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Data Offloading Approaches for Vehicle-to-Everything (V2X) Communications in 5G and Beyond
Published in Hussein T. Mouftah, Melike Erol-Kantarci, Sameh Sorour, Connected and Autonomous Vehicles in Smart Cities, 2020
Muhammed Nur Avcil, Mujdat Soyturk
V2X Communication: All of the communication methods required for vehicles to exchange data with other vehicles, infrastructure and environment are called V2X (Vehicle-to-Everything) communication [17]. The communication methods defined with V2X communication (as shown in Figure 9.1) are: – Vehicle to vehicle communication (V2V)– Vehicle to infrastructure communication (V2I)– Vehicle to cellular network communication (V2N)– Vehicle to portable devices (V2P)
Other technology aspects
Published in Hanky Sjafrie, Introduction to Self-Driving Vehicle Technology, 2019
V2XVehicle-to-Everything (V2X) is a general term for external communication between vehicles and other participants, mobile or stationary, in an intelligent traffic system. ETSI distinguishes four types of V2X communication: Vehicle-to-Vehicle (V2V)Vehicle-to-Vehicle (V2V), Vehicle-to-Infrastructure (V2I)Vehicle-to-Infrastructure (V2I), Vehicle-to-Network (V2N)Vehicle-to-Network (V2N), and Vehicle-to-Pedestrian (V2P)Vehicle-to-Pedestrian (V2P) [12]. V2V focuses on information exchange between vehicles in close proximity to each other. V2I refers to direct communication between vehicles and intelligent roads infrastructure, also known as Roadside Units (RSUs). V2N is associated with communication between vehicles and the Internet. V2P encompasses vehicle communication with human traffic participants, e.g., pedestrians, cyclists, etc.
Smart Urban Traffic Management for an Efficient Smart City
Published in Mohamed Lahby, Utku Kose, Akash Kumar Bhoi, Explainable Artificial Intelligence for Smart Cities, 2021
M. El Khaili, L. Terrada, A. Daaif, H. Ouajji
V2X, which stands for ‘vehicle to everything’, is the umbrella term for the car’s communication system, where information from sensors and other sources travel via high-bandwidth, low-latency, high-reliability links, paving the way to fully autonomous driving (Chen et al., 2017).
Smart Mobility in Smart Cities: Emerging challenges, recent advances and future directions
Published in Journal of Intelligent Transportation Systems, 2023
Soumia Goumiri, Saïd Yahiaoui, Soufiene Djahel
Enhancing the smartness of the new constructed roads and upgrading the existing infrastructure to make it more interactive with autonomous vehicles, for example, will certainly play a major role in reducing causalities on the roads. Such smart roads will be a source of a wealth of traffic data that can be of utmost importance to autonomous vehicles as well as traffic authorities to help them make optimal decisions to enhance the road safety. However, the vulnerability of autonomous vehicles to cyber attacks Sheehan et al. (2019) will constantly threaten the road safety if sophisticated countermeasures are not in place. Indeed, a hacker who succeeds to remotely control an autonomous vehicle can cause serious disruption to the traffic flow with high risks of human lives loss. Therefore, car manufacturers and cyber security researches and SMEs are invited to join their efforts to be ahead of the hackers by constantly thinking of new attack scenarios and developing solutions to face them. C-V2X (Cellular Vehicle-to-Everything) communication technologies refer to a system, where “everything” (i.e., the X) may be a different car, a person walking, a piece of road infrastructure, or a network server. This new emerging technology can enhance data collection and processing which will improve the decision making.
A Brief Review on mm-Wave Antennas for 5G and Beyond Applications
Published in IETE Technical Review, 2023
Paikhomba Loktongbam, Debasish Pal, A. K. Bandyopadhyay, Chaitali Koley
The future generation vehicular industry will be ubiquitously equipped with high-speed internet connections [186]. But this type of internet integrated technology for vehicular applications needs a considerable amount of data management and large bandwidth. Various modern technologies for vehicular applications (like Bluetooth, Zig-Bee, Radio-Frequency Identification, Ultra-Wideband, etc.) have been compared in [184]. Vehicular network technology mainly consists of V2V (vehicle-to-vehicle), V2I (vehicle-to-Internet), V2R (vehicle-to-road infrastructure), V2X (vehicle to everything), Vehicle-to-Device (V2D), Vehicle-to-Pedestrian (V2P), Vehicle-to-Grid (V2G). mm-wave communication is expected to play a crucial role in vehicular network communication, and some in-vehicle mm-wave communication measurements have been reported in [185].
Traffic efficiency and fairness optimisation for autonomous intersection management based on reinforcement learning
Published in Transportmetrica A: Transport Science, 2023
Yuanyuan Wu, David Z. W. Wang, Feng Zhu
With advanced on-board sensors, wireless Vehicle-to-Everything (V2X) communication technologies, precise control systems, high-level Connected and Automated Vehicles (CAVs) are able to perceive and exchange environmental information with each other and surroundings, including other V2X device equipped road users and traffic control infrastructures (Eskandarian, Wu, and Sun 2019; Molina-Masegosa and Gozalvez 2017). Thanks to the various automated driving systems (Xia et al. 2022, 2023), CAVs have the potential to change the way we travel and bring about transformative safety, mobility, energy and environment benefits. They are considered to be promising solutions for realising the envisioned autonomous traffic management systems in the future (Ngoduy, Keyvan-Ekbatani, and Treiber 2021; Rashidi et al. 2020; Shladover 2018). Originally proposed by Dresner and Stone (2004), Autonomous Intersection Management (AIM) is one of the envisaged systems tailored for CAVs, in which the traditional intersection management methods, such as traffic lights, are replaced by a reservation-based control system taking advantages of the communication ability of CAVs. It is a multi-agent system, in which CAVs are seen as autonomous agents which would communicate with the intersection manager (IM) agent and request the right-of-way across the intersection. And the IM agent assigns the right-of-way base on the collision free principle in a First-Come-First-Served (FCFS) manner. The FCFS strategy was adopted in their subsequent work because of its straightforward and fair features (Dresner and Stone 2008), referred to as FCFS-AIM. FCFS-AIM schedules the crossing of vehicles at intersections according to the order in which the vehicles approach, which is considered to be the fairest policy (Wierman 2011). However, this kind of fairness is rarely considered in follow-up research.