Microservice Architectures for Advanced Driver Assistance Systems: A Case-Study

Lotz, Jannik; Vogelsang, Andreas; Benderius, Ola; Berger, Christian · 2019 · Crossref

DOI: 10.1109/icsa-c.2019.00016

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Summary

This paper presents a case study evaluating the feasibility and impact of adopting Microservice Architectures (MSA) for Advanced Driver Assistance Systems (ADAS) in automotive software. Motivated by the increasing complexity of vehicle software and the push toward autonomous driving, the authors investigate whether MSA principles—successful in web applications—can reduce complexity and improve agility in automotive contexts. The study aims to design, transform, implement, and test an ADAS function close to series production standards, specifically a lane-following system, to assess the strengths, weaknesses, opportunities, and threats of this architectural shift. The research was conducted at Chalmers University of Technology and the Revere vehicle research laboratory. The team transformed an existing lane detection algorithm into a microservice-based system using the OpenDLV software ecosystem, which utilizes the libcluon middleware for distributed systems. The implementation relied on Docker for containerization and Alpine Linux with the PREEMPT_RT kernel patch to ensure real-time performance and resource efficiency. The system architecture consisted of four distinct microservices: a camera proxy for data input, a lane detection service using OpenCV algorithms, a lane follower service calculating steering and acceleration requests, and a CAN proxy service translating high-level commands into vehicle bus messages. The system was tested on a Volvo XC90 experimental platform, with communication handled via UDP multicast and shared memory. The results, evaluated through a SWOT analysis, indicate that MSA offers significant advantages in modularity, reuse, and scalability. The architecture allowed for independent development, deployment, and testing of services, facilitating faster integration and easier comparison of service versions. Scalability was demonstrated by cloning services to distribute load across Electronic Control Units (ECUs). However, the study identified notable weaknesses, including the shifting of complexity from individual modules to system-level orchestration and monitoring, as well as high introduction costs related to restructuring team structures and increased memory overhead. Opportunities include shorter time-to-market through over-the-air updates and reduced dependency errors. Threats involve potential "architectural smells" such as cyclic dependencies or inappropriate service intimacy, and increased security risks due to a larger attack surface. The study concludes that microservice architectures can effectively prepare automotive software for future challenges by reducing inter-domain complexity and enabling agile development, provided that MSA principles are carefully followed. The authors emphasize that success depends not only on technical implementation but also on organizational changes, including breaking down traditional domain-based team structures and addressing security and architectural anti-patterns. The findings suggest that while MSA introduces initial costs and complexity shifts, it offers a robust path toward more maintainable and scalable automotive software systems.

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