A5017953936- Human-Automation Interaction and Safety
- Traffic and Road Safety
- Safety Warnings and Signage
- Autonomous Vehicle Technology and Safety
- Automotive and Human Injury Biomechanics
- Older Adults Driving Studies
- Gaze Tracking and Assistive Technology
- Vehicle emissions and performance
- Traffic Prediction and Management Techniques
- Risk and Safety Analysis
- Traffic control and management
- Cognitive Functions and Memory
- Sleep and Work-Related Fatigue
- Healthcare Technology and Patient Monitoring
- Safety Systems Engineering in Autonomy
- Vehicle Dynamics and Control Systems
- Urban Transport and Accessibility
- Quality and Safety in Healthcare
- Occupational Health and Safety Research
- Transportation Planning and Optimization
- EEG and Brain-Computer Interfaces
- Neural and Behavioral Psychology Studies
- Face recognition and analysis
- Transportation and Mobility Innovations
- Advanced Computational Techniques in Science and Engineering
Volvo Cars (Sweden)
2015-2021
Chalmers University of Technology
2008-2021
Volvo (Sweden)
2011-2021
University of Leeds
2020
Uppsala University
2005-2012
Linköping University
2002
Objective: The objective of this paper was to outline an explanatory framework for understanding effects cognitive load on driving performance and review the existing experimental literature in light framework. Background: Although there is general consensus that taking eyes off forward roadway significantly impairs most aspects driving, primarily cognitively loading tasks are not well understood. Method: Based models driver attention, outlined. This can be summarized terms control...
Despite an abundant use of the term "Out loop" (OOTL) in context automated driving and human factors research, there is currently a lack consensus on its precise definition, how it can be measured, practical implications being or out loop during driving. The main objective this paper to consider above issues, with goal achieving shared understanding OOTL concept between academics practitioners. To end, reviews existing definitions outlines set concepts, which, based driver behaviour...
Objective: The aim of this study was to understand how secure driver supervision engagement and conflict intervention performance while using highly reliable (but not perfect) automation. Background: Securing engagement—by mitigating irony automation (i.e., the better automation, less attention drivers will pay traffic system, capable they be resume control) by communicating system limitations avoid mental model misconceptions—is a major challenge in human factors literature. Method: One...
Accurate, robust, inexpensive gaze tracking in the car can help keep a driver safe by facilitating more effective study of how to improve (i) vehicle interfaces and (ii) design future advanced assistance systems. In this study, authors estimate head pose eye from monocular video using methods developed extensively prior work ask two new interesting questions. First, much better they classify versus just pose? Second, are there individual-specific strategies that strongly correlate with...
This article examines the safety performance of Waymo Driver, an SAE level 4 automated driving system (ADS) used in a rider-only (RO) ride-hailing application without human driver, either vehicle or remotely.
Objective The public, regulators, and domain experts alike seek to understand the effect of deployed SAE level 4 automated driving system (ADS) technologies on safety. recent expansion ADS technology deployments is paving way for early stage safety impact evaluations, whereby observational data from both an a representative benchmark fleet are compared quantify performance.
Waymo's mission to reduce traffic injuries and fatalities improve mobility for all has led us expand deployment of automated vehicles on public roads without a human driver behind the wheel. As part this process, Waymo is committed providing with informative relevant data regarding demonstrated safety driving system, which we call Driver. The presented in paper represents more than 6.1 million miles Phoenix, Arizona metropolitan area, including operations trained operator steering wheel from...
Objectives With fully automated driving systems (ADS; SAE level 4) ride-hailing services expanding in the U.S., we are now approaching an inflection point history of vehicle safety assessment. The process retrospectively evaluating ADS impact (as seen with seatbelts, airbags, electronic stability control, etc.) can start to yield statistically credible conclusions. An measurement requires a comparison "benchmark" crash rate. Most benchmarks generated to-date have focused on current...
Driver distraction and driver inattention are frequently recognized as leading causes of crashes incidents. Despite this fact, there few methods available for the automatic detection distraction. Eye tracking has come forward most promising technology, but technique suffers from quality issues when used in field over an extended period time. Eye-tracking data acquired clearly differs what is a laboratory setting or driving simulator, algorithms that have been developed these settings often...
As naturalistic driving data become increasingly available, new analyses are revealing the significance of drivers' glance behavior in traffic crashes. Due to rarity crashes, even largest datasets, near-crashes often included and used as surrogates for However, date we lack a method assess extent which driver influences crash injury risk across both crashes near-crashes. This paper presents novel estimating from off-road alike; this can also be evaluate safety impact secondary tasks (such...
Predictive processing has been proposed as a unifying framework for understanding brain function, suggesting that cognition and behaviour can be fundamentally understood based on the single principle of prediction error minimisation. According to predictive processing, is statistical organ continuously attempts get grip states in world by predicting how these cause sensory input minimising deviations between predicted actual input. While ideas have had strong influence neuroscience cognitive...
This paper introduces a reference model of glance behavior for driving safety assessment. can improve the design automated and assistive systems. Technological limitations have previously hindered use unobtrusive eye trackers to measure in naturalistic conditions. presents comprehensive analysis eye-tracking data collected field operation test, using an tracker that proved be robust real-world scenarios. We describe post-processing technique enhance quality eye-tracker data, propose...
For over a century, researchers have wrestled with how to define good driving behavior, and the debate has surfaced anew for automated vehicles (AVs). We put forth concept of Drivership as framing realization behaviors. grounds evaluation behaviors in alignment between mutualistic expectations that exist amongst road users. Leveraging existing literature, we distinguish Empirical Expectations (i.e., reflecting "beliefs certain behavior will be followed," drawing on past experiences)...