In recent years, connected vehicle technologies emerged to provide a safer and more connected environment for transportation systems, which has further evolved into cellular vehicle-to-everything (C-V2X) technology. The current study contributes in the direction of future research of smart India @2047 in connected vehicles. The study presents the diverse aspects of 5G V2X as a comprehensive overview of Vehicle-to-Everything (V2X) technology that covers the significant scope of V2X technology, including its development, components, functionality, use cases, and future potential. It is observed that few surveys are available that cover limited aspects of 5G V2X communication technologies, with one or two preferred architectures, and only few provides the definitions of 3GPP use cases. Emergency vehicles (EMV) are identified as an important part of an emergency service, and the main goal of EMV is to reduce the response time. The study discusses the research challenges in the field of V2X and presents future directions to reduce the probability of untoward incidents and enhance the EMV response time. The work leverages by synthesizing the latest research in 5G V2X technological advancements like Multiple Input Multiple Output, Beamforming, and Integrated Sensing and Communication, highlighting the roles of 5G architectures and providing a deeper understanding of the 5GAA V2X use cases from the perspective of societal benefit. The study provides a comprehensive future research directions to the researchers on 5G V2X technologies and current research trends for smart EMV applications.

The increasing proliferation of power electronic converters, nonlinear loads, and distributed generation are leading to increased levels of harmonic and interharmonics in power networks. As a consequence, power quality (PQ) has become a critical performance indicator for power utilities and end-users. This study proposes a novel harmonic estimation method based on the real-time stationary discrete wavelet packet transform (RT-SDWPT). The proposed technique decomposes an input signal into frequency bands with harmonic information at cutoff frequencies and uses a compensation strategy to estimate root mean square (RMS) values of harmonics at every sampling period. The performance and effectiveness of the proposed method are assessed using real measurement data from field cases and experimental setup. The real measurements include challenging scenarios with harmonics, subharmonics, interharmonics, frequency deviation, and non-stationary PQ events. The proposed method outperforms the harmonic estimation provided by the discrete Fourier transform (DFT)-based approach and existing wavelet packet-based methods in terms of accuracy and speed.

The Third Generation Partnership Project (3GPP) has specified Cellular Vehicle-to-Everything (C-V2X) radio access technology in Releases 15–17, with an emphasis on facilitating direct communication between vehicles through the interface, sidelink PC5. This interface provides end-to-end network slicing functionality together with a stable cloud-native core network. The performance of direct vehicle-to-vehicle (V2V) communications has been improved by using the sidelink interface, which allows for a network infrastructure bypass. Sidelink transmissions make use of orthogonal resources that are either centrally allocated (Mode 1, Release 14) or chosen by the vehicles themselves (Mode 2, Release 14). With growing interest in connected and autonomous vehicles, the advancement in radio access technologies that facilitate dependable and low-latency vehicular communications is becoming more significant. This is especially necessary when there are heavy traffic conditions and patterns. We thoroughly examined the New Radio (NR) sidelink’s performance based on 3GPP Releases 15–17 under various vehicle densities, speeds, and distance settings. Thus, by evaluating sidelink’s strengths and drawbacks, we are able to optimize resource allocation to obtain maximum coverage in urban areas. The performance evaluation was conducted on Network Simulator 3 (NS3.34/5G-LENA) utilizing various network metrics such as average packet reception rate, throughput, and latency.

The ever need for transportation safety, faster and convenient travel, decrease in energy consumption, as well as inter-connectivity has led to the field of intelligent transportation system (ITS). At the core of ITS is the Internet of Vehicles (IoV) combining hardware/sensors, software, and network technologies. Vehicular ad hoc networks (VANETs) create mechanisms to connect IoV main elements, including vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I), and Vehicle-to-Sensors (V2S). ITS systems heavily rely on its network connecting different parts of its infrastructure and ensuring data exchanges. However, VANET security is one of the primary challenges faced by connected vehicles. In IoV, the network is accessed by a variety device making the system vulnerable to a multitude of malicious attacks, including distributed denial-of-service (DDoS) and black hole attacks. Since critical vehicle systems can be accessed remotely, successful attacks can lead to fatalities. In VANET, any node can function as a router for the other nodes, therefore a malicious node connected to the network may inject spoofed routing tables to the other nodes thereby affecting the operation of the entire network. To overcome this issue, we proposed a security scheme designed to improve routing protocols in the detection of black hole attack. The proposed approach is demonstrated on a Network Simulator (NS3.27) using different network parameters such as average packet loss rate, end-to-end delay, packet delivery ratio (PDR) and network yield. Simulation results demonstrate the proposed method adds 10-15% improvement (on average) in End-to-End Delay, Packet Delivery Rate, Packet Loss Rate and Network Yield as compared with conventional Greedy Parameter Stateless Routing and Path Aware Greedy Parameter Stateless Routing under the black hole attack.