Technology Developments and Impacts of Connected and Autonomous Vehicles: An Overview

Abstract

The scientific advancements in the vehicle and infrastructure automation industry are progressively improving nowadays to provide benefits for the end-users in terms of traffic congestion reduction, safety enhancements, stress-free travels, fuel cost savings, and smart parking, etc. The advances in connected, autonomous, and connected autonomous vehicles (CV, AV, and CAV) depend on the continuous technology developments in the advanced driving assistance systems (ADAS). A clear view of the technology developments related to the AVs will give the users insights on the evolution of the technology and predict future research needs. In this paper, firstly, a review is performed on the available ADAS technologies, their functions, and the expected benefits in the context of CVs, AVs, and CAVs such as the sensors deployed on the partial or fully automated vehicles (Radar, LiDAR, etc.), the communication systems for vehicle-to-vehicle and vehicle-to-infrastructure networking, and the adaptive and cooperative adaptive cruise control technology (ACC/CACC). Secondly, for any technologies to be applied in practical AVs related applications, this study also includes a detailed review in the state/federal guidance, legislation, and regulations toward AVs related applications. Last but not least, the impacts of CVs, AVs, and CAVs on traffic are also reviewed to evaluate the potential benefits as the AV related technologies penetrating in the market. Based on the extensive reviews in this paper, the future related research gaps in technology development and impact analysis are also discussed.

Autonomous Robots for Services—State of the Art, Challenges, and Research Areas

“…Research has shown that CAV communications are of undeniable importance. The current state of the art shows that the evolution of these connected autonomous vehicles (CAVs) in terms of vehicle-to-vehicle (V2V) communication is very well developed with a wide range of vehicle-to-infrastructure (V2I) implications [ 73 ].…”

Emerging opportunities for wildlife conservation with sustainable autonomous transportation

“…Object detection algorithms for AVs focus primarily on road signs, pedestrians, cyclists, or other vehicles (eg Jahromi et al 2019;Rosique et al 2019;Ahmed et al 2022), with comparatively fewer methods designed for animal detection (Sharma and Shah 2017;Munian et al 2020;Saxena et al 2020). The high levels of morphological variation across species, along with a wide range of sensory perception processes, behavioral responses, and means of locomotion, introduce several obstacles to automated animal detection methods.…”

Emergency Vehicle Driving Assistance System Using Recurrent Neural Network with Navigational Data Processing Method

“…One of the technological factors that can have a significant impact on emergency vehicle driving is the use of GPS and navigation systems. These systems can provide real-time updates about traffic conditions and route emergency vehicles around congestion or other obstacles, helping to ensure that they can reach their destination as quickly and efficiently as possible [8,9]. Another important technological factor is vehicle-to-everything communication, which enables vehicles to communicate with each other and with infrastructures, such as traffic signals and parking garages.…”