A Digital Smart City for Emerging Mobility Systems (2109.02811v3)

Abstract: The increasing demand for emerging mobility systems with connected and automated vehicles has imposed the necessity for quality testing environments to support their development. In this paper, we introduce a Unity-based virtual simulation environment for emerging mobility systems, called the Information and Decision Science Lab's Scaled Smart Digital City (IDS 3D City), intended to operate alongside its physical peer and its established control framework. By utilizing the Robot Operation System, AirSim, and Unity, we constructed a simulation environment capable of iteratively designing experiments significantly faster than it is possible in a physical testbed. This environment provides an intermediate step to validate the effectiveness of our control algorithms prior to their implementation in the physical testbed. The IDS 3D City also enables us to demonstrate that our control algorithms work independently of the underlying vehicle dynamics, as the vehicle dynamics introduced by AirSim operate at a different scale than our scaled smart city. Finally, we demonstrate the behavior of our digital environment by performing an experiment in both the virtual and physical environments and comparing their outputs.

• The paper presents a high-fidelity digital twin that bridges virtual simulations and physical testing for connected and automated vehicles.
• The paper employs a hybrid simulation architecture using Unity, ROS, and AirSim to accurately mimic real-world vehicle dynamics and control.
• The paper demonstrates reduced testing costs and enhanced safety by validating control algorithms in a scalable, virtual environment before physical deployment.

A Digital Smart City for Emerging Mobility Systems: A Technical Overview

The paper "A Digital Smart City for Emerging Mobility Systems" presents a virtual simulation framework tailored for the development and testing of emerging mobility systems, particularly those involving Connected and Automated Vehicles (CAVs). The framework, known as the Information and Decision Science Lab's Scaled Smart Digital City (IDS 3D City), is implemented using Unity, Robot Operation System (ROS), and Microsoft AirSim. This environment acts as an intermediate step between numerical simulations and physical testing of CAVs, providing a standardized platform for evaluating control algorithms and their performance.

The IDS 3D City is a high-fidelity replica of the physical IDS Scaled Smart City (IDS^3C), allowing for consistent transition between virtual and physical environments. This digital twin not only aids in design and implementation but also reduces costs and enhances the safety of CAV testing by enabling comprehensive pre-physical testing validation. Notably, the Virtual Smart City is capable of scaling vehicle dynamics to match those observed in real-world scenarios.

Key Features and Methodologies

1. Simulation and Control Architecture:
   • The multi-component architecture utilizes a central mainframe computer. Each CAV's positions are fed back into the system through a VICON motion capture system, mirroring a virtual environment communication via ROS nodes.
   • The fully adjustable IDL simulation environment approaches CAV integration through standards of traffic management and control algorithms designed to reflect real-world implications effectively.
2. Integrated Systems:
   • The IDS 3D City uses the coordination of Unity’s game engine, AirSim for dynamics and sensor simulation, and ROS# for communication across the system. AirSim equips vehicles with sensor suites and dynamic models that enable adjustment to vehicle-specific characteristics, including weight and aerodynamic drag.
   • ROS# module in Unity provides a seamless interface for communication that mirrors the protocols used in physical test scenarios, facilitating a hybrid physical-virtual operational model.
3. Validation and Experiments:
   • An experimental scenario involving the coordination of CAVs in a roundabout was tested in both digital and physical settings, yielding comparable results with noteworthy insights into the behavior of Intelligent Driver Model (IDM) vehicles under varied conditions.
   • Through the simulation architecture, parameters adjustable within Unity allow system-level adjustments to test control algorithms ahead of deployment in a physical scaled environment.

Implications and Future Research Directions

The IDS 3D City framework provides significant utility for researchers, affording a flexible, scalable, and similarly dynamic environment in which to test CAV methodologies. Practical implications include enhanced experimentation capabilities, expedited algorithm validation processes, and progressive development of CAV controls. This integrated environment allows for granular testing in a virtual setting, with direct transition capabilities to real-world applications.

The potential for future developments is vast. The authors suggest directions such as integrating air-ground cooperative control models, advancing mixed traffic scenarios involving both human-driven and automated vehicles, and the development of augmented-reality applications augmenting digital simulations with live physical controls. Additionally, there is promising room for advancements in optimal trajectory planning and interference predictions within this and similar systems.

This simulation framework highlights the importance of bridging the gap between purely physical and exclusively digital testing environments and serves as a model for future developments within smart city applications and CAV technology deployment. The IDS 3D City thus contributes significantly to validating and effectively deploying emerging mobility systems in increasingly complex urban environments.