Simulation for All: A Step-by-Step Cookbook for Developing Human-Centered Multi-Agent Transportation Simulators

As cities evolve toward more complex and multimodal transportation systems, the need for human-centered multi-agent simulation tools has never been more urgent. Yet most existing platforms remain limited—they often separate different types of road users, rely on scripted or pre-defined behaviors, largely overlook public transit users as active, embodied participants, and are rarely designed with accessibility in mind for non-technical users. To address this gap, the following paper presents the detailed specifications of a multi-agent simulation platform designed to support real-time, human-centered, and immersive studies of all road users, accompanied by open-sourced scripts for replication. Using high fidelity immersive virtual environments, our platform enables interaction across public transit users, pedestrians, cyclists, automated vehicles, and drivers. The architecture is modular, extensible, and designed for accessibility. The system integrates hardware-specific modules—including an omnidirectional treadmill for pedestrians, a seating arrangement for public transit users, a smart trainer for cyclists, and an actuated cockpit for drivers. Additionally, the platform simultaneously collects multimodal physiological, neurological, and behavioral data through embedded sensing devices such as functional near-infrared spectroscopy (fNIRS) for brain activity, eye tracking, and wrist-based biosensors. To show the usability of this system, we present three use cases across various areas of road user research. Simulation for All aims to pave the way for lowering the barrier to entry for high-fidelity transportation simulation, support experimentation across disciplines, and advance our understanding of multimodal mobility in increasingly complex urban environments. The codebase for the platform is available at [10], enabling replication and adaptation for transportation research applications.