Artificial Intelligence and Internet of Things for autonomous vehicles

Artificial Intelligence (AI) is a machine intelligence tool providing enormous possibilities for smart industrial revolution. It facilitates gathering relevant data/information, identifying the alternatives, choosing among alternatives, taking some actions, making a decision, reviewing the decision, and predicting smartly. On the other hand, Internet of Things (IoT) is the axiom of industry 4.0 revolution, including a worldwide infrastructure for collecting and processing of the data/information from storage, actuation, sensing, advanced services and communication technologies. The combination of high-speed, resilient, low-latency connectivity, and technologies of AI and IoT will enable the transformation towards fully smart Autonomous Vehicle (AV) that illustrate the complementary between real world and digital knowledge for industry 4.0. The purpose of this book chapter is to examine how the latest approaches in AI and IoT can assist in the search for the AV. It has been shown that human errors are the source of 90% of automotive crashes, and the safest drivers drive ten times better than the average [1]. The automated vehicle safety is significant, and users are requiring 1000 times smaller acceptable risk level. Some of the incredible benefits of AVs are: (1) increasing vehicle safety, (2) reduction of accidents, (3) reduction of fuel consumption, (4) releasing of driver time and business opportunities, (5) new potential market opportunities, and (6) reduced emissions and dust particles. However, AVs must use large-scale data/information from their sensors and devices

Emerging freeway traffic control strategies

Classical freeway traffic control approaches can be conveniently revisited in the light of the new technologies which have revolutionised data collection, data processing, communications and computing. In this chapter, the emerging freeway traffic control paradigms are illustrated, without claiming to be exhaustive, as the emerging control concepts are constantly evolving together with the new technologies on which they are based. The scenarios that unfold on the horizon are incredibly dense with potentialities and opportunities. Traffic data acquisition can be performed supplementing fixed sensors with probe vehicles. The overall traffic flow, even in case of mixed traffic consisting of conventional vehicles and intelligent vehicles, can be influenced by acting in a coordinated way at the level of the single intelligent vehicle. Large amounts of data can be collected, also exploiting unconventional data sources like social networks, making of paramount importance the development of traffic-oriented big data technologies, as well as efficient data mining techniques, in order to distinguish between useful and non-useful data and suitably process them. Privacy-preserving data sharing, cybersecurity, fault-tolerance and resilience concepts also play an important role in this new and challenging scenario