Speech-based interaction with in-vehicle computers: the effect of speech-based e-mail on drivers' attention to the roadway

Lights, Sirens, and Load: Anticipatory emergency medical treatment planning causes cognitive load during emergency response driving among paramedicine students

Paramedics face various unconventional and secondary task demands while driving ambulances, leading to significant cognitive load, especially during lights-and-sirens responses. Previous research suggests that high cognitive load negatively affects driving performance, increasing the risk of accidents, particularly for inexperienced drivers. The current study investigated the impact of anticipatory treatment planning on cognitive load during emergency driving, as assessed through the use of a driving simulator. We recruited 28 non-paramedic participants to complete a simulated baseline drive with no task and a cognitive load manipulation using the 1-back task. We also recruited 18 paramedicine students who completed a drive while considering two cases they were travelling to: cardiac arrest and infant seizure, representing varying difficulty in required treatment. The results indicated that both cases imposed considerable cognitive load, as indicated by NASA Task Load Index responses, comparable to the 1-back task and significantly higher than driving with no load. These findings suggest that contemplating cases and treatment plans may impact the safety of novice paramedics driving ambulances for emergency response. Further research should explore the influence of experience and the presence of a second individual in the vehicle to generalise to broader emergency response driving contexts.

A Novel Asynchronous Brain Signals-Based Driver-Vehicle Interface for Brain-Controlled Vehicles

Directly applying brain signals to operate a mobile manned platform, such as a vehicle, may help people with neuromuscular disorders regain their driving ability. In this paper, we developed a novel electroencephalogram (EEG) signal-based driver-vehicle interface (DVI) for the continuous and asynchronous control of brain-controlled vehicles. The proposed DVI consists of the user interface, the command decoding algorithm, and the control model. The user interface is designed to present the control commands and induce the corresponding brain patterns. The command decoding algorithm is developed to decode the control command. The control model is built to convert the decoded commands to control signals. Offline experimental results show that the developed DVI can generate a motion control command with an accuracy of 83.59% and a detection time of about 2 s, while it has a recognition accuracy of 90.06% in idle states. A real-time brain-controlled simulated vehicle based on the DVI was developed and tested on a U-turn road. Experimental results show the feasibility of the DVI for continuously and asynchronously controlling a vehicle. This work not only advances the research on brain-controlled vehicles but also provides valuable insights into driver-vehicle interfaces, multimodal interaction, and intelligent vehicles.

Visual and cognitive demands of manual and voice-based driving mode implementations on smartphones

Mobile phone apps and operating systems are increasingly adopting driving mode functions that attempt to reduce driver visual and cognitive demand by limiting functionality, using larger buttons and icons, and adding voice-based interactions. The present study assessed the visual and cognitive demands and the subjective level of distraction from two driving mode implementations (voice or manual) on an Android™ mobile phone using Google Assistant™, compared to a typical mobile phone operating system experience. While driving on a test track, participants performed several trials of five tasks on each of three interfaces: A mobile operating system interface, a manual driving mode interface, and a voice driving mode interface. Visual demand was measured with eye-gaze recordings, cognitive load was measured with the detection response task, and a Likert scale was used to rate the perceived level of distraction. The voice driving mode resulted in the lowest visual attention demand and lowest subjective ratings of distraction. The manual driving mode condition also reduced visual demand and subjective ratings of distraction relative to the mobile operating system condition. The cognitive load results were inconsistent across the task and interaction mode conditions. Overall, the results of this study provide positive evidence in support of voice-based driving mode implementations for reducing visual demand and subjective levels of distraction from mobile devices while driving. Moreover, the results suggest that manual driving mode implementations also have the potential to reduce visual demand and subjective levels of distraction, relative to the mobile operating system condition.

How is the duration of distraction related to safety-critical events? Harnessing naturalistic driving data to explore the role of driving instability

INTRODUCTION

Due to a variety of secondary tasks performed by drivers, distracted driving has become a critical concern. At 50 mph, sending/reading a text for 5 seconds is equivalent to driving the length of a football field (360 ft) with eyes closed. A fundamental understanding of how distractions lead to crashes is needed to develop appropriate countermeasure strategies. A key question is whether distraction increases driving instability, which then further contributes to safety-critical events (SCEs).

METHODS

By harnessing newly available microscopic driving data and using the safe systems approach, a subsample of naturalistic driving study data were analyzed, collected through the second strategic highway research program. Rigorous path analysis (including Tobit and Ordered Probit regressions) is used to jointly model the instability in driving (using coefficient of variation of speed) and event outcomes (including baseline, near-crash, and crash). The marginal effects from the two models are used to compute direct, indirect, and total effects of distraction duration on SCEs.

RESULTS

Results indicate that a longer duration of distraction was positively but non-linearly associated with higher driving instability and higher chances of SCEs. Where, the chance of a crash and near-crash was higher by 34% and 40%, respectively, with a unit increase in driving instability. Based on the results, the chance of both SCEs significantly increases non-linearly with an increase in distraction duration beyond 3 seconds. For instance, the chance of a crash is 16% for a driver distracted for 3 seconds, which increases to 29% if a driver is distracted for 10 seconds.

CONCLUSIONS AND PRACTICAL APPLICATIONS

Using path analysis, the total effects of distraction duration on SCEs are even higher when its indirect effects on SCEs through driving instability are considered. Potential practical implications including traditional countermeasures (changes in roadway environments) and vehicle technologies are discussed in the paper.

On the impact of advanced driver assistance systems on driving distraction and risky behaviour: An empirical analysis of irish commercial drivers

Advanced driver assistance systems (ADAS) present promising benefits in mitigating road collisions. However, these benefits are limited when risky drivers continue engaging in distraction events. While there is evidence that real-time warnings help improve driving behaviour, the sustained benefits of warning-based ADAS on reducing driving distraction in light commercial vehicle (LCV) drivers remain unclear. This research determines the effect of receiving instant distraction warnings over two years using a naturalistic driving dataset comprising around one million trips from 373 LCV drivers in the Republic of Ireland. Furthermore, the study applies Association Rule Mining (ARM) to find the contextual variables (e.g., speed limit, road type, traffic conditions) that increase the likelihood of distraction events. The results show that warning-based ADAS providing real-time warnings helps reduce distraction events triggering driver inattention, forward collision, and lane departure warnings. Over half of the studied fleet reduced these warnings by at least 50% - lane departure after two months and driver inattention and forward collision after six months. It is found that both passive and active monitoring systems, coupled with coaching and rewards, significantly reduce aggressive driving behaviours tied to harsh acceleration (by 76%) and harsh braking (by 65%). The results of ARM show that the driving context introduces explanatory information for road safety programs. Low-speed urban roads and the summer season increase the likelihood of driver inattention and forward collision warnings. In contrast, high-speed rural roads increase the likelihood of lane departure warnings. These research findings support road safety stakeholders in developing risk assessments based on warning-based ADAS, targeted campaigns to reduce driving distraction, and driving coaching programs.

Factors That Affect Drivers' Perception of Closing and an Immediate Hazard

OBJECTIVE

To measure the looming threshold for when drivers perceive closing and an immediate hazard and determine what factors affect these thresholds.

BACKGROUND

Rear-end collisions are a common type of crash. One key issue is determining when drivers first perceive they need to react. The looming threshold for closing and an immediate hazard are critical perceptual thresholds that reflect when drivers perceive they need to react.

METHOD

Two driving simulator experiments examined whether engaging in a cell phone conversation and whether the complexity of the roadway environment affect these thresholds for the perception of closing and immediate hazard. Half of the participants engaged in a cognitive task, the last letter task, to emulate a cell phone conversation, and all participants experienced both simple and complex roadway environments.

RESULTS

Drivers perceived an immediate hazard later when engaged in a cell phone conversation than when not engaged in a conversation but only when the driving task was relatively less demanding (e.g., simple roadway, slow closing velocity). Compared to simple scenes, drivers perceived closing and an immediate hazard later for complex scenes but only when closing velocity was 30 mph (48.28 km/h) or greater.

CONCLUSION

Cell phone conversation can affect when drivers perceive an immediate hazard when the roadway is less demanding. Roadway complexity can affect when drivers perceive closing and an immediate hazard when closing velocity is high.

APPLICATION

Results can aid accident analysis cases and the design of driving automation systems by suggesting when a typical driver would respond.

Multimodal interaction: Input-output modality combinations for identification tasks in augmented reality

Multimodal interaction (MMI) is being widely implemented, especially in new technologies such as augmented reality (AR) systems since it is presumed to support a more natural, efficient, and flexible form of interaction. However, limited research has been done to investigate the proper application of MMI in AR. More specifically, the effects of combining different input and output modalities during MMI in AR are still not fully understood. Therefore, this study aims to examine the independent and combined effects of different input and output modalities during a typical AR task. 20 young adults participated in a controlled experiment in which they were asked to perform a simple identification task using an AR device in different input (speech, gesture, multimodal) and output (VV-VA, VV-NA, NV-VA, NV-NA) conditions. Results showed that there were differences in the influence of input and output modalities on task performance, workload, perceived appropriateness, and user preference. Interaction effects between the input and output conditions on the performance metrics were also evident in this study, suggesting that although multimodal input is generally preferred by the users, it should be implemented with caution since its effectiveness is highly influenced by the processing code of the system output. This study, which is the first of its kind, has revealed several new implications regarding the application of MMI in AR systems.

Development of a Real-Time Simulator for a Semi-Autonomous Tele-Robot in an Unknown Narrow Path

This study proposes a teleoperation system for assistive controlling of the movement of a mobile robot in a narrow path. The teleoperation system is created by combining data from real and virtual devices. In CoppeliaSim we applied the Braitenberg algorithm and the open motion planning library module (OMPL). The Braitenberg algorithm is a sensor-based automatic motion designed to aid the robot operator in maneuvering through the narrow path. While the OMPL is used to create a path for the operator to control the robot in narrow paths or intersections within a narrow path, the simulation uses a virtual proximity sensor to fulfill the Braitenberg algorithm requirement. With dynamic simulation a laser rangefinder obtains the environmental data and displays it on the simulation screen. The simulation scene is subjected to the virtual proximity sensor and the Braitenberg algorithm is applied to the simulation scene. Afterward, simulation scripts are written to incorporate the linear and angular velocities into a robot operating system for real-time robot control. The results showed that the system was capable of combining real-time dynamic simulation with the real world. Furthermore, the proposed system could aid the operator in narrow path environments while avoiding collision.

Effects of different takeover request interfaces on takeover behavior and performance during conditionally automated driving

Automated driving is a developing trend that is coming to the consumer market, and conditionally automated driving (CAD) is anticipated to become the primary automated driving system. For enhancing both the comfort and security of human drivers in self-driving cars, the most significant concern of CAD is ensuring that not only can the driver conduct non-driving related tasks (NDRT) while automated driving is in progress, but also quickly and competently take over when the system reaches a limit and issues a takeover request (TOR). However, the level of distraction by NDRTs may affect the transition from automated driving to the human driver taking over. The focus of the present study was allowing a driver immersed in NDRTs to discover the TOR and take control of the driving quickly. A 3×2×2 factor experimental design was used: vehicle display interface information load (basic vs. prediction vs. advanced prediction interfaces); TOR information load (directional vs. non-directional information notifications); and degree of NDRT immersion (not performing vs. performing an NDRT when TOR prompt was issued). 48 participants were recruited, and different automotive display interfaces were used as TOR prompts with different information loads during driving to analyze the takeover behavior, performance, and subjective perception of the drivers, who were immersed in a smartphone-related task. The takeover process out of NDRT immersion was found to be more efficient with the advanced prediction interface, compared to the other two interfaces. All groups achieved faster takeovers and demonstrated better takeover performance if given directional rather than non-directional information, regardless of interface type or NDRT immersion.

“Just One Short Voice Message”—Comparing the Effects of Text- vs. Voice-Based Answering to Text Messages via Smartphone on Young Drivers’ Driving Performances

Despite the well-known distracting effects, many drivers still engage in phone use, especially texting and especially among young drivers, with new emerging messaging modes. The present study aims to examine the effects of different answering modes on driving performance. Twenty-four students (12 females), aged between 19 and 25 years (M = 20.83, SD = 1.53), volunteered for the study. They accomplished the Lane Change Task (LCT) with baseline and dual-task runs in a driving simulator. In dual-task runs, participants answered text messages on a smartphone by voice or text message with varying task complexity. Driving performance was measured by lane deviation (LCT) and subjective measures (NASA-TLX). Across all trials, driving performance deteriorated during dual-task runs compared with the baseline runs, and subjective demand increased. Analysis of dual-task runs showed a benefit for voice-based answering to received text messages that leveled off in the complex task. All in all, the benefits of using voice-based answering in comparison with text-based answering were found regarding driving performance and subjective measures. Nevertheless, this benefit was mostly lost in the complex task, and both the driving performance and the demand measured in the baseline conditions could not be reached.

Allocation of Driver Attention for Varying In-Vehicle System Modalities

OBJECTIVE

This paper examines drivers' allocation of attention using response time to a tactile detection response task (TDRT) while interacting with an in-vehicle information system (IVIS) over time.

BACKGROUND

Longer TDRT response time is associated with higher cognitive workload. However, it is not clear what role is assumed by the human and system in response to varying in-vehicle environments over time.

METHOD

A driving simulator study with 24 participants was conducted with a restaurant selection task of two difficulty levels (easy and hard) presented in three modalities (audio only, visual only, hybrid). A linear mixed-effects model was applied to identify factors that affect TDRT response time. A nonparametric time-series model was also used to explore the visual attention allocation under the hybrid mode over time.

RESULTS

The visual-only mode significantly increased participants' response time compared with the audio-only mode. Females took longer to respond to the TDRT when engaged with an IVIS. The study showed that participants tend to use the visual component more toward the end of the easy tasks, whereas the visual mode was used more at the beginning of the harder tasks.

CONCLUSION

The visual-only mode of the IVIS increased drivers' cognitive workload when compared with the auditory-only mode. Drivers showed different visual attention allocation during the easy and hard restaurant selection tasks in the hybrid mode.

APPLICATION

The findings can help guide the design of automotive user interfaces and help manage cognitive workload.

Improving Drivers' Hazard Perception and Performance Using a Less Visually-Demanding Interface

In-vehicle devices and infotainment systems occasionally lead to driver distraction, and as a result, increase the risk of missing on-road information. In the current study, a novel multi-touch interface for an in-vehicle infotainment system was evaluated, which potentially requires less visual attention and thus may reduce distraction and increase safety. The interface was compared with a functionally similar control interface in terms of hazard perception metrics and mental workload. Twenty-two participants drove a simulated route once with each system. During each drive, which included eight potentially-hazardous scenarios, participants were instructed to interact with one of the in-vehicle interfaces to perform phone calls or to navigate to specified destinations. Eye-gaze data were collected throughout the drive to evaluate whether participants detected the hazards while interacting with the in-vehicle interface, how much time they needed to identify them, and for how long they engaged with the secondary task. Additionally, after each drive, participants completed a NASA R-TLX questionnaire to evaluate their subjective workload during their engagement with the secondary tasks. Participants using the multi-touch interface needed less time to complete each secondary task and were quicker at identifying potential hazards around them. However, the probability of detecting hazards was similar for both interfaces. Finally, when using the multi-touch interface, participants reported lower subjective workload. The use of a multi-touch interface was found to improve drivers' performance in terms of identifying hazards quicker than the control condition. The road safety and driver distraction implications of this novel interface are discussed.

Effects of Cell Phone Conversation on the First Driver Response to a Stopped Lead Vehicle

Despite ample research on the effects of cell phone conversations on driving, the effects of such conversations on the looming threshold for an immediate hazard are not known. Prior research on the looming threshold for an immediate hazard in the absence of cell phone conversation indicated that the rate of optical expansion at threshold was .006 radians per second. We measured the rate of optical expansion and headway distance at first driving input when participants encountered a stopped lead vehicle while completing a car-following task. Half of them concurrently completed the Last Letter Task, a cognitive task that emulates a cell phone conversation. When compared to the second, third, and fourth scenario exposures to the stopped lead vehicle, the participant’s response on the first scenario exposure occurred when the lead vehicle’s optical expansion rate was relatively smaller and headway distance was larger. However, this effect of scenario exposure occurred only when drivers were engaged in a cell phone conversation. Additionally, participants started to initiate a response when the rate of optical expansion was much lower than the looming threshold reported in previous research. Our results indicate that the first driver input, as operationalized in the current study, does not indicate when drivers first perceive an immediate hazard.

Adaptive forward collision warnings: The impact of imperfect technology on behavioral adaptation, warning effectiveness and acceptance

Adaptive ADAS that adjust warnings according to the driver´s current need for support offer a great potential to increase safety. However, it is crucial to understand how drivers deal with dynamically adapting technologies particularly in situations in which driver state monitoring fails and the system shows unexpected behavior. To better understand the consequences of unreliable adaptive ADAS on safety and to assess how failures of an adaptive FCW influence driving behavior, we conducted a driving simulator study with N = 48 participants. Participants experienced critical brake events in situations with and without a distracting secondary task. An adaptive FCW provided visual warnings to undistracted drivers but highly supportive visuo-haptic warnings (brake jerks or vibration) to distracted drivers. In 20% of brake events, however, the system unexpectedly provided incorrectly adapted warnings in which the combination of warning type and distraction was reversed. This adaptive FCW was compared to a non-adaptive standard FCW that provided visual warnings only. We found that incorrect warnings impaired driver reactions and safety in distracted drivers, and these adverse behavioral effects had two sources: (1) Violations of the drivers´ expectancies about the warning, and hence, behavioral adaptation. (2) The absence of the compensatory effect of the highly supportive warning in case of distraction. In contrast, correctly adapted warnings reduced decrements in brake reaction times and fully offset safety deficits associated with driver distraction. Crucially, however, an effectiveness evaluation of the adaptive system's potential to support drivers when correct warnings were elicited failed to demonstrate a benefit of the adaptive FCW over the non-adaptive FCW. Our results thus emphasize that a high reliability is crucial for adaptive ADAS to improve safety and to prevent adverse effects due to behavioral adaptation.

Understanding driver distractions in fatal crashes: An exploratory empirical analysis

INTRODUCTION

Driver distraction has become a significant problem in transportation safety. As more portable wireless devices and driver assistance and entertainment systems become available to drivers, the sources of distraction are increasing.

METHOD

Based on the results of different studies in the literature review, this paper categorizes different distraction enablers into six subcategories according to their fundamental characteristics and how they would affect a driver's likelihood of engaging in non-driving related activities. The review also discusses the characteristics and influence of external and internal distractions. The objective of this study is to examine the effect of different distraction sources in fatal crashes with the consideration of a driver's age and sex. Tukey test, chi-square test of independence, Nemenyi post-hoc test, and Marascuilo procedure have been used to investigate the top distraction sources, the trend of distraction-affected fatal crashes, the effect of different distractions on drives in different age groups, and their influence on female and male drivers.

RESULTS

It was found that inner cognitive inferences accounted for the greatest proportion of driver engagement in distractions. Young drivers show a larger probability of being distracted by in-vehicle technology-related devices/objects. Within the group of young drivers, female drivers showed a higher probability than their male counterparts of engaging in distracted driving caused by in-vehicle technology-related devices. Among six subcategories of distractions, drivers older than 80 years old were found to be most likely affected by inner cognitive interferences.

Impact of adolescent media multitasking on cognition and driving safety

Adolescence is a critical period in brain development particularly in regions related to attention and executive function (EF). As the use of electronics and media in daily activities increases, one essential question is how adolescent attention development and related executive and speed processes are impacted by media multitasking (MM), or the simultaneous use of media (e.g., text messaging while watching television). This review examines current literature concerning (a) the prevalence of MM during adolescence; (b) relations between MM and adolescent cognitive development, specifically attention, speed of processing, and EF; and (c) real-world implications of MM including adolescents and driver distraction. Finally, future challenges and opportunities in MM research are explored with special attention given to overcoming the limitations of current research in this area and the critical need to advance our understanding of the impact of MM on adolescent driver safety.

Bibliometric analysis of simulated driving research from 1997 to 2016

OBJECTIVE

The objective of this study was to explore the evolution footprints of simulated driving research in the past 20 years through rigorous and systematic bibliometric analysis, to provide insights regarding when and where the research was performed and by whom and how the mainstream content evolved over the years.

METHODS

The analysis began with data retrieval in Web of Science with defined search terms related to simulated driving. BibExcel and CiteSpace were employed to conduct the performance analysis and co-citation network analysis; that is, probe of the performance of institutes, journals, authors, and research hotspots.

RESULTS

A total of 3,766 documents were filtered out and presented an exponential growth from 1997 to 2016. The United States contributed the most publications as well as international collaborations followed by Germany and China. In addition, several universities in The Netherlands and the United States dominated the list of contributing institutes. The leading journals were in transportation and ergonomics. The leading researchers were also recognized among the 8,721 contributing authors, such as J. D. Lee, D. L. Fisher, J. H. Kim, and K. A. Brookhuis. Finally, the co-citation analysis illuminated the evolution of simulated driving research that covered the following topics roughly in chronological order: task-induced stress, drivers with neurological disorders, alertness and sleepiness while driving, trust toward driving assistance systems, driver distraction, the effect of drug use, the validity of simulators, and automated driving.

CONCLUSIONS

This article employed bibliometric tools to probe the contributing countries, institutes, journals, authors, and mainstream hotspots of simulated driving research in the past 20 years. A systematic bibliometric analysis of this field will help researchers realize the panorama of global simulated driving and establish future research directions.

Effects of Cognitive Load and Anticipation on Driver Responses to a Critical Traffic Event

Existing studies on the effects of cognitive load on drivers’ responses to critical traffic events have yielded inconsistent results. The recently proposed cognitive control hypothesis offers a potential explanation for this discrepancy by suggesting that cognitive load selectively impairs aspects of driving relying on cognitive control, that is, novel, non-practiced or inherently difficult tasks, but leaves automatized responses unaffected. The present driving simulator study addressed one specific prediction of the cognitive control hypothesis, namely that the effect of cognitive load on responses to a traffic event should depend on whether the event it anticipated. The results generally supported this prediction, showing no effects of cognitive load on braking and gaze responses to an initial non-anticipated event and gradually increasing cognitive load effects as the scenario was repeated.

Effect of police mobile computer terminal interface design on officer driving distraction

Several crash reports have identified in-vehicle distraction to be a primary cause of emergency vehicle crashes especially in law enforcement. Furthermore, studies have found that mobile computer terminals (MCTs) are the most frequently used in-vehicle technology for police officers. Twenty police officers participated in a driving simulator-based assessment of visual behavior, performance, workload and situation awareness with current and enhanced MCT interface designs. In general, results revealed MCT use while driving to decrease officer visual attention to the roadway, but usability improvements can reduce the level of visual distraction and secondary-task completion time. Results also suggest that use of MCTs while driving significantly reduces perceived level of driving environment awareness for police officers and increases cognitive workload. These findings may be useful for MCT manufacturers in improving interface designs to increase police officer and civilian safety.

How safe is tuning a radio?: using the radio tuning task as a benchmark for distracted driving

Drivers engage in non-driving tasks while driving, such as interactions entertainment systems. Studies have identified glance patterns related to such interactions, and manual radio tuning has been used as a reference task to set an upper bound on the acceptable demand of interactions. Consequently, some view the risk associated with radio tuning as defining the upper limit of glance measures associated with visual-manual in-vehicle activities. However, we have little knowledge about the actual degree of crash risk that radio tuning poses and, by extension, the risk of tasks that have similar glance patterns as the radio tuning task. In the current study, we use counterfactual simulation to take the glance patterns for manual radio tuning tasks from an on-road experiment and apply these patterns to lead-vehicle events observed in naturalistic driving studies. We then quantify how often the glance patterns from radio tuning are associated with rear-end crashes, compared to driving only situations. We used the pre-crash kinematics from 34 crash events from the SHRP2 naturalistic driving study to investigate the effect of radio tuning in crash-imminent situations, and we also investigated the effect of radio tuning on 2,475 routine braking events from the Safety Pilot project. The counterfactual simulation showed that off-road glances transform some near-crashes that could have been avoided into crashes, and glance patterns observed in on-road radio tuning experiment produced 2.85-5.00 times more crashes than baseline driving.

A meta-analysis of in-vehicle and nomadic voice-recognition system interaction and driving performance

Driver distraction is a growing and pervasive issue that requires multiple solutions. Voice-recognition (V-R) systems may decrease the visual-manual (V-M) demands of a wide range of in-vehicle system and smartphone interactions. However, the degree that V-R systems integrated into vehicles or available in mobile phone applications affect driver distraction is incompletely understood. A comprehensive meta-analysis of experimental studies was conducted to address this knowledge gap. To meet study inclusion criteria, drivers had to interact with a V-R system while driving and doing everyday V-R tasks such as dialing, initiating a call, texting, emailing, destination entry or music selection. Coded dependent variables included detection, reaction time, lateral position, speed and headway. Comparisons of V-R systems with baseline driving and/or a V-M condition were also coded. Of 817 identified citations, 43 studies involving 2000 drivers and 183 effect sizes (r) were analyzed in the meta-analysis. Compared to baseline, driving while interacting with a V-R system is associated with increases in reaction time and lane positioning, and decreases in detection. When V-M systems were compared to V-R systems, drivers had slightly better performance with the latter system on reaction time, lane positioning and headway. Although V-R systems have some driving performance advantages over V-M systems, they have a distraction cost relative to driving without any system at all. The pattern of results indicates that V-R systems impose moderate distraction costs on driving. In addition, drivers minimally engage in compensatory performance adjustments such as reducing speed and increasing headway while using V-R systems. Implications of the results for theory, design guidelines and future research are discussed.

Effects of Cognitive Load on Driving Performance: The Cognitive Control Hypothesis

OBJECTIVE

The objective of this paper was to outline an explanatory framework for understanding effects of cognitive load on driving performance and to review the existing experimental literature in the light of this framework.

BACKGROUND

Although there is general consensus that taking the eyes off the forward roadway significantly impairs most aspects of driving, the effects of primarily cognitively loading tasks on driving performance are not well understood.

METHOD

Based on existing models of driver attention, an explanatory framework was outlined. This framework can be summarized in terms of the cognitive control hypothesis: Cognitive load selectively impairs driving subtasks that rely on cognitive control but leaves automatic performance unaffected. An extensive literature review was conducted wherein existing results were reinterpreted based on the proposed framework.

RESULTS

It was demonstrated that the general pattern of experimental results reported in the literature aligns well with the cognitive control hypothesis and that several apparent discrepancies between studies can be reconciled based on the proposed framework. More specifically, performance on nonpracticed or inherently variable tasks, relying on cognitive control, is consistently impaired by cognitive load, whereas the performance on automatized (well-practiced and consistently mapped) tasks is unaffected and sometimes even improved.

CONCLUSION

Effects of cognitive load on driving are strongly selective and task dependent.

APPLICATION

The present results have important implications for the generalization of results obtained from experimental studies to real-world driving. The proposed framework can also serve to guide future research on the potential causal role of cognitive load in real-world crashes.

Effects of auditory and tactile warning on response to visual hazards under a noisy environment

A warning signal presented via a visual or an auditory cue might interfere with auditory or visual information inside and outside a vehicle. On the other hand, such interference would be certainly reduced if a tactile cue is used. Therefore, it is expected that tactile cues would be promising as warning signals, especially in a noisy environment. In order to determine the most suitable modality of cue (warning) to a visual hazard in noisy environments, auditory and tactile cues were examined in this study. The condition of stimulus onset asynchrony (SOA) was set to 0ms, 500ms, and 1000ms. Two types of noises were used: white noise and noise outside a vehicle recorded in a real-world driving environment. The noise level LA_eq (equivalent continuous A-weighted sound pressure level) inside the experimental chamber of each type of noise was adjusted to approximately 60 dB (A), 70 dB (A), and 80 dB (A). As a result, it was verified that tactile warning was more effective than auditory warning. When the noise outside a vehicle from a real-driving environment was used as the noise inside the experimental chamber, the reaction time to the auditory warning was not affected by the noise level.

What's the law got to do with it? Legislation regarding in-vehicle technology use and its impact on driver distraction

Legislation in the road transport domain aims to control safety on the roads. Despite this, a critical issue affecting road safety is that of driver distraction. Although poorly defined, distraction is a significant road safety issue which, in part, is caused by the prevalence of technology within vehicles. Legislation surrounding the use of in-vehicle technologies are explored in this paper from a socio-technical system perspective. This reveals the wider context of the road transport system operating under the current laws using an Accimap analysis. A distinction in the law between the use of hand-held mobile phones, a device that is typically banned for use by drivers worldwide, and the use of other technological devices that are covered by more general laws against 'careless' and/or 'dangerous' driving was found. Historically, individual drivers' have been blamed for distraction, whereas the systems approach shows how current legislation may have created the conditions necessary for driver distraction.

Use, perceptions, and benefits of automotive technologies among aging drivers

Advanced in-vehicle technologies have been proposed as a potential way to keep older adults driving for as long as they can safely do so, by taking into account the common declines in functional abilities experienced by older adults. The purpose of this report was to synthesize the knowledge about older drivers and advanced in-vehicle technologies, focusing on three areas: use (how older drivers use these technologies), perception (what they think about the technologies), and outcomes (the safety and/or comfort benefits of the technologies). Twelve technologies were selected for review and grouped into three categories: crash avoidance systems (lane departure warning, curve speed warning, forward collision warning, blind spot warning, parking assistance); in-vehicle information systems (navigation assistance, intelligent speed adaptation); and other systems (adaptive cruise control, automatic crash notification, night vision enhancement, adaptive headlight, voice activated control). A comprehensive and systematic search was conducted for each technology to collect related publications. 271 articles were included into the final review. Research findings for each of the 12 technologies are synthesized in relation to how older adults use and think about the technologies as well as potential benefits. These results are presented separately for each technology. Can advanced in-vehicle technologies help extend the period over which an older adult can drive safely? This report answers this question with an optimistic "yes." Some of the technologies reviewed in this report have been shown to help older drivers avoid crashes, improve the ease and comfort of driving, and travel to places and at times that they might normally avoid.

Talking to your car can drive you to distraction

This research examined the impact of in-vehicle information system (IVIS) interactions on the driver’s cognitive workload; 257 subjects participated in a weeklong evaluation of the IVIS interaction in one of ten different model-year 2015 automobiles. After an initial assessment of the cognitive workload associated with using the IVIS, participants took the vehicle home for 5 days and practiced using the system. At the end of the 5 days of practice, participants returned and the workload of these IVIS interactions was reassessed. The cognitive workload was found to be moderate to high, averaging 3.34 on a 5-point scale and ranged from 2.37 to 4.57. The workload was associated with the intuitiveness and complexity of the system and the time it took participants to complete the interaction. The workload experienced by older drivers was significantly greater than that experienced by younger drivers performing the same operations. Practice did not eliminate the interference from IVIS interactions. In fact, IVIS interactions that were difficult on the first day were still relatively difficult to perform after a week of practice. Finally, there were long-lasting residual costs after the IVIS interactions had terminated. The higher levels of workload should serve as a caution that these voice-based interactions can be cognitively demanding and ought not to be used indiscriminately while operating a motor vehicle.

Taxonomy of Mitigation Strategies for Driver Distraction

Driver distraction can be described as the diversion of driver's attention from the primary task of driving and is one of the most common causes of crashes. Complex technologies that have either been introduced to the driving domain or are planned to be, raise the concern of high levels of distraction, by placing additional demands on drivers. Different mitigation strategies (e.g., warning and vehicle control) have been implemented in the vehicle to reduce driver distraction. However there has not been a clear definition or categorization of these strategies. This paper, therefore, proposes a taxonomy of mitigation strategies for driver distraction and relates the strategies to accumulated research in the areas of automation and adaptive aiding to define important design tradeoffs with each strategy. This taxonomy provides a framework that can guide research and address the driver distraction problem systematically.

Human-Automation Interaction

Automation does not mean humans are replaced; quite the opposite. Increasingly, humans are asked to interact with automation in complex and typically large-scale systems, including aircraft and air traffic control, nuclear power, manufacturing plants, military systems, homes, and hospitals. This is not an easy or error-free task for either the system designer or the human operator/automation supervisor, especially as computer technology becomes ever more sophisticated. This review outlines recent research and challenges in the area, including taxonomies and qualitative models of human-automation interaction; descriptions of automation-related accidents and studies of adaptive automation; and social, political, and ethical issues.

Driving Safety

Driving is a common and hazardous activity that is a prominent cause of death worldwide. Driver behavior represents a predominant cause, contributing to over 90% of crashes. In this review, I will focus on how driver behavior influences driving safety by describing the types of crashes and their general causes, the driving process, the perceptual and cognitive characteristics of drivers, and driver types and impairments. Evidence from each of these perspectives suggests that breakdowns of a multilevel control process are the fundamental factors that undermine driving safety. Drivers adapt and drive safely in a broad range of situations but fail when expectations are violated or when feedback is inadequate. The review concludes by considering driving safety from a societal risk management perspective.

Cognitive Workload Using Interactive Voice Messaging Systems

The current research sought to understand the sources of cognitive distraction stemming from voice-based in-vehicle infotainment systems (IVIS) to send and receive textual information. Three experiments each evaluated 1) a baseline single-task condition, 2) listening to e-mail/text messages read by a “natural” pre-recorded human voice, 3) listening to e-mail/text messages read by a “synthetic” computerized text-to-speech system, 4) listening and composing replies to e-mail/text messages read by a “natural” voice, and 5) listening and composing replies to e-mail/text messages read by a “synthetic” voice. Each task allowed the driver to keep their eyes on the road and their hands on the steering wheel, thus any impairment to driving was caused by the diversion of non-visual attention away from the task of operating the motor vehicle.

Changes over 12 months in eye glances during secondary task engagement among novice drivers

During their first year of driving, crash rates among novice drivers are very high but decline rapidly. However, it is not clear what skills or knowledge they are acquiring in this period. Secondary task engagement while driving is a contributing factor to many traffic collisions and some of the elevated crash risk among novices could be explained by greater prevalence or longer periods of eyes off the road while engaging in these non-driving tasks. The current study looked at the eye glances of novice teen drivers engaging in secondary tasks on a test track at 0 and 12 months of licensure and compared their performance with their parents. Novices improved from 0 to 12 months on their longest single glance off the forward roadway and total percentage of time for eyes off the forward roadway, but parents remained stable. Compared with their parents, the longest single glance off the forward roadway was longer for novices at 0 months, but by 12 months there was no difference between the groups. However, for total percentage of time for eyes off the forward roadway, novices performed the same as their parents at 0 months and actually had shorter times at 12 months. These findings could reflect the combined development of driving skills over 12 months and the relative experience that modern teenagers have with portable electronic devices. The results suggest that novice drivers are particularly poor at engaging with secondary tasks while driving.

Multi-modal assessment of on-road demand of voice and manual phone calling and voice navigation entry across two embedded vehicle systems

One purpose of integrating voice interfaces into embedded vehicle systems is to reduce drivers' visual and manual distractions with 'infotainment' technologies. However, there is scant research on actual benefits in production vehicles or how different interface designs affect attentional demands. Driving performance, visual engagement, and indices of workload (heart rate, skin conductance, subjective ratings) were assessed in 80 drivers randomly assigned to drive a 2013 Chevrolet Equinox or Volvo XC60. The Chevrolet MyLink system allowed completing tasks with one voice command, while the Volvo Sensus required multiple commands to navigate the menu structure. When calling a phone contact, both voice systems reduced visual demand relative to the visual-manual interfaces, with reductions for drivers in the Equinox being greater. The Equinox 'one-shot' voice command showed advantages during contact calling but had significantly higher error rates than Sensus during destination address entry. For both secondary tasks, neither voice interface entirely eliminated visual demand. Practitioner Summary: The findings reinforce the observation that most, if not all, automotive auditory-vocal interfaces are multi-modal interfaces in which the full range of potential demands (auditory, vocal, visual, manipulative, cognitive, tactile, etc.) need to be considered in developing optimal implementations and evaluating drivers' interaction with the systems. Social Media: In-vehicle voice-interfaces can reduce visual demand but do not eliminate it and all types of demand need to be taken into account in a comprehensive evaluation.

Assessing Cognitive Distraction in the Automobile

OBJECTIVE

The objective was to establish a systematic framework for measuring and understanding cognitive distraction in the automobile.

BACKGROUND

Driver distraction from secondary in-vehicle activities is increasingly recognized as a significant source of injuries and fatalities on the roadway.

METHOD

Across three studies, participants completed eight in-vehicle tasks commonly performed by the driver of an automobile. Primary, secondary, subjective, and physiological measures were collected and integrated into a cognitive distraction scale.

RESULTS

In-vehicle activities, such as listening to the radio or an audio book, were associated with a low level of cognitive workload; the conversation activities of talking to a passenger in the vehicle or conversing with a friend on a handheld or hands-free cell phone were associated with a moderate level of cognitive workload; and using a speech-to-text interfaced e-mail system involved a high level of cognitive workload.

CONCLUSION

The research established that there are significant impairments to driving that stem from the diversion of attention from the task of operating a motor vehicle and that the impairments to driving are directly related to the cognitive workload of these in-vehicle activities. Moreover, the adoption of voice-based systems in the vehicle may have unintended consequences that adversely affect traffic safety.

APPLICATION

These findings can be used to help inform scientifically based policies on driver distraction, particularly as they relate to cognitive distraction stemming from the diversion of attention to other concurrent activities in the vehicle.

The effects of social interactions with in-vehicle agents on a driver's anger level, driving performance, situation awareness, and perceived workload

Research has suggested that interaction with an in-vehicle software agent can improve a driver's psychological state and increase road safety. The present study explored the possibility of using an in-vehicle software agent to mitigate effects of driver anger on driving behavior. After either anger or neutral mood induction, 60 undergraduates drove in a simulator with two types of agent intervention. Results showed that both speech-based agents not only enhance driver situation awareness and driving performance, but also reduce their anger level and perceived workload. Regression models show that a driver's anger influences driving performance measures, mediated by situation awareness. The practical implications include design guidelines for the design of social interaction with in-vehicle software agents.

Is the Technology in Your Car Driving You to Distraction?

Driver distraction is increasingly recognized as a significant source of injuries and fatalities on the roadway. Distraction can arise from visual/manual interference, for example, when a driver takes his or her eyes off the road to interact with a device. Impairments also come from cognitive sources of distraction when attention is withdrawn from the processing of information necessary for the safe operation of a motor vehicle. In the latter case, the driver’s eyes may be on the roadway and his or her hands on the steering wheel, but he or she may not be attending to the information critical for safe driving. Concern over distracted driving is growing as more and more wireless devices are being integrated into the vehicle. We developed and validated a metric of distraction associated with the diversion of attention from driving. Our studies show that the distraction potential can be reliably measured, that cognitive workload systematically varies as a function of the secondary task performed by the driver, and that some activities, particularly newer voice-based interactions in the vehicle, are associated with surprisingly high levels of mental workload. Changing the culture of distracted driving will require a combination of scientifically based education concerning the hazards of inattention, regulations that target the root causes of distraction, and enforcement of the distracted driving laws.

Sharing the responsibility for driver distraction across road transport systems: a systems approach to the management of distracted driving

Distracted driving is acknowledged universally as a large and growing road safety problem. Compounding the problem is that distracted driving is a complex, multifaceted issue influenced by a multitude of factors, organisations and individuals. As such, management of the problem is not straightforward. Numerous countermeasures have been developed and implemented across the globe. The vast majority of these measures have derived from the traditional reductionist, driver-centric approach to distraction and have failed to fully reflect the complex mix of actors and components that give rise to drivers becoming distracted. An alternative approach that is gaining momentum in road safety is the systems approach, which considers all components of the system and their interactions as an integrated whole. In this paper, we review the current knowledge base on driver distraction and argue that the systems approach is not currently being realised in practice. Adopting a more holistic, systems approach to distracted driving will not only improve existing knowledge and interventions from the traditional approach, but will enhance our understanding and management of distraction by considering the complex relationships and interactions of the multiple actors and the myriad sources, enablers and interventions that make up the distracted driving system. It is only by recognising and understanding how all of the system components work together to enable distraction to occur, that we can start to work on solutions to help mitigate the occurrence and consequences of distracted driving.

Texting while driving: is speech-based text entry less risky than handheld text entry?

Research indicates that using a cell phone to talk or text while maneuvering a vehicle impairs driving performance. However, few published studies directly compare the distracting effects of texting using a hands-free (i.e., speech-based interface) versus handheld cell phone, which is an important issue for legislation, automotive interface design and driving safety training. This study compared the effect of speech-based versus handheld text entries on simulated driving performance by asking participants to perform a car following task while controlling the duration of a secondary text-entry task. Results showed that both speech-based and handheld text entries impaired driving performance relative to the drive-only condition by causing more variation in speed and lane position. Handheld text entry also increased the brake response time and increased variation in headway distance. Text entry using a speech-based cell phone was less detrimental to driving performance than handheld text entry. Nevertheless, the speech-based text entry task still significantly impaired driving compared to the drive-only condition. These results suggest that speech-based text entry disrupts driving, but reduces the level of performance interference compared to text entry with a handheld device. In addition, the difference in the distraction effect caused by speech-based and handheld text entry is not simply due to the difference in task duration.

Automation and Inattentional Blindness in a Simulated Flight Task

The study reported herein is a subset of a larger investigation on the role of automation in the context of single pilot aviation operations. This portion of the study focused on the relationship between automation and inattentional blindness (IB) occurrences for a runway incursion. The runway incursion critical stimulus was directly relevant to primary task performance. Participants performed the final five minutes of a landing scenario in one of three automation conditions (autopilot, autothrottle, and manual). Sixty non-pilot participants completed this study and 70% (42 of 60) failed to detect the runway incursion critical stimulus. Participants in the partial automation condition were significantly more likely to detect the runway incursion when compared to those in the full automation condition. The odds of participant detection in the full automation condition did not significantly vary from the manual condition. Participants that detected the runway incursion did not have significantly higher scores on any component of the NASA-TLX compared to those who failed to detect. The relationship demonstrated between automation condition and IB occurrence indicates the role of automation in operational attention detriment.

How does a lower predictability of lane changes affect performance in the Lane Change Task?

The Lane Change Task (LCT) is an established method to assess driver distraction caused by secondary tasks. In the LCT ISO standard, "course following and maneuvering" and "event detection" are mentioned as central task properties. Especially event detection seems to be a reasonable feature, as research suggests that distraction has profound effects on drivers' reactions to sudden, unexpected events. However, closer inspection of the LCT reveals that the events to be detected (lane change signs) and the required response are highly predictable. To investigate how the LCT's distraction assessment of secondary tasks might change if lane change events and responses were less predictable, we implemented three different versions of the LCT - an "original" one, a second one with lowered predictability of event position, and a third one with lowered predictability of event position and response. We tested each of these implementations with the same set of visual and cognitive secondary tasks of varying demand. The results showed that a decrease in predictability resulted in overall degraded performance in the LCT when using the basic lane change model for analysis. However, all secondary task conditions suffered equally. No differential effects were found. We conclude that although an ISO conforming implementation of the LCT might not be excessively valid regarding its depiction of safety relevant events, the results obtained are nevertheless comparable to what would be found in settings of higher validity.