729 research outputs found
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Comparing G-Force Measurement Between a Smartphone App and an In-Vehicle Accelerometer
No full textDue to their widespread adoption, smartphone applications (apps) could allow for a simple, low-cost assessment of driving behavior on a population scale. A number of existing apps are capable of measuring g-forces while driving, but few evaluations have been conducted to determine their accuracy. The goal of this study was to compare the measurement of g-forces between two devices: a custom-built smartphone app and an in-vehicle device that is currently used for research purposes (DAS). The test occurred under experimental conditions on a test track, where a vehicle, equipped with both the DAS and a smartphone with the app installed, performed a number of different acceleration events (e.g. hard-braking, sharp turning, etc.) under controlled conditions. We found that the app captured data that followed the same overall pattern of the DAS, but had a lower amplitude of measurement and a lower signal-to-noise ratio in the data. In general, the strength of the association between the app and DAS improved as the velocity of the events increased (though this was not true for all maneuvers). The correlations between the app and DAS were weaker for other maneuvers, and this may be due to delays in registering the maneuver. These findings indicate that a smartphone application did not register driving maneuvers in the same way that a dedicated in-vehicle device recorded them. Smartphones are ubiquitous and could represent a valuable driving research tool, however steps such as validation and testing are required, before they can be deployed in field trials
Comparison of Glancing Behaviors of Riders and Drivers at Unsignalized Intersections Involving Right Turns
No full textThe vulnerability of motorcyclists makes them the user group with the highest likelihood of a fatality on roads, a significant proportion of which occur at unsignalized intersections. The current research compares the scanning behaviors of two cohorts of participants at two different intersections involving a right turn. This on-road study included two cohorts: a ‘driver-rider’ group consisting of 20 participants who were both, licensed to drive and held an endorsement to ride a motorcycle, and a second ‘driver-only’ cohort comprising 10 participants who only held a driver license. Two types of comparisons were made: the number of anticipatory glances of the driver-rider at the two right intersections, both before and after the intersection, were compared when riding and driving across the same two intersections. Drivers-only completed the test route once while the driverriders navigated the same route once while riding, and a second time while driving, the exact order counterbalanced across all participants. The results showed that driver-rider made significantly more glances to the left when riding compared when driving after the intersection than before, while they made more glances to the right after the entry than before the intersection. Key Words: field study, motorcyclist behavior, driver-rider, anticipation, right turn across pat
It’s All in the Timing: Using the Attend Algorithm to Assess Texting in the Nest Naturalistic Driving Database
No full textTo better understand cellular phone texting behavior and its relationship to crashing, we combined the sample-level glance data of NEST with the AttenD buffer algorithm to visualize glancing during texting within naturalistic epochs ending in crashes or no crashes. We found that texting periods were quite similar across the two, both in duration, number of individual texting tasks, and overall shape of the AttenD buffer curve. However, we found that crash epoch texting tended to occur closer to the onset of a crash event, and that texting during crashing may be initiated when the AttenD buffer level is lower (indicating depleted situation awareness), possibly due to prior or ongoing operational or secondary activities. We also made similar comparisons for radio interaction tasks, and found substantial differences between radio crash and baseline interactions. We conclude that whether a texting period ends in a crash may be dependent upon more than the individual differences in length of texting or amount of glancing. One’s level of situation awareness at the start of the activity (indicating a potential lack of judgment in picking up the device), in combination with a cascading losses of situation awareness that arise from the temporal pattern of on-road and off-road glances upstream from a safety-critical event, may be key predictive factors
Comparison of Wrap Around Screens and HMDs on a Driver’s Response to an Unexpected Pedestrian Crossing Using Simulator Vehicle Parameters
No full textDriving simulators are typically used when analyzing hazardous and collision events, as dangerous drives can be performed in controlled environments without compromising driver safety. Most driving simulators use a form of wrap around screens to project the simulation as they provide a wide field of view for the user creating a more realistic experience. However, this visual modality is costly and not practical for smaller workspaces. Recent advancements in head mounted display (HMD) technology may make them a better alternative to wrap around screens, but studies have yet to compare the two visual modality effects on driver performance in hazardous scenarios. In this study, drivers completed two drive simulations, one using wrap around screens and the other using a commercially available HMD. Each simulation contained two different unexpected pedestrian crossings in which the perception-response time and brake movement time of the driver was assessed. Average vehicle speed and standard deviation of lateral position were also examined. Perception-response time was significantly longer for drivers when wearing the HMD than when using wrap around screens. There were also significant differences in vehicle speed during driver perception-response time and brake movement time between display modalities but standard deviation of lateral position only had significant differences during perception-response times. Further advancements in HMD technology are needed before they can provide an adequate alternative to wrap around screens when analyzing driver response scenarios
Time Series Categorization of Driving Maneuvers Using Acceleration Signals
No full textTwo methods of time series analysis were applied to naturalistic driving data. The SAX method reduces the dimensionality of the data by discretizing and quantizing it into distinct symbols. The matrix profile method works on raw data and computes a Euclidian distance measure between subsequences of the time series. Both methods can be used to search for motifs and discords (anomalies) in the data. We discuss the applications of these methods to look for driving patterns and show an example of a left turn that was identified using both methods. After comparing the methods, the matrix profile was the preferred method
Effects of Distraction Type, Driver Age, and Roadway Environment on Reaction Times – An Analysis Using SHRP-2 NDS Data
No full textEffects of different types of cell phone use were examined through an analysis of selected data from the SHRP2 Naturalistic Driving Study (NDS). Driving events involving lead-vehicle or approaching-vehicle incidents were analyzed to compare driver reaction times and crash probability across driver distraction type, driver age, and roadway environment. The analysis found that the median reaction time was 40.5% higher among drivers engaged in a visualmanual task such as texting, and crash risk for those drivers was 4.66 times higher compared to drivers who were undistracted. Median reaction times in urban environments were longer than those in freeway environments. Drivers aged 16- 19 exhibited faster reaction times then older drivers, but higher crash risk
Modeling the Effect of Subtask Boundaries on Driver Glance Behavior
No full textStudies of multitasking while driving have shown that drivers tend to switch attention at subtask boundaries. It is also known that the uncertainty of roadway information plays a significant role in attention switching. Yet, these two approaches have not been modeled together. In this study, we create an attention switching model that accounts for both subtask boundaries and uncertainty, and use Approximate Bayesian Computation-Markov Chain Monte Carlo (ABCMCMC) to determine the weight between the two factors, based on the empirical data. The weight was calculated for each of two different types of tasks, text reading and entry, that have subtask boundaries with different characteristics. We found that the subtask boundary in the text reading task nudged drivers to discontinue the distracting task and switch attention back to the road more than the subtask boundary in the text entry task. This study suggests that task structure may play a role in generating long glances
Sequential In-Vehicle Glance Analysis of Attention Maintenance Behavior for Trained and Untrained Young Drivers
No full textIn-vehicle tasks often require drivers to glance away from the forward roadway while driving for relatively long durations. Long in-vehicle glances are associated with an elevated risk of fatal crash involvement. In the current effort, the glance data reported in Yamani et al. (2016) where drivers received either an integrative training program for higher cognitive skills including attention maintenance (SAFE-T) or a placebo program, have been reanalyzed to uncover differences in glance behavior among trained and untrained drivers. By applying two alternative analytic techniques, the summed excess glance durations and the sequential glance analysis, the data indicated that the training was especially effective on limiting the duration of the first glance in the sequence compared to the rest of the glances in the sequence. The results imply that the training program has differential impacts on attention maintenance behavior at different stages of task interaction, such as orienting to, and processing of task-relevant information
Threats to Scientific Validity in Truck Driver Hours-of-Service Studies
No full textCommercial truck driver Hours-of-Service (HOS) rules are periodically revised to reduce driver fatigue and improve driver health in costefficient ways. HOS research must demonstrate causal relationships between HOS parameters and important safety outcomes. Thus, two scientific requirements are internal validity (demonstration of true cause-effect relationships) and external validity (generalizability to important real-world consequences). HOS rules ostensibly act by mitigating driver fatigue; thus, dependent measures in most HOS studies must verifiably capture and measure alertness/fatigue. That is, dependent measures must have construct validity. This paper examines these basic scientific validity requirements and finds significant threats to them within the designs of major U.S. HOS studies. Lessons learned apply to many other areas of behavioral research. Improved designs and compensatory methods are suggested for addressing validity threats and thereby increasing internal, external, and construct validity. Improving scientific validity would in turn raise the likelihood that HOS changes based on research would be safety-effective in the real world of truck transport on our nation’s highways
A Link Between Trust in Technology and Glance Allocation in On-Road Driving
No full textThis paper examines whether there is an association between preexposure trust in technology and subsequent glance behavior when interacting with a technology that was relatively novel for the majority of participants. After rating their level of trust in technology on a questionnaire, participants drove one of two vehicle models on a highway and engaged in a voice-based navigation address entry task. Subjective ratings of trust in new car technologies were found to be significantly positively correlated with a higher frequency of glances across all coded glance regions during the task. In one of the voice-interface implementations, these higher ratings of trust were also associated with a higher frequency of glances to the user interface, but with fewer long duration (>2s) glances per minute. A lower trust in technology in general showed some association with taking more time to complete interactions. The findings are discussed as highlighting the potential value of further research into the associations between trust and visual scanning behavior