Model-based Development for Autonomous Driving Software Considering Parallelization

TL;DR

This paper introduces a parallelization approach for autonomous driving software using Model-Based Development, enhancing real-time performance by extending existing methods to handle complex processing tasks.

Contribution

It extends the Model-Based Parallelizer to better support complex autonomous driving software, improving execution time and real-time capabilities.

Findings

Reduced execution time in autonomous driving software

Effective parallelization for complex processing tasks

Suitable for real-time autonomous vehicle applications

Abstract

In recent years, autonomous vehicles have attracted attention as one of the solutions to various social problems. However, autonomous driving software requires real-time performance as it considers a variety of functions and complex environments. Therefore, this paper proposes a parallelization method for autonomous driving software using the Model-Based Development (MBD) process. The proposed method extends the existing Model-Based Parallelizer (MBP) method to facilitate the implementation of complex processing. As a result, execution time was reduced. The evaluation results demonstrate that the proposed method is suitable for the development of autonomous driving software, particularly in achieving real-time performance.