Vehicular communication systems

About: Vehicular communication systems is a research topic. Over the lifetime, 2532 publications have been published within this topic receiving 64775 citations. The topic is also known as: V2V & vehicle-to-vehicle.

Location- and delay-aware cross-layer communication in V2I multihop vehicular networks

Abstract: Intelligent transportation systems are targeted to improve the traffic safety and driving experience of passengers. Vehicular ad hoc networks are wireless communication networks proposed to be used as parts of ITS. VANETs facilitate communication among vehicles, and between vehicles and roadside equipment. A key challenge in developing such systems is to design routing and MAC protocols that not only provide good end-to-end packet delay but can also quickly adapt to changes in the network topology due to vehicular mobility. In this article we outline a new framework for location- and delay-aware cross-layer communication that addresses these challenges. Our framework provides an efficient V2I data delivery system that relays packets over low-delay paths to a fixed base station or access point. Furthermore, an instance of this framework is also presented as a protocol. Our preliminary evaluations show that our design approach is promising, and provides delay predictability, fairness, and a good packet delivery ratio.

Investigating the Prospect of Leveraging Blockchain and Machine Learning to Secure Vehicular Networks: A Survey

Abstract: With recent developments in communication technologies, vehicular networks have become a reality with various applications. However, the cybersecurity aspect of vehicular networks is still an open issue that needs to be addressed with novel defence mechanisms against attacks. This paper first presents the state-of-the-art communication technologies in vehicular networks (either inter-vehicle networking or in-vehicle networking) along with their applications. Then we explore novel technologies including machine learning and blockchain as cybersecurity defence mechanisms in vehicular networks. Based on the extensive survey, we highlight some insights for future research to secure vehicular networks.

Is it possible to find social properties in vehicular networks

Abstract: Everyday, vehicles transit in a city and along their trajectories, they encounter other vehicles The frequency of these encounters is influenced by many factors, such as: vehicle speed, destinations, traffic conditions, and the period of the day However, these factors are justified by the public roads limits and the driver's behavior The people present daily routines and similar behaviors that have a great impact in the daily traffic evolution In this work, we present a numerical analysis of real and realistic data sets that describe the mobility of a set of vehicles Social metrics are computed, and the results obtained are compared to random graphs in the direction to verify if vehicular network presents a social behavior Finally, we discuss new social perspectives in vehicular networks

Study of Connectivity Probability of Vehicle-to-Vehicle and Vehicle-to-Infrastructure Communication Systems

Abstract: Considering the vehicular networks, multi-hop broadcasting is a frequently used method to deliver messages. Connectivity of wireless multi-hop networks is a critical measure for the planning, design, and evaluation of vehicular ad hoc networks. In an urban environment, vehicles can opportunistically exploit infrastructure through open Access Points (APs) and Road Side Units (RSUs) to efficiently communicate with other vehicles. Infrastructures (i.e., Base Stations (BSs), APs) are uniformly deployed along a road, while vehicles are distributed on the road randomly according to a Poisson distribution. For infrastructure-based vehicular networks, connectivity probability is the probability that an arbitrary vehicle access to the infrastructure. This paper proposes an analytical model to improve the connectivity probability of vehicle and infrastructure through multi-hop broadcasting in the infrastructure-based vehicular networks. We also consider the following factors: propagation distance, one hop transmission range, distribution of vehicles, vehicle density, average length of vehicles, and minimum safety distance between vehicles. The analytical model is validated by simulations.

FOX: A traffic management system of computer-based vehicles FOG

Abstract: Traffic congestion causes drivers' frustration and costs billions of dollars annually in lost time and fuel consumption. In order to overcome such issues, this paper presents a mechanism for Intelligent Transport Systems named FOX (Fast Offset XPath), which aims to detect and manage traffic congestion in Vehicular Ad hoc Networks. FOX is implemented in a FOG computing environment, taking advantage of the aspects inherent to this platform, such as scalability, low latency, the importance of geographical location and network conditions. The focus is to reduce the time to process, reroute and notify vehicles. Simulation results show that the proposed mechanism can reduce the average trip time, CO 2 emissions and fuel consumption. In particular, the average trip time was decreased approximately in 32%, the average fuel consumption in 14% and the stop time in 59%.