Elevation Aware 2D/3D Co-simulation Framework for Large-scale Traffic Flow and High-fidelity Vehicle Dynamics

TL;DR

This paper introduces an elevation-aware co-simulation framework combining SUMO and CARLA, enabling realistic large-scale traffic and vehicle dynamics simulation in complex terrains for autonomous vehicle testing.

Contribution

The novel framework integrates real-world elevation data into traffic and vehicle simulation environments, improving realism for autonomous driving system testing.

Findings

Successfully integrates OpenStreetMap and USGS elevation data

Demonstrates scalability in San Francisco regions

Reproduces steep and irregular terrains accurately

Abstract

Reliable testing of autonomous driving systems requires simulation environments that combine large-scale traffic modeling with realistic 3D perception and terrain. Existing tools rarely capture real-world elevation, limiting their usefulness in cities with complex topography. This paper presents an automated, elevation-aware co-simulation framework that integrates SUMO with CARLA using a pipeline that fuses OpenStreetMap road networks and USGS elevation data into physically consistent 3D environments. The system generates smooth elevation profiles, validates geometric accuracy, and enables synchronized 2D-3D simulation across platforms. Demonstrations on multiple regions of San Francisco show the framework's scalability and ability to reproduce steep and irregular terrain. The result is a practical foundation for high-fidelity autonomous vehicle testing in realistic, elevation-rich urban settings.