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Companies developing and maintaining software-only products like web shopsaim for establishing persistent links to their software running in the field.Monitoring data from real usage scenarios allows for a number of improvementsin the software life-cycle, such as quick identification and solution ofissues, and elicitation of requirements from previously unexpected usage. Whilethe processes of continuous integration, continuous deployment, and continuousexperimentation using sandboxing technologies are becoming well established insaid software-only products, adopting similar practices for the automotivedomain is more complex mainly due to real-time and safety constraints. In thispaper, we systematically evaluate sandboxed software deployment in the contextof a self-driving heavy vehicle that participated in the 2016 Grand CooperativeDriving Challenge (GCDC) in The Netherlands. We measured the system'sscheduling precision after deploying applications in four different executionenvironments. Our results indicate that there is no significant difference inperformance and overhead when sandboxed environments are used compared tonatively deployed software. Thus, recent trends in software architecting,packaging, and maintenance using microservices encapsulated in sandboxes willhelp to realize similar software and system engineering for cyber-physicalsystems.

Systematic Evaluation of Sandboxed Software Deployment for Real-time Software on the Example of a Self-Driving Heavy Vehicle