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

TL;DR

This paper introduces a comprehensive, human-centered multi-agent transportation simulation platform that supports real-time interaction, multimodal data collection, and accessibility, aiming to improve urban mobility research and planning.

Contribution

It presents a novel, modular, and accessible simulation platform with open-source scripts, integrating immersive virtual environments and multimodal sensing for diverse road users.

Findings

Demonstrated three use cases validating system usability.

Enabled interaction among various transportation modes.

Collected multimodal physiological and behavioral data.

Abstract

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, overlook public transit users as active participants, and are rarely designed with accessibility in mind for non-technical users. To address this gap, this paper presents the specifications of a multi-agent simulation platform designed to support real-time, human-centered, and immersive studies of all road users, accompanied by open-source 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, a seating arrangement, a smart trainer, and an actuated cockpit. Additionally, the platform collects multimodal physiological, neurological, and behavioral data through embedded sensing devices such as functional near-infrared spectroscopy (fNIRS), eye tracking, and wrist-based biosensors. To show the usability of this system, we present three use cases. Simulation for All aims to lower the barrier to entry for high-fidelity transportation simulation, support experimentation across disciplines, and advance our understanding of multimodal mobility in complex urban environments.