g., responding to unexpected traffic conflicts) were degraded by using the 511 travel system regardless of the type of phone used. Drivers using either cell phone to interact with the 511 information system were found to have a higher number of collisions and less situation awareness than those not interacting with the 511 system. Drivers using a hand-held cell phone were also found to have a higher frequency of braking responses. The increased crash risk of the phone users in our study (3.0 - 3.8) was very comparable to that reported by earlier studies of the risk of cell phone conversations
Road-to-Lab: Validation of the Static Load Test for Predicting On-Road Driving Performance While Using Advanced In-Vehicle Information and Communication Devices
Get PDFInformation, communication, and navigation devices need to beevaluated for ease-of-use and safety while driving. Lab tests, if validated, canevaluate prototype designs faster, more economically, and earlier than on-roadtests. The Static Load Test was evaluated for its ability to predict on-road driverperformance while using in-vehicle devices. In this test, participants performvarious in-vehicle tasks in a lab while viewing a videotaped road scene on amonitor, tapping a brake pedal when a central or peripheral light is observed. Forthe on-road comparison test, the device, tasks, and lights are the same, but theparticipants also drive the vehicle while performing the tasks and responding tothe lights. In both the lab and road tests, ten driver performance variables weremeasured. Our goal was to produce a linear model to predict an on-road variablefrom the lab data with low residual error, high percent variance explained, andfew errors in classifying tasks as meeting or not meeting on-road driverperformance criteria. Separate test data from a replicated Static Load Test at anindependent lab were used to further validate the models. The results indicate asimple, inexpensive, and low-fidelity Static Load Test can accurately predict anumber of on-road driver performance variables suitable for assessing the safetyand ease-of-use of advanced in-vehicle devices while driving
Enhancing the Messages Displayed on Dynamic Message Signs
Get PDFA human factors study was carried out to help enhance ways tocommunicate with highway motorists through dynamic message signs (DMS).Overhead mounted DMSs have been increasingly used by highway authorities inthe United States to present real-time traffic information and travel advice tomotorists. It is critical to post sign messages that can be quickly and clearlyunderstood by motorists, especially in high-volume traffic and construction/repairzones. Properly worded and formatted sign messages could spell the differencebetween comprehension and confusion. Message display factors investigated inthe study include display effects, color schemes, wording, and formats. Twoapproaches were employed in this study. First, a questionnaire survey wasdeveloped to collect motorists’ preferences regarding various message displayfactors. Second, a series of lab driving simulation experiments were set up toassess the effects of these factors and their interactions on motorists’comprehension of DMS messages. Study results suggested that static, one-framedmessages with more specific wording and no abbreviations were preferred.Amber or green or a green-amber combination were the most favored colors.Younger subjects took less response time to the DMS stimuli with higheraccuracy than older subjects. There were no significant gender differences
Effect of Simulator Training on Driving After Stroke: A Randomized Controlled Trial
Get PDFNeurologically impaired persons seem to benefit from drivingtraining programs, but there is no convincing evidence to support this notion. Wetherefore investigated the effect of simulator-based training on driving afterstroke. Eighty-three first ever sub-acute stroke patients entered a 5-week, 15-hourtraining program in which they were randomly allocated to either an experimental(simulator-based training) or control (driving-related cognitive tasks) group.Performance in off-road evaluations and an on-road test were used to assess thedriving ability of subjects pre- and post-training. Outcome of an official predrivingassessment administered 6 to 9 months post stroke were also considered.Both groups significantly improved in a visual and many neuropsychologicalevaluations and in the on-road test after training. There were no significantdifferences between both groups in improvements from pre- to post-trainingexcept in the “road sign recognition test,” in which the experimental subjectsimproved more. Statistically significant improvements in the three-class decision(“fit to drive,” “temporarily unfit to drive” and “unfit to drive”) were found infavor of the experimental group. Academic qualification and overall disabilitytogether determined subjects who benefited most from the simulator-baseddriving training. Significantly more experimental subjects (73%) than controls(42%) passed the follow-up official pre-driving assessment and were legallyallowed to resume driving. We concluded that simulator-based driving trainingwas a better method, especially for well educated and less disabled stroke patients. However, the findings of the study may have been modified as a resultof the large number of dropouts and the possibility of some neurological recoveryunrelated to training
Unsafe Rear-End Collision Avoidance in Alzheimer's Disease
No full textOBJECTIVES Assess response of drivers with Alzheimer’s disease (AD) to a traffic scenario creating the potential for a rear-end collision. BACKGROUND Rear-end crashes are among the most common crash types. Avoiding a crash requires continuous monitoring of neighboring vehicles, and anticipating and adjusting to changes in their speeds and positions, under pressure of time. This relies on visual perception, attention, memory, recognition of contextual cues such as approaching an intersection, and executive functions (decision making and implementation). AD impairs these processes, with clear implications for increased crash risk. (Rizzo et al., 2001) METHODS Sixty-one subjects with probable AD (defined by National Institute of Neurological and Communicative Disorders criteria) of mild severity, and 115 neurologically normal older adults were tested on a battery of visual, cognitive, and motor tests of abilities that are critical to safe automobile driving. Each participant also drove in a high-fidelity driving simulator. After a segment of uneventful driving, the participant suddenly encountered a lead vehicle stopped at a 4-way intersection waiting to turn left, posing a risk for a rear-end collision. The main dependent measure was the occurrence of an “improper response,” which included crashing into the lead vehicle, swerving out of the traffic lane, or stopping abruptly and prematurely. The secondary dependent measure was “first reaction time.” RESULTS Eighty-nine per cent of drivers with AD responded improperly to the stopped lead vehicle at the intersection compared to 65% of normal controls (OR=4.11, 95% CI 1.71-9.88, P=0.0007, Fisher’s exact test). Crash rates were similar in AD and normal controls (5% and 3%, respectively, P=0.4188), however drivers with AD were at higher risk of stopping abruptly (P<0.0001) or prematurely (P=0.0115). These differences persisted after adjusting for differences in age, education, driving exposure, or level of simulator discomfort. Abrupt stopping increased the risk of being struck from behind by the following vehicle (P=0.0262, Fisher’s exact test). The drivers with AD tended to respond slower to the encounter with the stopped lead vehicle at the intersection (first reaction time 11.5±3.5 sec in AD and 10.6±4.0 sec in controls, P=0.0548, Wilcoxon Rank Sum). Slower drivers were more likely to react improperly (P=0.0002). During a baseline segment, the drivers with AD showed increased variability of their steering (P=0.0006) with a tendency for increased variability of their speed (P=0.0757). The drivers with AD performed worse in almost all cognitive, visual, and motor tests on the battery, consistent with their mild dementia. The risk of improper reactions increased significantly with worse performances on COGSTAT (a composite measure of cognition), Complex Figure Test Copy and Recall, Judgment of Line Orientation, Benton Visual Retention Test, Trail Making Subtest B, far visual acuity, contrast sensitivity, and Useful Field of View tests. CONCLUSIONS Drivers with AD reacted slower and were at a higher risk of responding unsafely in a simulated complex driving condition that posed a hazard for a rear-end collision compared to neurologically normal drivers. Although the drivers with AD were not statistically more likely to strike a lead vehicle, their slow and inappropriate reactions, such as abrupt stopping, appeared to increase the potential for being struck by another vehicle. These impairments can be explained by the cognitive and visual dysfunction in AD, especially in the domains of visual perception, attention, memory, visuospatial abilities, and executive functions. ACKNOWLEDGMENTS This study was supported by: NIA AG 17717, NIA AG 15071. REFERENCES Rizzo, M., McGehee, D.V., Dawson, J.D., Anderson, S.N. (2001). Simulated car crashes at intersections in drivers with Alzheimer disease. Alzheimer Dis Assoc Disord., 15(1):10-20
Assessment of a Driver Interface for Lateral Drift and Curve Speed Warning Systems: Mixed Results for Auditory and Haptic Warnings
Get PDFLateral Drift Warning (LDW) and Curve Speed Warning (CSW)systems were developed to address two main critical events in run-off-roadcrashes, which are road edge departure and excessive speed. The LDW systemused a two-stage alert system, with the first stage activating when the driverdeparted a lane with a dashed boundary and the imminent, or second stage, whendeparting a lane with a solid boundary. The CSW also employed a two-stage alert,with the level based on the degree of over-speed for the upcoming curve. Thehaptic modality, in the form of seat vibration, was chosen as the first levelwarning for both systems, and auditory was chosen as the second or most urgentlevel. The two systems were installed in a fleet of instrumented vehicles andloaned to 78 randomly selected licensed drivers for approximately 4 weeks.Debriefing questions detailing the driver’s experience with the system wereadministered and analyzed in a two by two design of modality by system. Afterexamination of both the statistical results and the open-ended comments, thequestion of which modality is most appropriate is still uncertain. Each modalityhad positive aspects. Haptic does not alert the entire car and participants alsoconsidered it less distracting. Auditory provided better recognition betweenwarnings and participants were better able to understand the meaning and therequired response for each warning
Driver Assessment with Measures of Continuous Control Behavior
Get PDFThis paper reviews past research on stimulus/response analysis methods in continuous control tasks, and describes procedures for specifically measuring driver behavior in a car following task. Example driving simulator data is given for drivers with disease impairments. The data processing methods are summarized and example results are given to demonstrate the data analysis approach. Analysis of driver steering and speed control behavior have been used to identify normal highway operations and effects of various impairments, including drugs, alcohol, fatigue and medical conditions. Typical measures might include characteristics of control (steering, throttle, brake) activity, such as control reversals and expected values such as mean and standard deviation. More powerful time series analysis methods look at the relationship between stimulus and response variables. Fourier analysis procedures have been used to carry out stimulus/response relationships, such as steering response to wind gusts and roadway curvature, and speed response to lead vehicle speed variations. These methods allow the analysis of driver time delay in responding to stimulus inputs, and the correlation of driver response to the stimulus input. Typically, driver impairments lead to responses with increased time delay and decreased correlation
Evidence and Dimensions of Commercial Driver Differential Crash Risk
Get PDFThis paper highlights evidence from several instrumented vehiclestudies that crash risk varies significantly among commercial truck drivers, andalso cites findings from surveys of fleet safety managers and other experts on thetopic of individual differences in commercial driver crash risk. Within varioussubject groups, 10-15% of the drivers typically account for 30-50% of the crashrisk. This pattern is seen in measures of driver errors associated with crashes andalso in measures of driver drowsiness. The evidence also suggests, but does notyet prove, that these individual differences are long-term. To the extent that theseindividual differences are long-term, they may be considered personal traits. Thispaper conceptualizes driver risk factors, provides illustrative examples ofdifferential individual risk within groups of drivers, identifies driver factorsthought to be most associated with crash risk, and considers the opportunities forimproved commercial driving safety presented by differential crash risk