Jonathan M. Hankey

Human factors field evaluation of automotive headway maintenance/collision warning devices

Three on-road studies were conducted to determine how headway maintenance and collision warning displays influence driver behavior. Visual perspective, visual perspective with a pointer, visual perspective combined with an auditory warning, discrete visual warning, and discrete auditory warning were assessed during both coupled headway and deceleration events. Results indicate that when drivers are provided with salient visual information regarding safe headways, they utilize the information and increase their headway when appropriate. Auditory warnings were less effective than visual warnings for increasing headways but may be helpful for improving reaction time during events that require deceleration. Drivers were some what insensitive to false alarm rates, at least during short-term use. Finally, and most important, driver headway maintenance increased by as much as 0.5 s when the appropriate visual display was used. However, a study to investigate the long term effects of such displays on behavior is strongly recommended prior to mass marketing of headway maintenance/collision warning devices.

Near Crashes as Crash Surrogate for Naturalistic Driving Studies

Naturalistic driving is an innovative method for investigating driver behavior and traffic safety. However, as the number of crashes observed in naturalistic driving studies is typically small, crash surrogates are needed. A study evaluated the use of near crashes as a surrogate measure for assessment of the safety impact of driver behaviors and other risk factors. Two metrics, the precision and bias of risk estimation, were used to assess whether near crashes could be combined with crashes. The principles and exact conditions for improved precision and unbiased estimation were proposed and applied to data from the 100-Car Naturalistic Driving Study. The analyses indicated that a positive relationship exists between the frequencies of contributing factors for crashes and for near crashes. The study also indicated that analyses based on combined crash and near-crash data consistently underestimate the risk of contributing factors compared to use of crash data alone. At the same time, the precision of the estimation will increase. This consistent pattern allows investigators to identify true high-risk behaviors while qualitatively assessing potential bias. In summary, the study concluded that the use of near crashes as a crash surrogate provides definite benefit when naturalistic studies are not large enough to generate sufficient numbers of crashes for statistical analysis.

Driver crash risk factors and prevalence evaluation using naturalistic driving data

Significance This paper presents findings about the riskiest factors faced by drivers as informed through the first large-scale, crash-only analysis of naturalistic driving data. Results indicate that many secondary tasks or activities, particularly resulting from the use of handheld electronic devices, are of detriment to driver safety. The analysis uses a large naturalistic database comprising continuous in situ observations made via multiple onboard video cameras and sensors that gathered information from more than 3,500 drivers across a 3-y period. The accurate evaluation of crash causal factors can provide fundamental information for effective transportation policy, vehicle design, and driver education. Naturalistic driving (ND) data collected with multiple onboard video cameras and sensors provide a unique opportunity to evaluate risk factors during the seconds leading up to a crash. This paper uses a National Academy of Sciences-sponsored ND dataset comprising 905 injurious and property damage crash events, the magnitude of which allows the first direct analysis (to our knowledge) of causal factors using crashes only. The results show that crash causation has shifted dramatically in recent years, with driver-related factors (i.e., error, impairment, fatigue, and distraction) present in almost 90% of crashes. The results also definitively show that distraction is detrimental to driver safety, with handheld electronic devices having high use rates and risk.

Toward Developing an Approach for Alerting Drivers to the Direction of a Crash Threat

Objective: This study explored the potential for auditory and haptic spatial cuing approaches to alert drivers to the direction of a crash threat. Background: For an automobile equipped with multiple crash avoidance systems, effective cuing of the crash threat direction may help the driver avoid the crash. Because the driver may not be looking in the direction of a visual crash alert, nonvisual crash alerts were explored as an additional means of directing attention to a potential crash situation. Methods: In this in-traffic study, 32 drivers were asked to verbally report alert direction in the absence of any crash threats. Driver localization accuracy and response time were examined as a function of eight alert locations surrounding the vehicle and four directional alert approaches (auditory, haptic, haptic and auditory, and haptic and nondirectional auditory). The auditory directional alert approach used four speakers and broadband alert sounds, and the haptic directional alert approach used vibrations generated at various locations on the bottom of the drivers seat. Results: Overall, relative to the auditory alert approach, the three approaches that included the haptic seat alert component reduced correct localization response times by 257 ms and increased percentage correct localization from 32% to 84%. Conclusion: These results suggest that seat vibration alerts are a promising candidate for alerting drivers to the direction of a crash threat. Application: These findings should facilitate developing a multimodality integrated crash alert approach for vehicles equipped with multiple crash avoidance systems.

A method for evaluating collision avoidance systems using naturalistic driving data

This paper describes a method for use in evaluating the performance of collision avoidance systems (CASs) using naturalistic driving data collected during real crashes and near-crashes. The method avoids evaluation of algorithms against specific assumptions of reaction times or response inputs. It minimizes interpretation of the involved drivers perception and response levels which permits generalizing findings beyond the performance of the involved driver. The method involves four parts: input of naturalistic crash data into alert models to determine when alerts would occur, kinematic analysis to determine when different responses would be required to avoid collision, translation of the time available into an estimate of the percentage of the population able to avoid the specific event, and an evaluation of the frequency of alerts that would be generated by the CASs. The method permits comparison of CAS performance and provides guidance for CAS development. The method is described primarily in the context of Forward Collision Warning CASs, but is applicable to other CAS types.

An Evaluation of Alternative Methods for Assessing Driver Workload in the Early Development of In-Vehicle Information Systems

This study examined whether the effect of subsidiary tasks on driving performance can be predicted from stationary (static) testing. Alternative methods for assessing the performance of drivers during their use of in-vehicle information systems were examined. These methods included static testing in stationary vehicles, as well as dynamic, on-road testing. The measures that were obtained from static tests were evaluated in terms of how well they could predict measures obtained from driving performance during on-road testing (which included concurrent use of secondary information systems). The results indicated that measures obtained in static test settings were highly correlated with corresponding measures obtained from on-road performance testing. Also, the regression slopes and intercepts of on-road driving performance measures when predicting on-road lane deviations were more closely approximated under static conditions which required drivers to attend to concurrent, driving-like activities as well as secondary tasks. It is suggested that tests using multiple measures, together with a multivariate model, may hold the most promise for predicting eventual on-road driver performance in the early development of in-vehicle information systems. Although additional research and theoretical development are required, this research demonstrates that a set of relatively simple measures obtained analytically and from static testing can be used even now to help guide early system development.

The effects of age on crash risk associated with driver distraction

Background Driver distraction is a major contributing factor to crashes, which are the leading cause of death for the US population under 35 years of age. The prevalence of secondary-task engagement and its impacts on distraction and crashes may vary substantially by driver age. Methods Driving performance and behaviour data were collected continuously using multiple cameras and sensors in situ for 3542 participant drivers recruited for up to 3 years for the Second Strategic Highway Research Program Naturalistic Driving Study. Secondary-task engagement at the onset of crashes and during normal driving segments was identified from videos. A case-cohort approach was used to estimate the crash odds ratios associated with, and the prevalence of, secondary tasks for four age groups: 16-20, 21-29, 30-64 and 65-98 years of age. Only severe crashes (property damage and higher severity) were included in the analysis. Results Secondary-task-induced distraction posed a consistently higher threat for drivers younger than 30 and above 65 when compared with middle-aged drivers, although senior drivers engaged in secondary tasks much less frequently than their younger counterparts. Secondary tasks with high visual-manual demand (e.g. visual-manual tasks performed on cell phones) affected drivers of all ages. Certain secondary tasks, such as operation of in-vehicle devices and talking/singing, increased the risk for only certain age groups. Conclusions Teenaged, young adult drivers and senior drivers are more adversely impacted by secondary-task engagement than middle-aged drivers. Visual-manual distractions impact drivers of all ages, whereas cognitive distraction may have a larger impact on young drivers.

Naturalistic Driving Study: Technical Coordination and Quality Control

This report describes the technical coordination and quality control carried out by the Virginia Tech Transportation Institute (VTTI) for the Strategic Highway Research Program 2 (SHRP 2) Naturalistic Driving Study (NDS). This project encompassed procurement of the data acquisition system (DAS) and all associated installation and driver assessment equipment; coordination of human subjects protections; participant recruitment; training and coordination of the six site contractors that carried out participant enrollment, instrumentation, and data retrieval; data management; data processing; and quality control. From October 2010 through November 2013, the study collected continuous driving information on more than 3,000 light-vehicle drivers, covering about 50 million miles of driving in the six study sites. In this report, potential users of the SHRP 2 NDS data or findings will find a summary of data collection methods and procedures, instrumentation, quality control, and project management.

INITIAL DRIVER AVOIDANCE BEHAVIOR AND REACTION TIME TO AN UNALERTED INTERSECTION INCURSION.

Initial driver avoidance behavior and reaction time to an unexpected intersection incursion was determined using a state-of-the-art motion-based driving simulator (Iowa Driving Simulator). The intersection used for the experiment was on a two-lane rural highway (55 mph speed limit) that controlled perpendicular (crossing) traffic by stop signs. The subject vehicle did not have to stop and had the right-of-way on the highway. At one of three possible start times, an intersecting vehicle began moving into the intersection in front of the subject vehicle. This incurring vehicle intersected from either the drivers left or right side. Ninety-six subjects participated in the study. Subjects in the shortest, most severe collision avoidance situation were significantly slower to react and equally likely to steer or release the accelerator pedal as the initial avoidance maneuver. Subjects in the longest, least severe collision avoidance situation often released the accelerator pedal and braked prior to steering. Gender differences are also discussed.

Wet Night Visibility of Pavement Markings: A Static Experiment

Fifty-three participants evaluated the visibility of four different pavement marking materials under a simulated rain system operating at 0.8 in. (20 mm) of rain per hour at night while driving a vehicle on a closed test track. The conditions tested include a variable lighting condition, glare, pavement types, and two different vehicle types. The evaluation consisted of determining the detection distance of a start or an end point of a white 4-in. edge line. Results showed that lighting improved visibility and mitigated the effects of glare. Results also showed that the wet retroreflective tape provided the longest visibility distance, followed by equivalent performance of profile thermoplastic; large glass beads with standard paint provided the shortest visibility distance. The detection distance was compared with the retroreflective performance of the pavement marking technology. It was found that a log-linear relationship exists between the retroreflectivity and the detection distance. It was also found that the level of retroreflectivity provided by the materials tested did not provide adequate visibility distance for a sedan with a 2-s visibility time at speeds greater than 45 mph.