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Driving Simulators for Commercial Truck Drivers - Humans in the Loop
Get PDFThis paper reports the findings of a research study that addresses differences in human performance outcomes based on various driving simulators, as measured by comparison of scores resulting from completion of the Virtual Check Ride System (VCRS), a simulator-based, blended learning Commercial Drivers License (CDL) application. The objective of the project was to examine human performance across four different levels of driving simulators and to determine if driving simulators can contribute to human performance improvement. Each level of simulator has a definite set of tasks that can be performed on it to enhance human performance. By identifying which level of driving simulator is the best fit according to the skill, knowledge, and attitude task element, we can now prescribe for diagnostic, testing, pre-hire, remediation, safety issues and advanced driving skills
Quantifying the Benefits of Enhancing Medications on Driving Performance: Comparing OROS ® MPH vs. se-AMPH ER ® in Driving Safety of ADHD Teenagers as Case Example
Get PDFDriving simulation is the best way to safely and reliably assess theimpact of medical parameters on driving in a controlled, replicable environment,Driving performance should be evaluated using a composite driving score, sincethe pathway to impaired driving is highly idiosyncratic and could involve anynumber of individual driving parameters. Although simulators still do not haveaccepted standards for hardware, driving scenarios, or performance variables, wepropose a partial solution to permit comparisons of composite scores acrosssimulators. We recommend presenting simulator data via a standardized averageeffect size, which we call the Impaired Driving Score (IDS). We describe how theIDS is calculated, and present data comparing 16 male and 15 female teenagedrivers with ADHD who participated in a double-blind, placebo-controlled, crossoverstudy. Using an equivalent-dose regimen, we compared the effects of 72 mgof OROS® MPH (Concerta®), 30mg of se-AMPH XR® (Adderall XR®) andplacebo on driving performance. Participants drove our Atari Research DrivingSimulator at 5, 8, and 11 pm under all three medication conditions with at least aweek between conditions/drives. The primary outcome measure was participants’IDS. Across all three times, performance on Concerta® was superior to placebo(p=.005), while Adderall XR® was not (p=.14). When analyzed separately,however, only one variable was statistically significant (seconds spent speeding,p<.01). Composite driving scores permit the comparison of driving performanceacross various experimental conditions and with a normative database.Furthermore, since the IDS is based on a multi-faceted assessment of drivingperformance, it is less vulnerable to random effects and offers a more robustindicator of driving performance
The Spatial Extent of Attention During Driving
Get PDFThe present study examined the limits of spatial attention during driving using a dual-task performance paradigm. Drivers were asked to follow a lead vehicle that varied in speed while also detecting a light change in an array located above the roadway. Reaction time increased and accuracy decreased as a function of the horizontal location of the light change and the distance, from the driver, of the light change. In addition, RMS error in car following increased immediately following the light change. These results demonstrate that when drivers attend to a centrally located task, their ability to respond to other events varies as a function of horizontal visual angle and distance in the scene
Traffic Violations and Errors: The Effects of Sensation Seeking and Attention
Get PDFThe purpose of this study was to examine the effects of sensationseeking and attention in traffic violations and errors. Participants were 716volunteer male drivers from Ankara, Turkey. Drivers were asked to respond tocomputerized measures of monotonous and selective attention tests, and also tocomplete the Driver Behavior Questionnaire, Driving Skills Inventory, and ArnettInventory of Sensation Seeking. We first categorized participants into four groupsaccording to their correct responses of monotonous and selective attention tests byusing median-split: Group 1 = low scores on both monotonous and selectiveattention tests, Group 2 = high scores on both monotonous and selective attentiontests, Group 3 = low on monotonous attention and high on selective attention, andGroup 4 = high on monotonous attention and low on selective attention.Participants were also classified into two groups regarding their total sensationseeking scores as low and high sensation seekers. A 4 (attention groups) X 2(sensation seeking groups) MANOVA was conducted on traffic violations anderrors as dependent variables. MANOVA analysis indicated that high sensationseekers with high monotonous and selective attention are more likely to have ahigher number of traffic violations and errors than other groups. Since thesedrivers also reported lower levels of safety skills than other groups, it could beinterpreted as an indication of drivers’ overconfidence in their skills andunderestimation of the hazards in traffic. Such drivers were more likely to be risktakers in traffic situations
Effects of Lane Departure Warning on Drowsy Drivers' Performance and State in a Simulator
Get PDFDriver drowsiness is a major cause of severe accidents, many ofwhich involve a single vehicle lane departure. The objective of the experimentdescribed in this paper is to determine the relationships between drowsiness, lanedeparture events (LDE) and effects of a warning system. While in case of driverdistraction the impact of such a warning system can be tested in real traffic, forreasons of safety (and reproducibility), a laboratory-based driving simulator isbeing used in this project. The experiments were conducted with a cohort of 63healthy male subjects aged 22 to 27 driving for about 2.5 hrs in a stimuli-deprivedscenario with a six-fold repetition under carefully controlled conditions. Severalhundreds micro-sleep episodes were identified in the 53 successful trials byelectrooculogram and video signal and confirmed by behavioral analysis; morethan 800 lane departure warnings (LDW) occurred in the assisted sub-cohort of 17drivers. A combined analysis of the LDE with and without LDW showssignificant reduction in number, time, departure length and out-of-lane area forthe assisted subjects. The timing and design of the warning could furthermoreprevent almost 85% of the lane departure events caused by sleepiness
Useful Field of View Impairment in Partial Epilepsy
Get PDFPatients with epilepsy are at elevated risk for automobile crashes.Most collisions in drivers with epilepsy are not seizure-related, but may insteadresult from cognitive effects of epilepsy and antiepileptic drugs (AEDs) upondriving performance. The Useful Field of View (UFOV) score has demonstratedgood sensitivity and specificity for predicting automobile crashes. The goal in thispilot study was to assess impairments in the UFOV in subjects with partialepilepsy. Participants included 20 subjects with partial epilepsy. Neurologicallynormal control subjects of comparable age also participated. UFOV was assessedin all participants using the Visual Attention Analyzer, Model 3000 (VisualResources, Inc.). UFOV Task scores were added to calculate a UFOV Total scorefor each subject. UFOV scores were higher on all UFOV tasks in subjects withpartial epilepsy compared to neurologically normal individuals of similar age (p<0.05, Wilcoxon Rank Sum Test), suggesting a greater crash risk in individualswith partial epilepsy, even in the absence of an epileptic seizure. Causes ofimpaired UFOV scores include processing speed reduction, divided and selectiveattention impairments, and mild postoperative visual field deficits. Our ongoingstudies in drivers with epilepsy are aimed at further differentiating potentialeffects of seizures, antiepileptic drugs, and surgical lesions upon cognitiveabilities that are critical to safe automobile driving
Can Novice Drivers Recognize Foreshadowing Risks as Easily as Experienced Drivers?
Get PDFNovice drivers (16 and 17 years old) are almost ten times more likely to be involved in motor vehicle fatalities as adults 45-55 (NHTSA 2002). Besides traffic signs and other traffic control devices, there are many cues that help drivers further predict the presence of a potential risk in the driving environment. These cues are called foreshadowing elements (e.g., a pedestrian walking towards a crosswalk). It was hypothesized that given that younger adults have much less experience on the roads, it is more difficult for them to predict where potential cues might be positioned when foreshadowing elements are not present. However, in the presence of foreshadowing elements it was predicted that novice drivers should recognize risks as well as more experienced drivers. This research uses eye movement data gathered on a driving simulator to evaluate the use and effectiveness of the foreshadowing elements by novice and experienced drivers as predictors of areas in a scenario where risks may materialize. The research has potential implications for the sorts of instructional programs that might be developed for novice drivers
Driver Performance Assessment with a Car Following Model
Get PDFDriver performance is generally quantified by the state of the vehicle relative to the local road and traffic environment. Unfortunately these vehiclestate-based metrics are limited in their diagnostic value when it comes to trying to assess how: (i) drivers individually adopted different control strategies, (ii) how they individually adapted to the issues under investigation (e.g., in-vehicle task execution, driver support system exposure, or impairment), or (iii) why drivers individually were more or less affected by the factor under study. By representing a driver’s behavior in an identifiable computational driver model, insight is gained into how drivers may differentially benefit or be impaired by the condition at hand. Such a model also shows how the myriad of possible performance metrics are all “necessarily” correlated. Based on test track car following data, a driver car following model is introduced and identified for each driver and used to show how drivers differ in their car following control strategies. It is demonstrated that the adopted target time headway (THW) strongly influences the associated control strategy (i.e., effort) as well as the safety margin (i.e., the minimum THWs experienced) and that subjects who adopt a longer target THW also exhibit a lower bandwidth control strategy (i.e., less effort)
Driving Performance in a Simulator as a Function of Pavement and Shoulder Width, Edge Line Presence, and Oncoming Traffic
Get PDFDriving simulation has primarily been used to study issues of driver distraction and to evaluate in-vehicle devices. The visualization and driver performance capabilities of simulators can be applied to more traditional traffic engineering problems as well. This project aims to demonstrate the usefulness of a driving simulator in evaluating geometric designs for two-lane roads. Paved surface width has been shown to be correlated with crash rates and travel speeds on two-lane rural roads throughout Texas. The current project examines how travel lane width, edge line striping, and shoulder width affect driver errors on these roadway types. Issues of simulator validity, scenario development, and simulator sickness are discussed
Performing E-mail Tasks While Driving: The Impact of Speech-Based Tasks on Visual Detection
Get PDFDrivers listened and responded to e-mail messages presented in ahuman voice and two types of synthetic speech (concatenative and formant) whiledriving a simulator. Their performance for visual event detection, vehicle control,and message responses was assessed. Results indicated that the type of speechoutput system affected drivers’ detection of visual changes in the drivingenvironment; they were poorer at detecting these events when either of thesynthetic speech systems was used. Drivers detected fewer visual changes duringthe difficult messages than during the baseline driving. No effects of the speechsystem type or e-mail message difficulty were observed on the vehicle controlmeasures. Drivers were also less accurate when responding to message content formessages presented in synthetic speech (concatenative) compared with recordedhuman voice. Subjective ratings indicated that listening to the synthetic speechrequired more mental effort than listening to the recorded human voice.Preference ratings for the interfaces decreased as mental effort increased. Theresults indicated that although drivers were not required to direct their attentionaway from the road, using the speech-based interfaces reduced drivers’ visualevent detection and their response accuracy to messages themselves