United States. National Highway Traffic Safety Administration. Office of Human-Vehicle Performance Research

The Impact of Driver Inattention on Near-Crash/Crash Risk: An Analysis Using the 100-Car Naturalistic Driving Study Data

As part of the HASTE European Project, effects of visual and cognitive demand on driving performance and driver state were systematically investigated by means of artificial, or surrogate, In-vehicle Information Systems (S-IVIS). The present paper reports results from simulated and real motorway driving. Data were collected in a fixed base simulator, a moving base simulator and an instrumented vehicle driven in real traffic. The data collected included speed, lane keeping performance, steering wheel movements, eye movements, physiological signals and self-reported driving performance. The results show that the effects of visual and cognitive load affect driving performance in qualitatively different ways. Visual demand led to reduced speed and increased lane keeping variation. By contrast, cognitive load did not affect speed and resulted in reduced lane keeping variation. Moreover, the cognitive load resulted in increased gaze concentration towards the road centre. Both S-IVIS had an effect on physiological signals and the drivers’ assessment of their own driving performance. The study also investigated differences between the three experimental settings (static simulator, moving base simulator and field). The results are discussed with respect to the development of a generic safety test regime for In-vehicle Information Systems.

Effects of visual and cognitive load in real and simulated motorway driving

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.

https://www.pnas.org/content/pnas/113/10/2636.full.pdf

Driver crash risk factors and prevalence evaluation using naturalistic driving data.

Technological advances are bringing connected and autonomous vehicles (CAVs) to the ever- evolving transportation system. Anticipating the public acceptance and adoption of these technologies is important. A recent internet-based survey was conducted polling 347 Austinites to understand their opinions on smart-car technologies and strategies. Ordered-probit and other model results indicate that respondents perceive fewer crashes to be the primary benefit of autonomous vehicles (AVs), with equipment failure being their top concern. Their average willingness to pay (WTP) for adding full (Level 4) automation ($7,253) appears to be much higher than that for adding partial (Level 3) automation ($3,300) to their current vehicles. This study estimates the impact of demographics, built-environment variables, and travel characteristics on Austinites’ WTP for adding such automations and connectivity to their current and coming vehicles. It also estimates adoption rates of shared autonomous vehicles (SAVs) under different pricing scenarios ($1, $2, and $3 per mile), choice dependence on friends’ and neighbors’ adoption rates, and home-location decisions after AVs and SAVs become a common mode of transport. Higher-income, technology-savvy males, living in urban areas, and those who have experienced more crashes have a greater interest in and higher WTP for the new technologies, with less dependence on others’ adoption rates. Such behavioral models are useful to simulate long-term adoption of CAV technologies under different vehicle pricing and demographic scenarios. These results can be used to develop smarter transportation systems for more efficient and sustainable travel.

Assessing Public Opinions of and Interest in New Vehicle Technologies: An Austin Perspective

Although there has been much speculation about the potential of Augmented Reality (AR), there are very few empirical studies about its effectiveness. This paper describes an experiment that tested the relative effectiveness of AR instructions in an assembly task. Task information was displayed in user's field of view and registered with the workspace as 3D objects to explicitly demonstrate the exact execution of a procedure step. Three instructional media were compared with the AR system: a printed manual, computer assisted instruction (CAI) using a monitor-based display, and CAI utilizing a head-mounted display. Results indicate that overlaying 3D instructions on the actual work pieces reduced the error rate for an assembly task by 82%, particularly diminishing cumulative errors - errors due to previous assembly mistakes. Measurement of mental effort indicated decreased mental effort in the AR condition, suggesting some of the mental calculation of the assembly task is offloaded to the system.

/pdf/comparative-effectiveness-of-augmented-reality-in-object-14ymlugs1n.pdf

Comparative effectiveness of augmented reality in object assembly

Attentional demand requirements of an automobile moving-map navigation system

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. Language: en

/pdf/the-effects-of-age-on-crash-risk-associated-with-driver-1bd1z0a4nm.pdf

The effects of age on crash risk associated with driver distraction.

Two research studies were performed in which an operational in-car navigation display system was tested and evaluated. In the first study, the visual attentional demand requirements for specific tasks associated with the navigation system were compared with those of a wide variety of conventional (though modern) instrument panel tasks. The purpose in gathering these data was to evaluate whether or not the navigation tasks created demands that were greater than those of conventional tasks, and if so, by how much. The second study addressed the effectiveness, efficiency, and strategy associated with three different kinds of route guidance, memorized route, conventional paper map, and the navigation system. Results of the studies indicate that drivers are able to use the navigation system effectively and that it compares favorably with paper maps. However, visual scan patterns are changed when using the navigation system. Furthermore, drivers use a visual sample process which is quite different from that used for either paper maps or memorized route. Other findings indicate that the visual attentional demand of most navigator tasks is within the range of that for conventional tasks, however, a few tasks do have high visual attentional demand. These latter tasks could be modified to reduce their visual attentional demand.

Visual Attentional Demand of An In-car Navigation Display System

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 driver's 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.

Jonathan F. Antin

Papers

Driver crash risk factors and prevalence evaluation using naturalistic driving data.

Attentional demand requirements of an automobile moving-map navigation system

The effects of age on crash risk associated with driver distraction.

Visual Attentional Demand of An In-car Navigation Display System

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