AWARE Initiative

AWARE turns human understanding into intelligent action.

AWARE translates understanding of human state and environment into intelligent systems that better serve people across transportation, workplaces, homes, and public spaces. As people move through these environments, their attention, workload, physical condition, emotional state, goals, and capabilities constantly shift—yet intelligent systems often fail to recognize these changes. AWARE studies how intelligent systems can better understand human context and better support human decision-making, safety, health, productivity, and quality of life.

Rooted at MIT AgeLab and the MIT Center for Transportation & Logistics, AWARE brings together expertise in artificial intelligence, mobility, health, behavioral science, human factors, and systems engineering. It is a community of researchers, industry partners, government agencies, students, and public-sector organizations working to bridge the gap between intelligent technology and human need.

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Research at Real-World Scale

Miles of naturalistic driving data

Drivers in the naturalistic study

Different vehicle brands in research fleet

K+

Research participant database

The challenge lies in rigid systems, not variable humans

The real differentiator between intelligent driving systems will be technologies that can interpret and respond to human state, behavior, and variability.

Research Themes

The AWARE Initiative focuses on four areas: mobility, home, shared and social places, and work. Mobility examines how vehicles, automation, interfaces, and sensing systems support safer and more meaningful movement. Home investigates how connected environments and ambient intelligence enhance care, health, and well-being in everyday decision-making. Shared & Social Places studies human interaction with intelligent systems across transportation networks, community spaces, and service environments. Work explores how intelligent systems adapt to mixed-generation workforces, changing tasks, and evolving cognitive demands.

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Human state, capability, and readiness

We study how attention, workload, fatigue, impairment, health, emotion, and individual capability affect interaction with technology. The goal is to determine whether a person is prepared to decide and act, needs support, or should not be interrupted.

Human–AI collaboration and shared control

We examine how people and intelligent systems communicate, exchange information, coordinate actions, and share responsibility. This includes adaptive assistance, transitions of control, intervention timing, and maintaining appropriate human understanding and authority.

Trust, adaptation, use, and experience

We investigate how trust, expectations, interaction strategies, and behavior develop through experience and understanding system capabilities and limitations. Longitudinal and experimental studies help explain why people adopt, reject, misuse, or adapt to intelligent technologies.

Context-aware sensing, prediction, and support

We integrate multimodal sensing, behavioral modeling, and information about the person, task, technology, and environment to understand human intent and anticipation of risk, and provide support appropriate to the person’s needs and situation.

Social and multi-agent interaction

We study how drivers, pedestrians, cyclists, and passengers, communicate and coordinate with other people, vehicles, agents, and intelligent systems through movement, gaze, timing, and gesture. This work supports more predictable and understandable interaction in dynamic and complex environments.

Health, safety, and mobility across the lifespan

We examine how intelligent technologies can support performance, safety, independence, and well-being as needs, health conditions, and capabilities change across the lifespan.

Multimodal human state and intent estimation

Intelligent systems are increasingly capable of detecting people, objects, and features of the environment. But detecting a person is different from understanding them. What are they attending to? What are they trying to do? How are they responding to the environment, and what are they likely to do next? AWARE combines behavioral, physiological, vehicle, system, and environmental data with advanced AI methods to model human behavior in context. These models allow intelligent systems to incorporate human state and intent into their decision-making processes, anticipate needs, operate proactively, improve planning, and coordinate smoothly.

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Human interaction and coordination

When using intelligent systems, human behavior is also shaped by other people operating in the same environment and by characteristics of the surrounding environment. Many important interactions rely on subtle combinations of cues like movement, gaze, gesture, and their timing. These cues are challenging for intelligent systems to interpret. Human Interaction and Coordination examines how people communicate, negotiate, and share responsibility with one another and with intelligent systems. AWARE develops behavioral and computational models of interactions involving drivers, pedestrians, passengers, remote operators, and intelligent systems to improve predictability and more natural coordination in complex environments.

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Benchmarking and validation

The rapid growth of human-aware AI has created a need for common methods to compare systems and determine whether they improve outcomes. Existing benchmarks rarely connect technical model performance with meaningful changes in human behavior. AWARE develops datasets, validation protocols, and performance measures for evaluating human-state estimation, predictive models, and adaptive interventions. This work supports developing standards for human-aware intelligent systems.

Human adaptation to intelligent systems

People change how they use intelligent systems as they gain experience. People learn the system’s capabilities, limitations, and safeguard mechanisms, and adjust their behavior in response. AWARE studies how human behavior changes with repeated use of AI and automation. Through longitudinal naturalistic studies and controlled experiments, we examine how people adapt their behavior, expectations, interaction strategies, and attention over time. This research helps design systems that account for how people adapt to technology over time, beyond their initial interactions.

Behavioral design and adaptive intervention

Detecting human state is only one part of the challenge. An equally important question is how an intelligent system should respond once it understands the human and the surrounding context. AWARE develops and evaluates interfaces, adaptive alerts, interventions, and performance during shared control. We study when intervention is needed, how it should be delivered, its effectiveness, and when the best response may be no intervention at all.

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Partner with AWARE

AWARE collaborates with organizations interested in advancing human-aware AI and addressing questions that require both behavioral and technical expertise.

Opportunities may include sponsored research, collaborative studies, workshops, data analysis, and access to specialized research capabilities.

Interested in discussing an idea or research need? Reach out.

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