Continuous Experimentation for Automotive Software on the Example of a Heavy Commercial Vehicle in Daily Operation
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As the automotive industry focuses their efforts more and more towards the software end of the spectrum, techniques to deliver new software value at a fast pace are needed. Continuous Experimentation, a practice coming from the web-based systems world, is one of such techniques. It enables researchers and developers to use real-world data to verify their hypothesis and steer the software evolution based on performances and user preferences, reducing the reliance on simulations and guesswork. Several challenges prevent the verbatim adoption of this practice on automotive cyber-physical systems, e.g., safety concerns and computational resources limitations; nonetheless, the automotive field is starting to take interest in this technique. This work aims at demonstrating and evaluating a prototypical Continuous Experimentation cycle, performed on a distributed computational system housed in a commercial truck tractor that is used in daily operations by a logistic company. The system comprises computing units and sensors, and is only accessible remotely via a mobile connection, which is also the only communication channel that can be used for software deployment and data retrieval. The experimentation process resulted in the team being able to base software development choices on the real-world data collected during the experimental procedure. Finally, a set of previously identified design criteria to enable Continuous Experimentation on automotive systems was discussed in light of the presented work.
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