Modeling and Simulation of Autonomous Driving Function in Functional Mockup Interface Using Virtual Test Co-simulation Environment

• Published in: 2022 IEEE 14th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM) pp. 1 - 6
• Main Authors: De Guia, Joseph M., Duraisamy, Nishanti, Opina, Gil L., Tripathi, Anshuman, Devaraj, Madhavi
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.12.2022
• Subjects: autonomous driving; Autonomous vehicles; Data models; functional mockup interface; Mathematical models; modeling and simulation; simulator; Software; Solid modeling; System integration; Vehicle dynamics; virtual test toolchain
• ISSN: 2770-0682
• DOI: 10.1109/HNICEM57413.2022.10109513

Modeling and simulation using Virtual Testing Toolchain (VTT) for autonomous driving (AD) is a helpful tool to integrate different platforms that can carry out co-simulation and exchange of data. This is to enable effective and efficient testing of autonomous vehicle (AV) performance without the physical vehicle and infrastructure. Therefore, the system integration can be executed in any of the platforms to simulate or describe the dynamic parts of the AV development from the different software environment. An open simulation with virtual approach is required relying on a simulation-driven, rule-based scenario evaluation and automated test execution. In this paper we explore and evaluate the AD controller model using Functional Mockup Interface (FMI) in a virtual testing co-simulation environment. The FMU was developed in MATLAB/Simulink. The FMU testing and verification use the open-loop approach for the Input/Output (I/O) component accuracy. Then co-simulate the FMU model in AVL Model. Connect with Vehicle Simulation Model (VSM) and Virtual Test Drive (VTD) as the VTT environment. This is to validate the AD controller five (5) test cases. The VTT simulation development of the AD controller function helps to validate the performance of the planner controller and obstacle detection. We were able to assess the FMU controller steering, brake, acceleration performance and compare the actual outputs of the AD system being evaluated.