Publications (19)
Value of Temporal Dynamics Information in Driving Scene Segmentation
Li Ding, Jack Terwilliger, Rini Sherony +2
Semantic scene segmentation has primarily been addressed by forming representations of single images both with supervised and unsupervised methods. The problem of semantic segmenta…
Dynamics of Pedestrian Crossing Decisions Based on Vehicle Trajectories in Large-Scale Simulated and Real-World Data
Jack Terwilliger, Michael Glazer, Henri Schmidt +5
Humans, as both pedestrians and drivers, generally skillfully navigate traffic intersections. Despite the uncertainty, danger, and the non-verbal nature of communication commonly f…
Designing Toward Minimalism in Vehicle HMI
Julia Kindelsberger, Lex Fridman, Michael Glazer +1
We propose that safe, beautiful, fulfilling vehicle HMI design must start from a rigorous consideration of minimalist design. Modern vehicles are changing from mechanical machines…
The Context of Crash Occurrence: A Complexity-Infused Approach Integrating Semantic, Contextual, and Kinematic Features
Meng Wang, Zach Noonan, Pnina Gershon +3
Understanding the context of crash occurrence in complex driving environments is essential for improving traffic safety and advancing automated driving. Previous studies have used…
To Walk or Not to Walk: Crowdsourced Assessment of External Vehicle-to-Pedestrian Displays
Lex Fridman, Bruce Mehler, Lei Xia +3
Researchers, technology reviewers, and governmental agencies have expressed concern that automation may necessitate the introduction of added displays to indicate vehicle intent in…
SideEye: A Generative Neural Network Based Simulator of Human Peripheral Vision
Lex Fridman, Benedikt Jenik, Shaiyan Keshvari +3
Foveal vision makes up less than 1% of the visual field. The other 99% is peripheral vision. Precisely what human beings see in the periphery is both obvious and mysterious in that…
CLERA: A Unified Model for Joint Cognitive Load and Eye Region Analysis in the Wild
Li Ding, Jack Terwilliger, Aishni Parab +4
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…
Arguing Machines: Human Supervision of Black Box AI Systems That Make Life-Critical Decisions
Lex Fridman, Li Ding, Benedikt Jenik +1
We consider the paradigm of a black box AI system that makes life-critical decisions. We propose an "arguing machines" framework that pairs the primary AI system with a secondary o…
A Description of a Subtask Dataset with Glances
B. D. Sawyer, Sean Seaman, Linda Angell +3
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 road…
Semi-Automated Annotation of Discrete States in Large Video Datasets
Lex Fridman, Bryan Reimer
We propose a framework for semi-automated annotation of video frames where the video is of an object that at any point in time can be labeled as being in one of a finite number of…
Driver Gaze Region Estimation Without Using Eye Movement
Lex Fridman, Philipp Langhans, Joonbum Lee +1
Automated estimation of the allocation of a driver's visual attention may be a critical component of future Advanced Driver Assistance Systems. In theory, vision-based tracking of…
MIT Advanced Vehicle Technology Study: Large-Scale Naturalistic Driving Study of Driver Behavior and Interaction with Automation
Lex Fridman, Daniel E. Brown, Michael Glazer +15
For the foreseeble future, human beings will likely remain an integral part of the driving task, monitoring the AI system as it performs anywhere from just over 0% to just under 10…
Investigating Drivers' Head and Glance Correspondence
Joonbum Lee, Mauricio Muñoz, Lex Fridman +3
The relationship between a driver's glance pattern and corresponding head rotation is highly complex due to its nonlinear dependence on the individual, task, and driving context. T…
Automated Synchronization of Driving Data Using Vibration and Steering Events
Lex Fridman, Daniel E Brown, William Angell +3
We propose a method for automated synchronization of vehicle sensors useful for the study of multi-modal driver behavior and for the design of advanced driver assistance systems. M…
Detecting Road Surface Wetness from Audio: A Deep Learning Approach
Irman AbdiÄ, Lex Fridman, Erik Marchi +4
We introduce a recurrent neural network architecture for automated road surface wetness detection from audio of tire-surface interaction. The robustness of our approach is evaluate…
What Can Be Predicted from Six Seconds of Driver Glances?
Lex Fridman, Heishiro Toyoda, Sean Seaman +5
We consider a large dataset of real-world, on-road driving from a 100-car naturalistic study to explore the predictive power of driver glances and, specifically, to answer the foll…
Eye Contact Between Pedestrians and Drivers
Dina AlAdawy, Michael Glazer, Jack Terwilliger +5
When asked, a majority of people believe that, as pedestrians, they make eye contact with the driver of an approaching vehicle when making their crossing decisions. This work prese…
Owl and Lizard: Patterns of Head Pose and Eye Pose in Driver Gaze Classification
Lex Fridman, Joonbum Lee, Bryan Reimer +1
Accurate, robust, inexpensive gaze tracking in the car can help keep a driver safe by facilitating the more effective study of how to improve (1) vehicle interfaces and (2) the des…
Driver Glance Classification In-the-wild: Towards Generalization Across Domains and Subjects
Sandipan Banerjee, Ajjen Joshi, Jay Turcot +2
Distracted drivers are dangerous drivers. Equipping advanced driver assistance systems (ADAS) with the ability to detect driver distraction can help prevent accidents and improve d…