MultiDrive: A Co-Simulation Framework Bridging 2D and 3D Driving Simulation for AV Software Validation

TL;DR

MultiDrive is a co-simulation framework that seamlessly integrates 2D and 3D simulators for comprehensive AV software testing, enabling efficient scenario exploration and detailed validation.

Contribution

It introduces a novel multi-agent co-simulation framework that simplifies transitioning scenarios between simulators and automates testing processes for AV motion planning.

Findings

Uncovered discrepancies in motion planner behavior under realistic conditions

Automated scenario transition reduces testing effort

Framework supports detailed analysis and visualization

Abstract

Scenario-based testing using simulations is a cornerstone of Autonomous Vehicles (AVs) software validation. So far, developers needed to choose between low-fidelity 2D simulators to explore the scenario space efficiently, and high-fidelity 3D simulators to study relevant scenarios in more detail, thus reducing testing costs while mitigating the sim-to-real gap. This paper presents a novel framework that leverages multi-agent co-simulation and procedural scenario generation to support scenario-based testing across low- and high-fidelity simulators for the development of motion planning algorithms. Our framework limits the effort required to transition scenarios between simulators and automates experiment execution, trajectory analysis, and visualization. Experiments with a reference motion planner show that our framework uncovers discrepancies between the planner's intended and actual behavior, thus exposing weaknesses in planning assumptions under more realistic conditions. Our framework is available at: https://github.com/TUM-AVS/MultiDrive