Jonathan F. Antin

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.

An evaluation of the effectiveness and efficiency of an automobile moving-map navigational display

This experiment was performed to evaluate the effectiveness and efficiency of navigating with an automobile moving-map display relative to navigating with a conventionl paper map and along a memorized route, which served as a baseline for comparison. Results indicated that there were no differences in the quality of routes selected when using either the paper map or the moving map to navigate. However, the moving map significantly drew the drivers gaze away from the driving task relative to the norm established in the memorized route condition, as well as in comparison to the paper map. These findings are discussed in the context of the different navigation strategies evoked by use of the paper and moving-map methods of navigation.

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.

Conventional Versus Moving-Map Navigation Methods: Efficiency and Safety Evaluation

Thirty-eight male and female participants, aged 21 to 50 years, drove to three unfamiliar destinations using three different methods of navigation: Nav, an in-vehicle moving-map and route guidance navigation system; Free, the free use of paper maps or computer printouts, but without access to the navigation system; and Way, which was the same as Free, but with waypoints also provided. Each participant had a minimum of 6 weeks of prior experience using in-vehicle navigation technology. The routes were each designed to sample urban, rural, and highway road categories. Methods were counterbalanced across route and presentation order. An onboard experimenter administered the study. Data were gathered to assess navigational efficiency, workload, and safety-related driving errors. A peripheral detection task was included as a loading task to measure workload and spare attentional capacity objectively; the rating scale of mental effort was included as a subjective measure of mental effort. Use of the navigation system produced better results than either of the two conventional methods in terms of several key metrics related to driver workload, driving errors, and navigational efficiency. These results support the notion that an onboard, moving-map navigation system incorporating route guidance can play a meaningful role in enhancing navigational efficiency and safety for experienced navigation system users. Future research is recommended to examine eye glance and other driver behaviors further, such as lane excursions and headway maintenance, to gain additional insight into the effect of method of navigation on the primary driving task.

Instantaneous Measures of Mental Workload: An Initial Investigation

Many researchers have implicitly or explicitly averaged measures of mental workload over a given run or period of time. This process tends to mask specific features (e.g. peaks) of interest in the flow of instantaneous mental workload (IMWL). A study was conducted in which thirty subjects performed computer tasks which quantifiably varied in difficulty during a run. These tasks emphasized perceptual, mediational, psychomotor, and storage and retrieval from short-term memory processes. Data were gathered on the following candidate measures of momentary load: instantaneous primary task performance, instantaneous Michon tapping and time estimation secondary task performance, instantaneous pulse and respiration rates, and two types of online subjective opinion. Data were short-term averaged and used to develop regression models to evaluate the ability of the measures to track IMWL. Primary task performance (response time for functional subtasks) and both forms of online subjective opinion measures showed great promise as measures of IMWL.

Performance of basic kinematic thresholds in the identification of crash and near-crash events within naturalistic driving data

Understanding causal factors for traffic safety-critical events (e.g., crashes and near-crashes) is an important step in reducing their frequency and severity. Naturalistic driving data offers unparalleled insight into these factors, but requires identification of situations where crashes are present within large volumes of data. Sensitivity and specificity of these identification approaches are key to minimizing the resources required to validate candidate crash events. This investigation used data from the Second Strategic Highway Research Program Naturalistic Driving Study (SHRP 2 NDS) and the Canada Naturalistic Driving Study (CNDS) to develop and validate different kinematic thresholds that can be used to detect crash events. Results indicate that the sensitivity of many of these approaches can be quite low, but can be improved by selecting particular threshold levels based on detection performance. Additional improvements in these approaches are possible, and may involve leveraging combinations of different detection approaches, including advanced statistical techniques and artificial intelligence approaches, additional parameter modifications, and automation of validation processes.

A validation of the low mileage bias using naturalistic driving study data

INTRODUCTION This paper evaluated the low mileage bias (LMB) phenomenon for senior drivers using data mined from the Second Strategic Highway Research Program (SHRP 2) Naturalistic Driving Study. Supporters of the LMB construct postulate that it is only those seniors who drive the lowest annual mileage who are primarily responsible for the increased crash rates traditionally attributed to this population in general. METHOD The current analysis included 802 participants, all aged 65 or older who were involved in 163 property damage and injury crashes, and deemed to be at-fault in 123 (75%) of those instances. Poisson regression models were used to evaluate the association between annualized mileage driven and crash risk. RESULTS Results show that the crash rate for drivers with lower annualized mileage (i.e., especially for those driving fewer than approximately 3000miles per year) was significantly higher than that of drivers with higher annualized mileage, and that 25% of the overall sample were low- mileage drivers according to this criterion. Data were also evaluated by gender and meta-age group (i.e., younger-old: 65-74 and older-old: 75-99), and the results were consistent across these sub-groups. CONCLUSIONS This study provides strong support for the existence of the LMB. PRACTICAL APPLICATIONS These results can help to reshape how transportation safety stakeholders view senior drivers in general and help them to focus their efforts on those seniors most in need of either risk-reducing countermeasures or alternative means of transportation.

Vulnerable Road Users: How Can Automated Vehicle Systems Help to Keep Them Safe and Mobile?

For the first time in 2015, the Automated Vehicle Symposium featured a breakout session explicitly devoted to vulnerable road users (VRUs) and their use of and interactions with automated vehicles. A number of stakeholders, experts, and researchers from a variety of fields presented and discussed the state of current research and thought concerning the potential relationship of vulnerable road users and automated vehicles and how to maximize the benefits this novel technology might bring to these individuals. The topics included the role of design, various technological solutions, policies, and programs that could advance the safe mobility of VRUs in a future with an integrated fleet of automated vehicle systems. Through expert-led small group discussion, the breakout group produced a list of possible definitions for VRUs including pedestrians, cyclists, seniors (pedestrians as well as drivers), and identified key research gaps within the context of this multifaceted segment of the population. Some of these gaps related to motorcycle interactions, how different groups of VRUs will accept emerging AV technologies, and goals and solutions when considering how best to share limited roadway space across all road user constituencies.

Naturalistic Driving Study: Collecting Data on Cell Phone Use

This report details the methodology used to acquire cell phone use records from a subset of participants in the SHRP 2 Naturalistic Driving Study (NDS) during the time when they were enrolled in the study. The cell phone records were then matched with participants’ NDS driving data to identify the times while they were driving when they may have been using their cell phones. These data will help researchers quickly and accurately identify events of interest in the NDS database related to cell phone use, from which researchers can learn crucial information about driver behavior and changes in crash risk when drivers choose to use or not to use cell phones. This report provides researchers with essential information about the Cell Phone Records Study (CPRS) data and how the data were collected. It describes the methods used to recruit and enroll CPRS participants, the collaboration with the cell phone carriers, and the processes of obtaining data from the carriers and directly from the participants. It also provides summary information on the data collected and discusses some limitations of the data.