When Intelligent Transportation Systems Sensing Meets Edge Computing: Vision and Challenges

The widespread use of mobile devices and sensors has motivated data-driven applications that can leverage the power of big data to benefit many aspects of our daily life, such as health, transportation, economy, and environment. Under the context of smart city, intelligent transportation systems (ITS), such as a main building block of modern cities and edge computing (EC), as an emerging computing service that targets addressing the limitations of cloud computing, have attracted increasing attention in the research community in recent years. It is well believed that the application of EC in ITS will have considerable benefits to transportation systems regarding efficiency, safety, and sustainability. Despite the growing trend in ITS and EC research, a big gap in the existing literature is identified: the intersection between these two promising directions has been far from well explored. In this paper, we focus on a critical part of ITS, i.e., sensing, and conducting a review on the recent advances in ITS sensing and EC applications in this field. The key challenges in ITS sensing and future directions with the integration of edge computing are discussed.

ExtendAIST: Exploring the Space of AI-in-the-Loop System Testing

The AI-in-the-loop system (AIS) has been widely used in various autonomous decision and control systems, such as computing vision, autonomous vehicle, and collision avoidance systems. AIS generates and updates control strategies through learning algorithms, which make the control behaviors non-deterministic and bring about the test oracle problem in AIS testing procedure. The traditional system mainly concerns about properties of safety, reliability, and real-time, while AIS concerns more about the correctness, robustness, and stiffness of system. To perform an AIS testing with the existing testing techniques according to the testing requirements, this paper presents an extendable framework of AI-in-the-loop system testing by exploring the key steps involved in the testing procedure, named ExtendAIST, which contributes to define the execution steps of ExtendAIST and design space of testing techniques. Furthermore, the ExtendAIST framework provides three concerns for AIS testing, which include: (a) the extension points; (b) sub-extension points; and (c) existing techniques commonly present in each point. Therefore, testers can obtain the testing strategy using existing techniques directly for corresponding testing requirements or extend more techniques based on these extension points.