Internet of Things-aided Smart Grid: Technologies, Architectures, Applications, Prototypes, and Future Research Directions

Traditional power grids are being transformed into Smart Grids (SGs) to address the issues in existing power system due to uni-directional information flow, energy wastage, growing energy demand, reliability and security. SGs offer bi-directional energy flow between service providers and consumers, involving power generation, transmission, distribution and utilization systems. SGs employ various devices for the monitoring, analysis and control of the grid, deployed at power plants, distribution centers and in consumers' premises in a very large number. Hence, an SG requires connectivity, automation and the tracking of such devices. This is achieved with the help of Internet of Things (IoT). IoT helps SG systems to support various network functions throughout the generation, transmission, distribution and consumption of energy by incorporating IoT devices (such as sensors, actuators and smart meters), as well as by providing the connectivity, automation and tracking for such devices. In this paper, we provide a comprehensive survey on IoT-aided SG systems, which includes the existing architectures, applications and prototypes of IoT-aided SG systems. This survey also highlights the open issues, challenges and future research directions for IoT-aided SG systems

Big Data and the Internet of Things

Advances in sensing and computing capabilities are making it possible to embed increasing computing power in small devices. This has enabled the sensing devices not just to passively capture data at very high resolution but also to take sophisticated actions in response. Combined with advances in communication, this is resulting in an ecosystem of highly interconnected devices referred to as the Internet of Things - IoT. In conjunction, the advances in machine learning have allowed building models on this ever increasing amounts of data. Consequently, devices all the way from heavy assets such as aircraft engines to wearables such as health monitors can all now not only generate massive amounts of data but can draw back on aggregate analytics to "improve" their performance over time. Big data analytics has been identified as a key enabler for the IoT. In this chapter, we discuss various avenues of the IoT where big data analytics either is already making a significant impact or is on the cusp of doing so. We also discuss social implications and areas of concern.Comment: 33 pages. draft of upcoming book chapter in Japkowicz and Stefanowski (eds.) Big Data Analysis: New algorithms for a new society, Springer Series on Studies in Big Data, to appea

A Systematic Survey of Control Techniques and Applications: From Autonomous Vehicles to Connected and Automated Vehicles

Vehicle control is one of the most critical challenges in autonomous vehicles (AVs) and connected and automated vehicles (CAVs), and it is paramount in vehicle safety, passenger comfort, transportation efficiency, and energy saving. This survey attempts to provide a comprehensive and thorough overview of the current state of vehicle control technology, focusing on the evolution from vehicle state estimation and trajectory tracking control in AVs at the microscopic level to collaborative control in CAVs at the macroscopic level. First, this review starts with vehicle key state estimation, specifically vehicle sideslip angle, which is the most pivotal state for vehicle trajectory control, to discuss representative approaches. Then, we present symbolic vehicle trajectory tracking control approaches for AVs. On top of that, we further review the collaborative control frameworks for CAVs and corresponding applications. Finally, this survey concludes with a discussion of future research directions and the challenges. This survey aims to provide a contextualized and in-depth look at state of the art in vehicle control for AVs and CAVs, identifying critical areas of focus and pointing out the potential areas for further exploration

Milestones in Autonomous Driving and Intelligent Vehicles Part \uppercase\expandafter{\romannumeral1}: Control, Computing System Design, Communication, HD Map, Testing, and Human Behaviors

Interest in autonomous driving (AD) and intelligent vehicles (IVs) is growing at a rapid pace due to the convenience, safety, and economic benefits. Although a number of surveys have reviewed research achievements in this field, they are still limited in specific tasks and lack systematic summaries and research directions in the future. Our work is divided into 3 independent articles and the first part is a Survey of Surveys (SoS) for total technologies of AD and IVs that involves the history, summarizes the milestones, and provides the perspectives, ethics, and future research directions. This is the second part (Part \uppercase\expandafter{\romannumeral1} for this technical survey) to review the development of control, computing system design, communication, High Definition map (HD map), testing, and human behaviors in IVs. In addition, the third part (Part \uppercase\expandafter{\romannumeral2} for this technical survey) is to review the perception and planning sections. The objective of this paper is to involve all the sections of AD, summarize the latest technical milestones, and guide abecedarians to quickly understand the development of AD and IVs. Combining the SoS and Part \uppercase\expandafter{\romannumeral2}, we anticipate that this work will bring novel and diverse insights to researchers and abecedarians, and serve as a bridge between past and future.Comment: 18 pages, 4 figures, 3 table

Automated driving and autonomous functions on road vehicles

In recent years, road vehicle automation has become an important and popular topic for research and development in both academic and industrial spheres. New developments received extensive coverage in the popular press, and it may be said that the topic has captured the public imagination. Indeed, the topic has generated interest across a wide range of academic, industry and governmental communities, well beyond vehicle engineering; these include computer science, transportation, urban planning, legal, social science and psychology. While this follows a similar surge of interest – and subsequent hiatus – of Automated Highway Systems in the 1990’s, the current level of interest is substantially greater, and current expectations are high. It is common to frame the new technologies under the banner of “self-driving cars” – robotic systems potentially taking over the entire role of the human driver, a capability that does not fully exist at present. However, this single vision leads one to ignore the existing range of automated systems that are both feasible and useful. Recent developments are underpinned by substantial and long-term trends in “computerisation” of the automobile, with developments in sensors, actuators and control technologies to spur the new developments in both industry and academia. In this paper we review the evolution of the intelligent vehicle and the supporting technologies with a focus on the progress and key challenges for vehicle system dynamics. A number of relevant themes around driving automation are explored in this article, with special focus on those most relevant to the underlying vehicle system dynamics. One conclusion is that increased precision is needed in sensing and controlling vehicle motions, a trend that can mimic that of the aerospace industry, and similarly benefit from increased use of redundant by-wire actuators