- Bruce Mehler is a Research Scientist in the MIT AgeLab and N.E. Univ. Transportation Center, and former Director of A... moreBruce Mehler is a Research Scientist in the MIT AgeLab and N.E. Univ. Transportation Center, and former Director of Applications & Development at NeuroDyne Medical Corporation. He has an extensive background in the development and application of non-invasive physiological monitoring technologies and interests in workload assessment, individual differences in response to cognitive demand and stress, and in how individuals adapt to new technologies. He continues an interest in behavioral medicine.edit
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The next generation of automotive human machine interface (HMI) systems is expected to be heavily dependent upon artificial intelligence; from autonomous driving to speech assistance, from gesture & touch-enabled interfaces to web &... more
The next generation of automotive human machine interface (HMI) systems is expected to be heavily dependent upon artificial intelligence; from autonomous driving to speech assistance, from gesture & touch-enabled interfaces to web & mobile integration. Smooth, safe, and user-friendly interaction between the driver and the vehicle is a key to winning market share. This panel aims to discuss challenges and opportunities for the next generation of automotive HMI from the perspective of human factors and user behavior. Panelists from industry and academia will offer their unique perspectives on the concerns and opportunities in developing future in-vehicle HMIs.
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This eBook is a collection of articles from a Frontiers Research Topic. Frontiers Research Topics are very popular trademarks of the Frontiers Journals Series: they are collections of at least ten articles, all centered on a particular... more
This eBook is a collection of articles from a Frontiers Research Topic. Frontiers Research Topics are very popular trademarks of the Frontiers Journals Series: they are collections of at least ten articles, all centered on a particular subject. With their unique mix of varied contributions from Original Research to Review Articles, Frontiers Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area! Find out more on how to host your own Frontiers Research Topic or contribute to one as an author by contacting the Frontiers Editorial Office: frontiersin.org/about/contac
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As speech technology becomes a significant modality in the vehicle environment, it is essential to develop and assess mechanisms that can reduce driver distraction. Although speech-based interfaces are natural candidates for hands-busy,... more
As speech technology becomes a significant modality in the vehicle environment, it is essential to develop and assess mechanisms that can reduce driver distraction. Although speech-based interfaces are natural candidates for hands-busy, eyes-busy environments such as the vehicle, they also present a potential safety hazard. Since language is inherently a cognitive process, the more attention that is required by the speech interface, the less that is available for the task of driving. Due to inevitability of vehicle-based speech interfaces, the question becomes how to design and modulate the human-computer communication flow so as to minimize the extra cognitive burden on the vehicle occupants. Similar observations can also be applied to pedestrians using smartphone-based applications, where distracted pedestrians pay less attention to where they are going. This project explored both basic and applied aspects of voice based human-machine interface interaction with the goal of providi...
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Non-intrusive, real-time analysis of the dynamics of the eye region allows us to monitor humans’ visual attention allocation and estimate their mental state during the performance of real-world tasks, which can potentially benefit a wide... more
Non-intrusive, real-time analysis of the dynamics of the eye region allows us to monitor humans’ visual attention allocation and estimate their mental state during the performance of real-world tasks, which can potentially benefit a wide range of human-computer interaction (HCI) applications. While commercial eye-tracking devices have been frequently employed, the difficulty of customizing these devices places unnecessary constraints on the exploration of more efficient, end-to-end models of eye dynamics. In this work, we propose CLERA, a unified model for Cognitive Load and Eye Region Analysis, which achieves precise keypoint detection and spatiotemporal tracking in a joint-learning framework. Our method demonstrates significant efficiency and outperforms prior work on tasks including cognitive load estimation, eye landmark detection, and blink estimation. We also introduce a large-scale dataset of 30 k human faces with joint pupil, eye-openness, and landmark annotation, which aims...
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Background: The literature documents that intellectually capable autism spectrum disorder (ASD) is frequently associated with driving avoidance. Because ASD is associated with high levels of comorbid anxiety and our previous work... more
Background: The literature documents that intellectually capable autism spectrum disorder (ASD) is frequently associated with driving avoidance. Because ASD is associated with high levels of comorbid anxiety and our previous work suggested heightened anxiety during driving simulation, we evaluated whether driving behavior assessed through a driving simulator would improve with antianxiety medication. Objective: This was an open label, proof of concept study testing the usefulness and tolerability of the nonsedating, short acting anti-anxiety medication buspirone, using a randomly assigned crossover design. Methods: The sample consisted of 24 adult drivers (5 female) with DSM-V ASD (mean age 28.4 years) who completed two simulated driving sessions, one while taking the anti-anxiety medication buspirone and one without it. Results: Treatment with buspirone was associated with significantly improved driving performance as measured by less variability in lane positioning, a proxy for sa...
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Previous research indicates that drivers may forgo their supervisory role with partial-automation. We investigated if this behavior change is the result of the time automation was active. Naturalistic data was collected from 16 Tesla... more
Previous research indicates that drivers may forgo their supervisory role with partial-automation. We investigated if this behavior change is the result of the time automation was active. Naturalistic data was collected from 16 Tesla owners driving under free-flow highway conditions. We coded glance location and steering-wheel control level around Tesla Autopilot (AP) engagements, driver-initiated AP disengagements, and AP steady-state use in-between engagement and disengagement. Results indicated that immediately after AP engagement, glances downwards and to the center-stack increased above 18% and there was a 32% increase in the proportion of hands-free driving. The decrease in driver engagement in driving was not gradual over-time but occurred immediately after engaging AP. These behaviors were maintained throughout the drive with AP until drivers approached AP disengagement. In conclusion, drivers may not be using AP as recommended (intentionally or not), reinforcing the call fo...
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BACKGROUND The emergence of partial-automation in consumer vehicles is reshaping the driving task, the driver role, and subsequent driver behavior. When using partial-automation, drivers delegate the operational control of the dynamic... more
BACKGROUND The emergence of partial-automation in consumer vehicles is reshaping the driving task, the driver role, and subsequent driver behavior. When using partial-automation, drivers delegate the operational control of the dynamic driving task to the automation system, while remaining responsible for monitoring, object/event detection, response selection, and execution. Hence, driving has become a collaboration between driver and automation systems that is characterized by dynamic Transfers of Control (TOC). OBJECTIVE This study aimed to assess how drivers leverage automation in real-world driving, identify driver and system-initiated TOCs, and provide a taxonomy to capture the underlying driver behaviors associated with automation disengagement. METHODS Fourteen participants drove instrumented Cadillac CT6 vehicles for one-month each, yielding 1690 trips (22,108 miles), with a total of 5343 TOCs between manual driving, SAE Level 1 Adaptive Cruise Control (ACC), and SAE Level 2 Super Cruise (SC). RESULTS The use of automation on limited access highways was prevalent (40 % of the miles driven were with SC and 10 % with ACC) yet not continuous. Drivers frequently initiated transitions between automation levels (mean = 9.98, SD = 8.32, transitions per trip), temporarily taking over the longitudinal and/or lateral vehicle control. These transitions were not necessarily related to immediate risk mitigation, but rather to the execution of functions beyond the automation system's capabilities or representing preferences in task execution. Driver-initiated TOCs from SC to manual driving followed the structure and temporal aspects of the hierarchical model of driver behavior. Strategic, Maneuver, and Control TOCs were associated with significantly different patterns of vehicle kinematics, automation disengagement modality, and TOC duration. System-initiated automation disengagements from SC to manual driving were rare (1%). CONCLUSIONS Generalizing from objective, real-world driving data, this study provides an ecologically valid taxonomy for transfer of control building upon the hierarchical model of driver behavior. We show that driver-automation interactions can occur in each level of the hierarchical model and that TOCs are part of the driver's strategic, maneuver, and control levels of decision making. Thus, TOCs are not isolated or rare events, but rather an integral part of an ongoing, continuous and dynamic collaboration. This taxonomy contextualizes TOCs, paving the way for greater understanding of when and why drivers will takeover control, exposes the underlying motivations for TOCs, and characterizes how these are reflected in the driver's actions. The findings can inform the development of driver-centered automation systems as well as policies and guidelines for current and future automation levels.
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The chapter aims at analyzing the impact of wrist-wearable electrodermal potential (EDP) devices on measuring levels of alertness previously assessed using electroencephalography (EEG). EDP is expected to prove less time-consuming and... more
The chapter aims at analyzing the impact of wrist-wearable electrodermal potential (EDP) devices on measuring levels of alertness previously assessed using electroencephalography (EEG). EDP is expected to prove less time-consuming and less complicated to set up. A gender-balanced and age-diverse sample of experienced drivers drove on-road while connected to the EDP wearable and results were recorded.
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In this study we compare glance patterns observed in field experiment driving studies with glance patterns observed in the naturalistic SHRP 2 NEST database. We describe the methodology used to identify appropriate naturalistic epochs and... more
In this study we compare glance patterns observed in field experiment driving studies with glance patterns observed in the naturalistic SHRP 2 NEST database. We describe the methodology used to identify appropriate naturalistic epochs and to prepare glances for comparison to field experiment data, and graphically show points of similarity and points of contrast between the two sets of data. Overall, glance patterns observed in field experiments appear to hold in naturalistic data, with a few caveats. Using naturalistic glance data to validate experimentally-acquired glance data appears to show promise and provides confidence for conclusions drawn from behaviors observed in controlled on-road driving scenarios.
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Driving simulator validation is an important and ongoing process. Advances in in-vehicle human machine interfaces (HMI) mean there is a continuing need to reevaluate the validity of use cases of driving simulators relative to real world... more
Driving simulator validation is an important and ongoing process. Advances in in-vehicle human machine interfaces (HMI) mean there is a continuing need to reevaluate the validity of use cases of driving simulators relative to real world driving. Along with this, our tools for evaluating driver demand are evolving, and these approaches and measures must also be considered in evaluating the validity of a driving simulator for particular purposes. We compare driver glance behavior during HMI interactions with a production level multi-modal infotainment system on-road and in a driving simulator. In glance behavior analysis using traditional glance metrics, as well as a contemporary modified AttenD measure, we see evidence for strong relative validity and instances of absolute validity of the simulator compared to on-road driving.
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To investigate possible relationships between drivers’ sensation seeking and glance behavior while interacting with human-machine interfaces, a total of 70 drivers’ eye-glance data, Sensation Seeking Scale (SSS), and Driver Behavior... more
To investigate possible relationships between drivers’ sensation seeking and glance behavior while interacting with human-machine interfaces, a total of 70 drivers’ eye-glance data, Sensation Seeking Scale (SSS), and Driver Behavior Questionnaire (DBQ) data were collected and analyzed. Participants conducted radio tuning tasks with two standard production interfaces while driving on a highway, and their glance allocations to defined regions were recorded and manually annotated. Results showed that sensation seeking scores were related with self-reported violation scores, off-road glance patterns, and driving speed: (1) violation scores of DBQ were positively correlated with sensation seeking, (2) mean and standard deviation of off-road glance duration were positively correlated with sensation seeking for younger drivers (under 40 years), (3) total off-road glance time per minute and number of off-road glances per minute were positively correlated with sensation seeking for older dri...
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Associations between user characteristics and system features to technology adoption have been discussed in various domains. However, less is known about how different factors potentially affect the adoption of in-vehicle smart... more
Associations between user characteristics and system features to technology adoption have been discussed in various domains. However, less is known about how different factors potentially affect the adoption of in-vehicle smart technologies. This study builds and tests a research model that describes the relationships of individual characteristics, preconceptions, and task performance and perceptions measured during a system experience to attitudes and expectations toward in-vehicle technologies. Based on empirical data from three research cases—voice-control interface, active parallel parking assist, and cross traffic alert—this study finds perceptions of a hands-on system experience to have strong associations with postexperience attitudes and expectations. Individual characteristics including age and health, general preconceptions, and task performance were found to have weaker relationships. Based on the findings, this article discusses implications for research in the emerging domain of smart technologies in automobiles, as well as for practice in design and delivery of in-vehicle technologies.
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As the characteristics of in-vehicle human-machine interfaces (HMIs), the driving task, and the expectations and behavior of drivers have evolved, so too should our thinking and approach to HMI design and evaluation. This panel will... more
As the characteristics of in-vehicle human-machine interfaces (HMIs), the driving task, and the expectations and behavior of drivers have evolved, so too should our thinking and approach to HMI design and evaluation. This panel will present background and perspectives on the current status, emerging needs, challenges, and opportunities in this area. A key focus for the panel is an emphasis on attention support. Detailed contextual description is provided below for reference to allow panelists to keep their opening remarks relatively brief to allow for substantive question and discussion time with the audience.
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Speeding is a prevalent and risky behavior. This study leveraged the MIT Advanced Vehicle Technology naturalistic driving data to identify and characterize speeding behavior across automation levels including Manual Driving, Adaptive... more
Speeding is a prevalent and risky behavior. This study leveraged the MIT Advanced Vehicle Technology naturalistic driving data to identify and characterize speeding behavior across automation levels including Manual Driving, Adaptive Cruise Control (ACC), and Pilot Assist (PA) that supports both longitudinal and lateral vehicle control. We analyzed 146 hours of motorway driving from 15 participants who each drove an instrumented vehicle for one month. Speeding prevalence, magnitude, and duration distributions were compared across automation levels using logistic mixed effect models. Findings indicated that although PA was the most prevalent driving state during free flow motorway driving, drivers were more likely to speed with ACC compared to during Manual Driving or with PA. Automation, ACC and PA, were associated with longer speeding durations and lower speeding magnitudes compared to driving manually. These findings can inform the development of automation systems that may help r...
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A field operational test assessed visual-manual disengagement when driving with adaptive cruise control (ACC) relative to manual driving. Ten volunteers drove instrumented vehicles on public roads for 4 weeks, using the vehicles as they... more
A field operational test assessed visual-manual disengagement when driving with adaptive cruise control (ACC) relative to manual driving. Ten volunteers drove instrumented vehicles on public roads for 4 weeks, using the vehicles as they would their own. To study change over time, the 4-week trial was divided evenly into two periods. Analyses were based on video of drives on limited-access highways when speed was above 25 mph. Visual-manual disengagement from driving was defined as periods when drivers had both hands off the steering wheel or performed visual-manual secondary activity with electronics. Odds of visual-manual disengagement increased from period 1 (weeks 1 and 2) to period 2 (weeks 3 and 4) more during ACC use than during manual driving. Conversely, odds of cellphone manipulation and hands-offwheel behavior increased in period 2 during manual driving only, suggesting a nuanced connection between behavioral adaptation to ACC use after a month of exposure.
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Tesla auto lane change is a feature within Autopilot (AP) – a collection of automated driving features designed to assist the driver with automatic steering and adaptive cruise control. In order to determine how drivers engage in... more
Tesla auto lane change is a feature within Autopilot (AP) – a collection of automated driving features designed to assist the driver with automatic steering and adaptive cruise control. In order to determine how drivers engage in maneuvers performed automatically by AP, 5,154 manual and automated lane change events along with video, system data, and vehicle kinematics were extracted from over 691 hours of naturalistic driving from 19 different drivers. Findings indicate that drivers performed manual lane changes more frequently than auto lane changes despite the use of Autopilot being more prevalent than manual driving on motorways. Auto lane changes occurred at higher speed and were associated with fewer acceleration and braking events and narrower distributions of kinematic characteristics. The lower frequency and kinematic variability in auto lane changes may suggest that drivers use this feature in a limited set of circumstances.
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Forward collision warning (FCW) systems typically employ forward sensing technologies to identify possible forward collisions and provide an alert to the driver in the event they have not recognized a threat. These systems have... more
Forward collision warning (FCW) systems typically employ forward sensing technologies to identify possible forward collisions and provide an alert to the driver in the event they have not recognized a threat. These systems have demonstrated safety benefits. However, because the base rate of collisions is low, sensitive FCW systems can provide a high rate of alarms in situations with no or low probability of collision, which may negatively impact driver responsiveness and satisfaction. We examined over 2000 naturally occurring FCWs in two modern vehicles as a part of a naturalistic driving study investigation into advanced vehicle technologies. Analysts used cabin and forward camera footage, as well as environmental characteristics, to judge the likelihood of a crash during each alert, which were used to model the likelihood of an alert representing a possible collision. Only nine FCWs were considered “crash possible and imminent”. Road-type, speed, traffic density, and deceleration ...
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Research Interests: Psychology and Automation
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Abstract Objective Adaptive cruise control (ACC) and lane centering are usually marketed as convenience features but may also serve a safety purpose. However, given that speeding is associated with increased crash risk and worse crash... more
Abstract Objective Adaptive cruise control (ACC) and lane centering are usually marketed as convenience features but may also serve a safety purpose. However, given that speeding is associated with increased crash risk and worse crash outcomes, the extent to which driver’s speed using ACC may reduce the maximum safety benefit they can obtain from this system. The current study was conducted to characterize speeding behavior among drivers using adaptive cruise control and a similar system with added lane centering. Methods We recruited 40 licensed adult drivers from the Boston, Massachusetts, metro area. These drivers were given either a 2017 Volvo S90 or a 2016 Range Rover Evoque to use for about 4 weeks. Results Drivers were significantly more likely to speed while they used ACC (95%) relative to periods of manual control (77%). A similar pattern arose for drivers using ACC with added lane centering (96% vs. 77%). Drivers who traveled over the posted limit with these systems engaged also sped slightly faster than drivers controlling their vehicle manually. Finally, we found that these differences were the most pronounced on limited-access roads with a lower speed limit (55 mph). Conclusions These findings point to a possible obstacle to obtaining the full safety potential from this advanced vehicle technology. Any consideration of the net safety effect of ACC and lane centering should account for the effects of more frequent and elevated speeding.
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Traffic safety has been traditionally addressed through individual improvements to the car by manufacturers; improvements to the driver through education and enforcement; and, improvements to the infrastructure by government. While none... more
Traffic safety has been traditionally addressed through individual improvements to the car by manufacturers; improvements to the driver through education and enforcement; and, improvements to the infrastructure by government. While none of these approaches is incorrect, they are incomplete. The authors believe that further opportunities for enhancing safety are to be found in creatively exploiting the overlapping and interactive nature of the role of the vehicle, driver, and driving environment in accident prevention and mitigation. The authors apply wellness, as developed in the fields of health behavior and sports psychology, as an integrating framework to envision driver performance as dynamic and improvable. From this perspective, and building on advances in ambient intelligence, they propose the development of an AwareCar. The AwareCar concept would detect driver state (fatigue or stress); display that information to the driver to improve the driver’s situational awareness in r...
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Researchers, technology reviewers, and governmental agencies have expressed concern that automation may necessitate the introduction of added displays to indicate vehicle intent in vehicle-to-pedestrian interactions. An automated online... more
Researchers, technology reviewers, and governmental agencies have expressed concern that automation may necessitate the introduction of added displays to indicate vehicle intent in vehicle-to-pedestrian interactions. An automated online methodology for obtaining communication intent perceptions for 30 external vehicle-to-pedestrian display concepts was implemented and tested using Amazon Mechanic Turk. Data from 200 qualified participants was quickly obtained and processed. In addition to producing a useful early-stage evaluation of these specific design concepts, the test demonstrated that the methodology is scalable so that a large number of design elements or minor variations can be assessed through a series of runs even on much larger samples in a matter of hours. Using this approach, designers should be able to refine concepts both more quickly and in more depth than available development resources typically allow. Some concerns and questions about common assumptions related to...
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This paper describes a set of data made available that contains detailed subtask coding of interactions with several production vehicle human machine interfaces (HMIs) on open roadways, along with accompanying eyeglance data.
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Research Interests: Business and Automation
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Human visual perception forms different levels of abstractions expressing the essential semantic components in the scene at different scales. For real-world applications such as driving scene perception, abstractions of both coarse-level,... more
Human visual perception forms different levels of abstractions expressing the essential semantic components in the scene at different scales. For real-world applications such as driving scene perception, abstractions of both coarse-level, such as the spatial presence of the lead vehicle, and the fine-level, such as the words on a traffic sign, serve as important signals for driver's decision making. However, the granularities of perception required for levels of abstractions are generally different. While current computer vision research makes significant progress in tasks of understanding the global scene (image classification), and dense scene (semantic segmentation), our work takes steps to explore the gap in between. In this paper, we propose Multi-class Probability Pyramid as a representation built on the top of pixel-level semantic scene labels. This representation forms region-level abstractions by controlling the granularity of local semantic information, and thus disentangles the variation of scene semantics at different resolutions. We further show how such representation can be effectively used for evaluation purposes, including interpretable evaluation of scene segmentation and unsupervised diagnosis of segmentation predictions.
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Behavioral techniques centered on pelvic floor muscle exercises are recognized as low-risk interventions that decrease the frequency of urinary incontinence in most individuals and are also utilized in treating other pelvic floor... more
Behavioral techniques centered on pelvic floor muscle exercises are recognized as low-risk interventions that decrease the frequency of urinary incontinence in most individuals and are also utilized in treating other pelvic floor disorders.“Kegel” exercises, developed by Arnold Kegel, were intended to employ instrumental feedback to assist patients in learning how to do pelvic floor exercises properly. The development of vaginal and rectal EMG sensors and multi-channel instrumentation support objective quantification and aid in easy-to-understand discrimination training. The present chapter focuses on the role that biofeedback techniques, and surface electromyography (sEMG) in particular, can play in pelvic floor muscle training.
• Surface electromyography (sEMG) is a painless and noninvasive method of monitoring muscle activity and resting tonus that can be used both in assessment and training applications. • Biofeedback techniques may be applied both for general... more
• Surface electromyography (sEMG) is a painless and noninvasive method of monitoring muscle activity and resting tonus that can be used both in assessment and training applications. • Biofeedback techniques may be applied both for general relaxation training and in retraining of functional patterns of muscle activation. • An understanding of the basic principles of sEMG technique can significantly enhance recording quality and utility.