Artificial Intelligence in Autonomous Vehicles—A Survey of Trends and Challenges

Summary

The potential for connected automated vehicles is multifaceted, and automated advancement deals with more of Internet of Things (IoTs) development enabling artificial intelligence (AI). Early advancements in engineering, electronics, and many other fields have inspired AI. There are several proposals of technologies used in automated vehicles. Automated vehicles contribute greatly toward traffic optimization and casualty reduction. In studying vehicle autonomy, there are two categories of development available: high‐level system integrations like new‐energy vehicles and intelligent transportation systems and the other involves backward subsystem advancement like sensor and information processing systems. The Advanced Driver Assistance System shows results that meet the expectations of real‐world problems in vehicle autonomy. Situational intelligence that collects enormous amounts of data is considered for high‐definition creation of city maps, land surveying, and quality checking of roads as well. The infotainment system of the transport covers the driver's gesture recognition, language transaction, and perception of the surroundings with the assistance of a camera, Light Detection and Ranging (LiDAR), and Radio Detection And Ranging (RADAR) along with localization of the objects in the scene. This chapter discusses the history of autonomous vehicles (AV), trending research areas of artificial intelligence technology in AV, state‐of‐the‐art datasets used for AV research, and several Machine Learning (ML)/Deep Learning (DL) algorithms constituting the functioning of AV as a system, concluding with the challenges and opportunities of AI in AV.