BEAM: The Modeling Framework for Behavior, Energy, Autonomy & Mobility

TL;DR

BEAM is an open-source agent-based transportation modeling framework that simulates individual travel behaviors and interactions within urban systems, providing detailed insights for policy analysis and planning.

Contribution

It introduces a novel, high-resolution, agent-based modeling framework that captures complex transportation dynamics without relying on traditional demand models.

Findings

Successfully applied to New York City case study

Demonstrates detailed simulation of individual travel behaviors

Provides insights into congestion, mode share, and emissions

Abstract

This report outlines the concepts, mechanisms and inner dynamics of the BEAM (Behavior, Energy, Autonomy, and Mobility) modeling framework. BEAM is an open-source large-scale high-resolution transportation model that harnesses the principles of the actor model of computation to build a powerful and efficient agent-based model of travel behavior. It allows a detailed microscopic view of how people make travel choices and interact with the transportation system, enabling more accurate simulations of human mobility and urban transport networks. It also allows the analysis of numerous spatially defined but interacting layers, and integrates them into a cohesive representation of a regional transportation system. This integrated picture provides invaluable insights to policy makers and other stakeholders about how changes to the transportation system result in changes to traffic congestion, mode share, energy use, and emissions throughout a modeled region. These capabilities are demonstrated with a case study of New York City that showcase BEAM's application in a very large and intricate urban transportation system, without relying on existing travel demand models. The unique ability of BEAM to simulate individual behaviors, integrate with other models, and adapt to different real-world scenarios underscores its importance in the rapidly evolving field of transportation and emphasizes its potential as a valuable proof-of-concept tool to contribute to more informed and effective policy and planning decisions.