AUTOSAR Runnable Periods Optimization for DAG-Based Complex Automobile Applications

When developing an automobile control application, its scheduling parameters as well as the control algorithm itself should be carefully optimized to achieve the best control performance from given computing resources. Moreover, since the wide acceptance of the AUTOSAR standard, where finer-granular scheduling entities (called runnables) rather than the traditional real-time tasks are used, the number of scheduling parameters to be optimized is far greater than the traditional task-based control systems. Hence, due to the vast problem space, it is not feasible to reuse existing time-consuming search-based optimization methods. With this motivation, this paper presents an analytical codesign method for deciding runnable periods that minimize given control cost functions. Our solution approach, based on the Lagrange multiplier method, can find optimized runnable periods in polynomial times due to its analytical nature. Moreover, our evaluation results for synthesized applications with varying complexities show that our method performs significantly better (12% to 59% of control cost reductions) than a state-of-the-art evolutionary algorithm. To the best of our knowledge, this study is one of the first attempts to find runnable periods that maximize a given system’s control performance.

Developing e-learning solutions in the automotive industry

In the rapid developing market of automotive industry, cutting-edge technologies are being introduced. One such example is the AUTOSAR standard. Companies are investing a large amount of finances for the training of their employees into the intricacies of such technologies. In order to face such an increase of the training costs, automotive corporation have started lately switching their approach to e-Learning systems. This paper presents an e-Learning approach developed in the automotive industry in order to address the demands of teaching AUTOSAR standard. The developed e-Learning project is called Academy. In order to develop the e-Learning solution we focused on the Software Development part of automotive industry. Therefore we had to gather the ideas from different trainers, come with a common approach and use specific techniques so that the trainee should get a real feeling of the material. It is presented the design, implementation and evaluation of this e-Learning solution, but more than that faced issues and learned lessons. Developing this solution has offered different insights into how to approach such a task which are useful for the further expansion of the project, but also for future researchers who might encounter such a challenge of developing e-Learning solutions for the automotive industry. These are all grouped in a set of guidelines related to following a model of implementation, getting track of participants, user interaction with the AUTOSAR standard, test and production development and so on.

Design of Vehicle Diagnostic Communication Module Based on AUTOSAR Software Architecture

In order to solve the problem that vehicle diagnostic system is of bad uniformity and versatility, which due to the different vehicle diagnostic system communication protocols developed by the different vehicle OEMs according to their own needs, this paper proposes a design method of vehicle CAN bus diagnostic communication module based on AUTOSAR standard. This module follow the AUTOSAR standard and it can be implemented in accordance with the international standard ISO 15765. The results of the test show that when this module is applied to some car dashboard, it can satisfy the needs of the vehicle diagnostic communication system, and it is of good standardization, versatility and portability.