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As the automotive industry focuses its attention more and more towards thesoftware functionality of vehicles, techniques to deliver new software value ata fast pace are needed. Continuous Experimentation, a practice coming from theweb-based systems world, is one of such techniques. It enables researchers anddevelopers to use real-world data to verify their hypothesis and steer thesoftware evolution based on performances and user preferences, reducing thereliance on simulations and guesswork. Several challenges prevent the verbatimadoption of this practice on automotive cyber-physical systems, e.g., safetyconcerns and limitations from computational resources; nonetheless, theautomotive field is starting to take interest in this technique. This work aimsat demonstrating and evaluating a prototypical Continuous Experimentationinfrastructure, implemented on a distributed computational system housed in acommercial truck tractor that is used in daily operations by a logistic companyon public roads. The system comprises computing units and sensors, and softwaredeployment and data retrieval are only possible remotely via a mobile dataconnection due to the commercial interests of the logistics company. This studyshows that the proposed experimentation process resulted in the developmentteam being able to base software development choices on the real-world datacollected during the experimental procedure. Additionally, a set of previouslyidentified design criteria to enable Continuous Experimentation on automotivesystems was discussed and their validity confirmed in the light of thepresented work.

Continuous Experimentation for Automotive Software on the Example of a Heavy Commercial Vehicle in Daily Operation