It is important to sufficiently guarantee an automotive system's safety, because otherwise terrible consequences may happen. Generally the safety in an automotive system includes two aspects: reliability and timeliness. Previous studies have proposed many approaches to how to improve them. However, few of them consider the development cost along with their improvement. In this study, we aim to propose a method that can build a safety-guaranteed and development cost-minimized schedule for functionality modeled as a directed acyclic graph running on an automotive system. Unlike previous studies that tightly couple the development cost minimization with other requirements together, we start by building a schedule with the minimum development cost by ignoring safety requirement. Then, reliability and real-time requirements are subsequently taken into consideration. Together with automotive safety integrity level decomposition options provided by International Standard called ISO 26262, the decomposition is evaluated for each task to improve its safety, and tasks are then successively chosen to adjust the schedule, such that its safety can be maximized with incurring the least extra development cost. This procedure continues until a schedule that meets safety requirement is built. Experiments on a real-life automotive benchmark and extensive synthetic functionality demonstrate that our proposed heuristics outperform the state-of-the-art heuristic algorithm, and a typical intelligent optimization algorithm.
|Original language||English (US)|
|Journal||IEEE Transactions on Intelligent Transportation Systems|
|State||Accepted/In press - 2020|
All Science Journal Classification (ASJC) codes
- Automotive Engineering
- Mechanical Engineering
- Computer Science Applications
- Automotive safety integrity level (ASIL)
- DAG functionality
- automotive system
- directed acyclic graph (DAG)
- genetic algorithm
- intelligent optimization machine learning.
- safety guarantee
- schedule optimization