Work

TravelAgent: Generative agents in the built environment

Year: 2025

Type: article

Abstract: Understanding human behavior in the built environment is critical for designing highly-functional, human-centered urban spaces. Traditional approaches, such as manual observations, surveys, and simple simulations, often struggle to capture the complexity and nuance of real-world human behavior and experience. Here we introduce TravelAgent, a novel agentic simulation platform that models pedestrian navigation, activity, and human-like decision-making in the built environment. TravelAgent is proposed to help design teams and decision-makers understand how different users might experience diverse built environments under varying environmental conditions. TravelAgent integrates Generative Agents, multi-modal sensory inputs, and virtual environments, enabling agents to perceive, navigate, and interact with their surroundings, with tasks ranging from goal-oriented navigation to free exploration. We share analysis from 200 simulations with 3364 decision points and task completion rate of ∼80%, across diverse spatial layouts and agent archetypes. We present spatial, linguistic, and sentiment analysis, and show how agents react and experience their surroundings. Finally, we suggest TravelAgent as a new paradigm for designing, simulating, and understanding human experiences in urban environments.

Source: Environment and Planning B Urban Analytics and City Science

DOI: 10.1177/23998083251360458

Authors: Ariel Noyman, Kai Hu, Kent Larson

Institutions: MIT Media Lab, Massachusetts Institute of Technology, South China University of Technology

Language: English

Topic: Evacuation and Crowd Dynamics

Subfield: Ocean Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Sustainable cities and communities

Open Access status: hybrid

Estimated APC paid: $3,650