Challenges to Human Drivers in Increasingly Automated Vehicles

Understanding trust calibration in automated driving: the effect of time, personality, and system warning design

Under the human-automation codriving future, dynamic trust should be considered. This paper explored how trust changes over time and how multiple factors (time, trust propensity, neuroticism, and takeover warning design) calibrate trust together. We launched two driving simulator experiments to measure drivers' trust before, during, and after the experiment under takeover scenarios. The results showed that trust in automation increased during short-term interactions and dropped after four months, which is still higher than pre-experiment trust. Initial trust and trust propensity had a stable impact on trust. Drivers trusted the system more with the two-stage (MR + TOR) warning design than the one-stage (TOR). Neuroticism had a significant effect on the countdown compared with the content warning.Practitioner summary: The results provide new data and knowledge for trust calibration in the takeover scenario. The findings can help design a more reasonable automated driving system in long-term human-automation interactions.

Rendezvous Under Temporal Uncertainty

OBJECTIVE

Three experiments sought to understand performance limitations in controlling a ship attempting to meet another moving ship that approached from various trajectories. The influence of uncertainty, resulting from occasional unpredictable delays in one's own movement, was examined.

BACKGROUND

Cognitive elements of rendezvous have been little studied. Related work such as the planning fallacy and bias toward underestimating time-to-contact imply a tendency toward late arrival at a rendezvous.

METHODS

In a simplified simulation, participants controlled the speed and/or heading of their own ship once per scenario to try to rendezvous with another ship. Forty-five scenarios of approximately 30 s were conducted with different starting geometries and, in two of three experiments, with different frequencies and lengths of the unexpected delays.

RESULTS

Perfect rendezvous were hard to obtain, with a general tendency to arrive late and pass behind the target vessel, although this was dependent on the angle of approach and relative speed. When occasional delays were introduced, less frequent but longer delays disrupted performance more than shorter but more frequent delays. Where delays were possible, but no delay occurred, there was no longer evidence of a general tendency to more frequently pass behind the target ship. Additionally, people did not wait to see if the unpredictable delays would occur before executing a course of action. Different control strategies were deployed and dual axis control was preferred.

CONCLUSIONS

The tendency to arrive late and the influence of the possibility of uncertain delays are discussed in relationship to control strategies.

A Bayesian Regression Analysis of the Effects of Alert Presence and Scenario Criticality on Automated Vehicle Takeover Performance

OBJECTIVE

This study investigates the impact of silent and alerted failures on driver performance across two levels of scenario criticality during automated vehicle transitions of control.

BACKGROUND

Recent analyses of automated vehicle crashes show that many crashes occur after a transition of control or a silent automation failure. A substantial amount of research has been dedicated to investigating the impact of various factors on drivers' responses, but silent failures and their interactions with scenario criticality are understudied.

METHOD

A driving simulator study was conducted comparing scenario criticality, alert presence, and two driving scenarios. Bayesian regression models and Fisher's exact tests were used to investigate the impact of alert and scenario criticality on takeover performance.

RESULTS

The results show that silent failures increase takeover times and the intensity of posttakeover maximum accelerations and decrease the posttakeover minimum time-to-collision. While the predicted average impact of silent failures on takeover time was practically low, the effects on minimum time-to-collision and maximum accelerations were safety-significant. The analysis of posttakeover control interaction effects shows that the effect of alert presence differs by the scenario criticality.

CONCLUSION

Although the impact of the absence of an alert on takeover performance was less than that of scenario criticality, silent failures seem to play a substantial role-by leading to an unsafe maneuver-in critical automated vehicle takeovers.

APPLICATION

Understanding the implications of silent failure on driver's takeover performance can benefit the assessment of automated vehicles' safety and provide guidance for fail-safe system designs.

Distracted worker: Using pupil size and blink rate to detect cognitive load during manufacturing tasks

This study sets out to extend the use of blink rate and pupil size to the assessment of cognitive load of completing common automotive manufacturing tasks. Nonoptimal cognitive load is detrimental to safety. Existing occupational ergonomics approaches come short of measuring dynamic changes in cognitive load during complex assembling tasks. Cognitive demand was manipulated by having participants complete two versions of the n-back task (easy, hard). Two durations of the physical task were also considered (short, long). Pupil size and blink rate increased under greater cognitive task demand. High cognitive load also resulted in longer task completion times, and higher ratings of mental and temporal demand, and effort. This exploratory study offers relevant insights on the use of ocular metrics for cognitive load assessment in occupational ergonomics. While the existing eye-tracking technology may yet limit their adoption in the field, they offer advantages over the more popular expert-based and self-reported techniques in measuring changes in cognitive load during dynamic tasks.

Tools for Transport: Driven to Learn With Connected Vehicles

Vehicle automation and assistance technologies have been touted as a means to reduce traffic collisions by minimizing or eliminating "error-prone" and inefficient human operators. In concept, automation exists on a continuum that includes engaged driving by a human operator augmented by automated support features, vigilant driver monitoring of vehicle behavior with the possibility of driver take-over, to full automation with no active monitoring by a human operator. Moreover, the degree of automation varies by vehicle features (e.g., lane centering, emergency braking, adaptive cruise control, parking), by setting, meaning that automated features may or may not be available depending on specific attributes of the traffic environment (e.g., traffic volume, road geometry, etc), and by implementation (e.g., haptic vs. auditory warnings). Thus, these automotive "transportation tools" are highly heterogeneous and pose unique challenges and opportunities for driver training. In this paper, we report the results of an experimental study (n = 36) to determine if enhanced vehicle feedback influences driver trust, effort, frustration, and performance (indexed by reaction time) in a virtual driving environment. Results are contextualized in the extant literature on learning to operate motor vehicles and outline key research questions essential for understanding the processes by which skilled performance develops with respect to a real-world practical tool: the increasingly automated automobile.

John Senders, Human Error, and System Safety

OBJECTIVE

I examine John Senders' work and discuss his influence on the study of error causation,error mitigation, and sociotechnical system safety.

BACKGROUND

John Senders' passing calls for an evaluation of the impact of his work.

METHOD

I review literature and accident investigation findings to discuss themes in Senders' work and potential associations between that work and error causation and system safety.

RESULTS

Senders consistently emphasized empirical rigor and theoretical exploration in his research, with the desire to apply that work to enhance human performance. He has contributed to changing the way error has been viewed, and to developing and implementing programs and techniques to mitigate error. While a causal relationship between Senders' work and safety cannot be established, an association can be drawn between his research and efforts to mitigate error.

CONCLUSION

Because of Senders' work, we have a better understanding of error causation and enhanced ways of mitigating system errors. However, new sources of error, involving advanced systems and operators' knowledge and understanding of their functionalities can, if not addressed, degrade system safety.

APPLICATION

Modifications to advanced automation and operator training are suggested, and research to improve operator expertise in interacting with automated systems proposed.

Vision, attention, and driving

Safe driving demands the coordination of multiple sensory and cognitive functions, such as vision and attention. Patients with neurologic or ophthalmic disease are exposed to selective pathophysiologic insults to driving-critical systems, placing them at a higher risk for unsafe driving and restricted driving privileges. Here, we evaluate how vision and attention contribute to unsafe driving across different patient populations. In ophthalmic disease, we focus on macular degeneration, glaucoma, diabetic retinopathy, and cataract; in neurologic disease, we focus on Alzheimer's disease, Parkinson's disease, and multiple sclerosis. Unsafe driving is generally associated with impaired vision and attention in ophthalmic and neurologic patients, respectively. Furthermore, patients with ophthalmic disease experience some degree of impairment in attention. Similarly, patients with neurologic disease experience some degree of impairment in vision. While numerous studies have demonstrated a relationship between impaired vision and unsafe driving in neurologic disease, there remains a dearth of knowledge regarding the relationship between impaired attention and unsafe driving in ophthalmic disease. In summary, this chapter confirms-and offers opportunities for future research into-the contribution of vision and attention to safe driving.

Advanced vehicle technologies and road safety: A scoping review of the evidence

The proliferation of Advanced Vehicle Technologies (AVTs) has generated both excitement and concern among researchers, policymakers, and the general public. An increasing number of driver assistance systems are already available in today's automobiles; many of which are expected to become standard. Therefore, synthesizing the available evidence specific to the safety of AVTs is critical. The goal of this scoping review was to summarize this evidence with a focus on AVTs that require some driver oversight (i.e., Levels 0-3 as per the Society of Automotive Engineers (SAE) levels of automation taxonomy). A scoping review of research literature on AVTs was conducted for studies up to March 2018. Inclusion criteria consisted of: any study with empirical data of AVTs that included male and female drivers aged 16 years and older, healthy people (i.e., without impairments), passenger vehicles, driving simulators and/or large databases with road safety information that could be analyzed for the purpose of examining AVTs (SAE Levels 0-3), as well as measures of driving outcomes. A total of 324 peer-reviewed studies from 25 countries met the inclusion criteria for this review with over half published in the last 5 years. Data was extracted and summarized according to the following categories: measures used to evaluate the effect of AVTs on road safety (objective) and driver perceptions of the technology (subjective), testing environment, and study populations (i.e., driver age). The most commonly reported objective measures were longitudinal control (50 %), reaction time (40 %), and lateral position (23 %). The most common subjective measures were perceptions of trust (27 %), workload (20 %), and satisfaction (17 %). While most studies investigated singular AVTs (237 of 324 studies), the number of studies after 2013 that examined 2 or more AVTs concurrently increased. Studies involved drivers from different age groups (51 %) and were conducted in driving simulators (70 %). Overall, the evidence is generally in favour of AVTs having a positive effect on driving safety, although the nature and design of studies varied widely. Our examination of this evidence highlights the opportunities as well as the challenges involved with investigating AVTs. Ensuring such technologies are congruent with the needs of drivers, particularly younger and older driver age groups, who are known to have a higher crash risk, is critical. With automotive manufacturers keen to adopt the latest AVTs, this scoping review highlights how testing of this technology has been undertaken, with a focus on how new research can be conducted to improve road safety now and in the future.

Driving Into the Future

This work considers the future of driving in terms of both its short- and long-term horizons. It conjectures that human-controlled driving will follow in the footsteps of a wide swath of other, now either residual or abandoned human occupations. Pursuits that have preceded it into oblivion. In this way, driving will dwindle down into only a few niche locales wherein enthusiasts will still persist, much in the way that steam train hobbyists now continue their own aspirational inclinations. Of course, the value of any such prognostication is in direct proportion to the degree that information is conveyed, and prospective uncertainty reduced. In more colloquial terms: the devil is in the details of these coming transitions. It is anticipated that we will see a progressive transformation of the composition of on-road traffic that will be registered most immediately in the realm of professional transportation in which the imperative for optimization exceeds that in virtually all other user segments. The transition from manual control to full automation will be more punctate than gradualist in its evolutionary development. As performance optimization slowly exhausts the commercial sector, it will progressively transition more into the discretionary realm by dint of simple technology transfer alone. The hedonic dimension of everyday driving will be dispersed and pursued by progressively fewer individuals. The traveling window of generational expectation will soon mean that human driving will be largely “forgotten,” as each sequential generation matures without this, still presently common experience. Indications of this stage of progress are beginning to be witnessed in the demographic profile of vehicle usage and ownership rates. The purpose of the exposition which follows is to consider and support each of these stated propositions.

Preface to the Special Issue on Human Factors and Advanced Vehicle Automation: Of Benefits, Barriers, and Bridges to Safe and Effective Implementation

OBJECTIVE

The aim of this special issue is to bring together the latest research related to driver interaction with various types of vehicle automation.

BACKGROUND

Vehicle technology has undergone significant progress over the past decade, bringing new support features that can assist the driver and take on more and more of the driving responsibilities.

METHOD

This issue is comprised of eight articles from international research teams, focusing on different types of automation and different user populations, including driver support features through to highly automated driving systems.

RESULTS

The papers comprising this special issue are clustered into three categories: (a) experimental studies of driver interactions with advanced vehicle technologies; (b) analysis of existing data sources; and (c) emerging human factors issues. Studies of currently available and pending systems highlight some of the human factors challenges associated with the driver-system interaction that are likely to become more prominent in the near future. Moreover, studies of more nascent concepts (i.e., those that are still a long way from production vehicles) underscore many attitudes, perceptions, and concerns that will need to be considered as these technologies progress.

CONCLUSIONS

Collectively, the papers comprising this special issue help fill some gaps in our knowledge. More importantly, they continue to help us identify and articulate some of the important and potential human factors barriers, design considerations, and research needs as these technologies become more ubiquitous.