activity
20172023
most citedMIT Advanced Vehicle Technology Study: Large-Scale Naturalistic Driving Study of Driver Behavior and Interaction with Automation

239 citations · 300 across the 5 of their papers we have counts for

collaborators

7 papers

cs.HC2023★ 15 cited

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…

cs.HC2019

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…

cs.HC2019

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…

cs.HC2019★ 3 cited

Hacking Nonverbal Communication Between Pedestrians and Vehicles in Virtual Reality

Henri Schmidt, Jack Terwilliger, Dina AlAdawy +1

We use an immersive virtual reality environment to explore the intricate social cues that underlie non-verbal communication involved in a pedestrian's crossing decision. We "hack"…

cs.CV2019★ 5 cited

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…

cs.NE2018★ 38 cited

DeepTraffic: Crowdsourced Hyperparameter Tuning of Deep Reinforcement Learning Systems for Multi-Agent Dense Traffic Navigation

Lex Fridman, Jack Terwilliger, Benedikt Jenik

We present a traffic simulation named DeepTraffic where the planning systems for a subset of the vehicles are handled by a neural network as part of a model-free, off-policy reinfo…