V2I Communication Research Articles

Vehicle Safety Application through the Integration of Flood Detection and Safe Overtaking in Vehicular Communication

Road safety in Malaysia is a major concern due to frequent floods and accidents caused by overtaking. These issues result in significant injuries and losses. In this paper, we introduce a new system called the Safe Driving Tool (SDT). The SDT integrates a Flood Detection System (FDS) and a Vehicle Overtaking System (VOS) using Long-Range (LoRa) communication technology. The FDS continuously monitors water levels in flood-prone areas. It alerts drivers about potential hazards through vehicle-to-infrastructure (V2I) communication. Simultaneously, the VOS enables safe overtaking maneuvers. It does this by exchanging information with nearby vehicles through vehicle-to-vehicle (V2V) communication. Through testing and experimentation, we have shown that the SDT system effectively reduces accident risks and losses associated with floods and overtaking. The system's performance under various conditions confirms the reliability and effectiveness of LoRa communication technology in enhancing vehicular safety. This study represents a significant advancement in road safety. It combines flood detection and overtaking assistance into a single unified system, addressing two major causes of road accidents in Malaysia. The integration of V2I and V2V communication provides a comprehensive solution that improves driver awareness and decision-making. This ultimately leads to safer driving environments and enhanced driver convenience. Doi: 10.28991/CEJ-2024-010-09-015 Full Text: PDF

Software Defined Radio-Based Long-Term Evolution for Infrastructure-Based Vulnerable Road Users Safety: A Field Demonstration

The limited connectivity of vehicles presents a notable challenge, as their inability to establish communication with other vehicles and pedestrians can lead to safety concerns, particularly for vulnerable road users (VRUs). The Infrastructure-to-Pedestrian (I2P) communication pathway can play a vital role in mitigating these safety concerns, as implementing I2P is expected to significantly enhance safety for pedestrians, cyclists, and motorcyclists. The Third Generation Partnership Program (3GPP) introduced cellular vehicle-to-everything (V2X) communication with the release for 3GPP Release 14 in 2017. In this paper, we conduct an extensive review of V2I and I2P communication, and then present a Long-Term Evolution (LTE)-I2P communication architecture. We later describe key ideas of software-defined networks and their concepts for I2P services. Additionally, we conduct a field test of I2P LTE-based communication and assess its feasibility. The urban connected testbed in downtown Chattanooga, “MLK Smart Corridor,” services is the experimental platform for this assessment. Performance indicators like average end-to-end (E2E) latency and packet delivery ratio (PDR) are used for comparison.

A Full-Metal Dual-Band Millimeter-Wave Antenna Array With Concomitant Multifold Orthogonal Beamforming for V2V and V2I Communications

A Full-Metal Dual-Band Millimeter-Wave Antenna Array With Concomitant Multifold Orthogonal Beamforming for V2V and V2I Communications

Deep Reinforcement Learning Assisted Hybrid Precoding for V2I Communications With Doppler Shift and Delay Spread

Deep Reinforcement Learning Assisted Hybrid Precoding for V2I Communications With Doppler Shift and Delay Spread

Secure and efficient vehicle data downloading scheme with privacy-preserving in VANETs

Data downloading is a basic data transfer requirement in VANETs. Cooperation data downloading can use all V2C, V2I and V2V communications to improve the data downloading efficiency. Security and identity privacy preserving of data downloading should be paid more attention to protect the required vehicle. Otherwise, the data and identity information leakages would lead to immeasurable loss. To address these challenges, we propose a lattice-based secure vehicle data downloading scheme with privacy-preserving for VANETs. The vehicle request message authentication and identity privacy of the vehicle are achieved by a designed lattice-based ring signature. We prove that the proposed scheme is strong unforgeable and unconditional privacy preserving in the random oracle model. The request data also is encrypted by a symmetric encryption algorithm to achieve the data confidentiality. Moreover, thanks to the post-quantum security of the lattice-based cryptographic tools, the proposed data downloading also can defend against the quantum attacks. At the same time, cooperation data downloading also can be used in this paper to improve the effects of data downloading. Performance comparison and analysis shows that the proposed scheme shares some advantages with respect to the space and computation efficiency. The main character of the proposed scheme is that the impact of the vehicle ring group number on both the computation and space efficiency is effective controlled, such as the fixed signature length for any ring group size. As a result, the bandwidth and computation resources of VANETs can be saved by using the proposed scheme. We also simulate the proposed scheme by NS-3 which shows the average download success ratio is always within the interval [95%−100%] and cooperative downloading can improve the downloading efficiency by 86%.

The Environmental Benefits of an Automatic Idling Control System of Connected and Autonomous Vehicles (CAVs)

The transportation sector is regarded as the main culprit in greenhouse gas emission in the urban network, particularly idling vehicles waiting at signalized intersections. Although autonomous vehicles can be a promising technology to tackle vehicle idling, their environmental benefits receive little attention compared with their safety and mobility issues. This study investigated the environmental benefits of autonomous vehicles equipped with an automatic idling control function based on the queue discharge time and traffic signal information transmitted from the traffic signal controller via V2I communication using microscopic mobility and emission simulation models, VISSIM and MOVES, in Haeundae-gu in Busan, Korea. This study found that the function contributes to a significant reduction in CO2 emissions by 23.6% for all-inclusive emission and 94.3% for idling emission, respectively. Moreover, total reduced idling time accounts for 47.6% of the total travel time and 94.3% of the total idling time, respectively. Consequently, the autonomous vehicles equipped with automatic vehicle idling control function under C-ITS can play an important role in reducing greenhouse gas emissions and fuel consumption as well in the urban network.

An Improved Authentication Scheme for V2I Communication

An Improved Authentication Scheme for V2I Communication

Beam Tracking Assisted High Mobility V2I Communications With Extremely Large Lens Antenna Array

Beam Tracking Assisted High Mobility V2I Communications With Extremely Large Lens Antenna Array

Privacy-preserving V2I communication and secure authentication using ECC with physical unclonable function

Privacy-preserving V2I communication and secure authentication using ECC with physical unclonable function

A Compact Filtering Antenna System with Wide-Angle Scanning Capability for V2I Communication

A Compact Filtering Antenna System with Wide-Angle Scanning Capability for V2I Communication

Evaluation of the performance of the vehicular ad hoc network protocols in the case of V2I and EV2I communications

Vehicular ad hoc network (VANET) is an intelligent technology that enables efficient communication, secure data transmission, and traffic management. The purpose of routing protocols in the VANET network is to route data between vehicles (V2V) and vehicles-to-infrastructure (V2I). Recently, researchers have shown interest in designing effective routing protocols for the VANET network, as not all existing protocols are suitable for all traffic scenarios. Electric vehicles (EVs) are increasingly being adopted and integrated into intelligent transportation systems (ITS). Developed countries are actively promoting sustainable transportation solutions to increase energy efficiency and reduce carbon emissions. Therefore, this research presents an EV charging station (CS) management scheme based on communication between EVs and RSUs, with performance evaluation simulated using VANET network protocols. In this study, the G-MDORA, MDORA, and geographical routing protocol (GRP) protocols were modified to accommodate V2I communication, and RSUs were distributed along the roadmap. Additionally, a scheme for managing electric vehicle CS was presented, focusing on the communication between electric vehicles and RSUs in the EV2I context. Performance was evaluated using the G-MDORA, GRP, and MDORA protocols, considering factors such as throughput, communication overhead, packet delivery ratio, and end to end delay.

Beam Tracking Based on a New State Model for mmWave V2I Communication on 3D Roads

<p>The expansion of 5G and Internet of Things has laid a good foundation for the in-depth research of Internet of vehicles. Low frequency resources are scarce, and Internet of vehicles communication requires extremely high communication rate. Millimeter wave can meet the above two requirements, but its characteristics and the complicated communication conditions of Internet of vehicles make it difficult to combine the two. Overcoming these problems and making beam tracking accurate and steady is a major challenge at present. In this paper, a new extended Kalman filter tracking algorithm is proposed for mmWave V2I scenarios. On the basis of the original algorithm, a threshold prediction update mechanism is added. A new scheme is adopted, which takes position and velocity as tracking variables, and the tracking model is derived for the first time in MIMO 3D scenarios based on this scheme. The model considers the three-dimensional road conditions, including the vehicle deflection motion and the millimeter wave link blocked by large vehicles, which is more suitable for practical application scenarios. The simulation results reveal that the position and velocity tracking scheme is superior to the angle and gain tracking scheme, and the tracking error of the proposed algorithm is lower than that of the algorithms using similar state models. Based on the three-dimensional scene, it considers more realistic situations, and is more consistent with the kinematic characteristics of the vehicle and has more practical significance.</p> <p> </p>

Position-Based Adaptive Beamforming and Roadside Unit Sectorization for V2I Communications

Position-Based Adaptive Beamforming and Roadside Unit Sectorization for V2I Communications

Reinforcement Learning-Based Joint Beamwidth and Beam Alignment Interval Optimization in V2I Communications

The directional antenna combined with beamforming is one of the attractive solutions to accommodate high data rate applications in 5G vehicle communications. However, the directional nature of beamforming requires beam alignment between the transmitter and the receiver, which incurs significant signaling overhead. Hence, we need to find the optimal parameters for directional beamforming, i.e., the antenna beamwidth and beam alignment interval, that maximize the throughput, taking the beam alignment overhead into consideration. In this paper, we propose a reinforcement learning (RL)-based beamforming scheme in a vehicle-to-infrastructure system, where we jointly determine the antenna beamwidth and the beam alignment interval, taking into account the past and future rewards. The simulation results show that the proposed RL-based joint beamforming scheme outperforms conventional beamforming schemes in terms of the average throughput and the average link stability ratio.

Image-Based Beam Tracking With Deep Learning for mmWave V2I Communication Systems

Image-Based Beam Tracking With Deep Learning for mmWave V2I Communication Systems

Multicriteria and Quality of Service- Aware Vertical Handover Solution for Vehicle-to-Infrastructure Communication in Multitier Heterogeneous Networks.

The growing integration of vehicle-to-infrastructure (V2I) communication within multitier heterogeneous networks (HetNets) introduces challenges in maintaining seamless connectivity and Quality of Service (QoS) for vehicular users. This paper introduces a modified Multicriteria and QoS-aware Vertical Handover Decision Algorithm (mV2I-MHA) tailored to address these challenges. By considering multiple criteria - such as packet loss ratio, cost, available bandwidth and packet latency - the proposed solution intelligently manages vertical handovers between different network tiers. Numerous Multi-Criteria Decision-Making (MCDM) techniques have been proposed to address the right target network selection aiming to reduce unnecessary handovers, incorrect network selections and the associated processing time. However, many of these solutions overlook the significance of varying criteria weights in vertical handover decisions made by their selection algorithms. Through comprehensive simulations and comparisons with existing techniques, the effectiveness of the proposed – in this paper - solution is demonstrated in enhancing handover success rate, reducing handover failure rate, minimizing latency, and overall elevating the QoS for V2I communication in multitier HetNets. MATLAB R2020a was utilized to simulate the work. Using packet latency and handover failure as the metrics for performance, the results were contrasted with those of an existing works in terms of handover failure rate and packet delay. The developed mV2I-MHA showed considerable percentage reductions of 10.5% and 23.9% in packet latency and handover failure rate, respectively.

LSTM-Based Predictive mmWave Beam Tracking via Sub-6 GHz Channels for V2I Communications

LSTM-Based Predictive mmWave Beam Tracking via Sub-6 GHz Channels for V2I Communications

Deep Reinforcement Learning-Based mmWave Beam Alignment for V2I Communications

Deep Reinforcement Learning-Based mmWave Beam Alignment for V2I Communications

Predictive Beam Tracking and Power Allocation With Cooperative Sensing for V2I Communication

Predictive Beam Tracking and Power Allocation With Cooperative Sensing for V2I Communication

Effective Joint Scheduling and Power Allocation for URLLC-Oriented V2I Communications

Effective Joint Scheduling and Power Allocation for URLLC-Oriented V2I Communications