As the automotive industry focuses its attention more and more towards the software functionality of vehicles, 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 limitations from computational resources; nonetheless, the automotive field is starting to take interest in this technique. This work aims at demonstrating and evaluating a prototypical Continuous Experimentation infrastructure, implemented on a distributed computational system housed in a commercial truck tractor that is used in daily operations by a logistic company on public roads. The system comprises computing units and sensors, and software deployment and data retrieval are only possible remotely via a mobile data connection due to the commercial interests of the logistics company. This study shows that the proposed experimentation process resulted in the development team being able to base software development choices on the real-world data collected during the experimental procedure. Additionally, a set of previously identified design criteria to enable Continuous Experimentation on automotive systems was discussed and their validity confirmed in the light of the presented work.

中文翻译：

---

以重型商用车日常运行为例，对汽车软件进行连续实验

随着汽车行业越来越关注车辆的软件功能，需要快速交付新软件价值的技术。持续实验，一种来自基于网络的系统世界的实践，就是这样的技术之一。它使研究人员和开发人员能够使用真实世界的数据来验证他们的假设，并根据性能和用户偏好引导软件发展，减少对模拟和猜测的依赖。一些挑战阻止了这种做法在汽车网络物理系统上的逐字采用，例如安全问题和计算资源的限制；尽管如此，汽车领域开始对这种技术产生兴趣。这项工作旨在演示和评估原型连续实验基础设施，该基础设施在安装在商用卡车拖拉机中的分布式计算系统上实施，该拖拉机由公共道路上的物流公司用于日常运营。该系统包括计算单元和传感器，出于物流公司的商业利益，软件部署和数据检索只能通过移动数据连接远程进行。这项研究表明，提议的实验过程使开发团队能够根据在实验过程中收集的真实世界数据做出软件开发选择。此外，