Street Smart in 5G : Vehicular Applications, Communication, and Computing

Recent advances in information technology have revolutionized the automotive industry, paving the way for next-generation smart vehicular mobility. Specifically, vehicles, roadside units, and other road users can collaborate to deliver novel services and applications that leverage, for example, big vehicular data and machine learning. Relatedly, fifth-generation cellular networks (5G) are being developed and deployed for low-latency, high-reliability, and high bandwidth communications. While 5G adjacent technologies such as edge computing allow for data offloading and computation at the edge of the network thus ensuring even lower latency and context-awareness. Overall, these developments provide a rich ecosystem for the evolution of vehicular applications, communications, and computing. Therefore in this work, we aim at providing a comprehensive overview of the state of research on vehicular computing in the emerging age of 5G and big data. In particular, this paper highlights several vehicular applications, investigates their requirements, details the enabling communication technologies and computing paradigms, and studies data analytics pipelines and the integration of these enabling technologies in response to application requirements.Peer reviewe

VANETs Signal Quality-based Route Selection in Smart Cities

In road networks, the most common metrics to determine the optimal route relaying two points are either the path length or the travel time. However, as autonomous smart cars are expected to emerge in future smart cities and lead to an unprecedented growth of mobile applications spectrum for both drivers and passengers, we argue that other metrics can be also considered for route selection. Therefore, the best route for a driver will be also determined by specific in-vehicle users' requirements such as, ensuring sufficient quality for wireless connection with minimum cost, and selecting preferred access networks, etc. To this end, we propose an original algorithm that enables route selection based on maximum expected signal quality with respect to the drivers' maximum tolerated prolongation of journey. Our ultimate objective is to select the route that ensures sufficient signal quality for users on board by maximizing the usage of VANETs resources, through RSUs, while minimizing the usage of the costly LTE-A resources. The obtained simulation results, under several scenarios, have proven the high efficiency of the proposed algorithm

Clustering and 5G-enabled smart cities: a survey of clustering schemes in VANETs

This chapter highlights the importance of Vehicular Ad-hoc Networks (VANETs) in the context of the 5Genabled smarter cities and roads, a topic that attracts significant interest. In order for VANETs and its associated applications to become a reality, a very promising avenue is to bring together multiple wireless technologies in the architectural design. 5G is envisioned to have a heterogeneous network architecture. Clustering is employed in designing optimal VANET architectures that successfully use different technologies, therefore clustering has the potential to play an important role in the 5G-VANET enabled solutions. This chapter presents a survey of clustering approaches in the VANET research area. The survey provides a general classification of the clustering algorithms, presents some of the most advanced and latest algorithms in VANETs, and it is among the fewest works in the literature that reviews the performance assessment of clustering algorithms

Dynamic multiagent method to avoid duplicated information at intersections in VANETs

Vehicular ad hoc networks (VANETs) allow vehicles to contact one another to provide safety and comfort applications. However, mobility is a great challenge in VANETs. High vehicle speed causes topological changes that result in unstable networks. Therefore, most previous studies focused on using clustering techniques in roads to reduce the effect of vehicle mobility and enhance network stability. Vehicles stop moving at intersections, and their mobility does not impact clustering. However, none of previous studies discussed the impact of vehicle stopping at intersections on base stations (BSs). Vehicles that have stopped moving at intersections continue to send the same information to BSs, which causes duplicated information. Hence, this study proposes a new method named dynamic multiagent (DMA) to filter cluster information and prevent duplicated information from being sent to BSs at intersections. The performance of the proposed method was evaluated through simulations during the use of DMA and without-DMA (W-DMA) methods based on real data collected from 10 intersections in Batu Pahat City, Johor, Malaysia. Overall, the proposed DMA method results in a considerable reduction in duplicated information at intersections, with an average percentage of 81% from the W-DMA method

Fog Connectivity Clustering and MDP Modeling for Software-defined Vehicular Networks

Intelligent and networked vehicles cooperate to create a mobile Cloud through vehicular Fog computing (VFC). Such clouds rely heavily on the underlying vehicular networks, so estimating communication resilience allows to address the problems caused by intermittent vehicle connectivity for data transfers. Individually estimating the communication stability of vehicles, nevertheless, undergoes incorrect predictions due to their particular mobility patterns. Therefore, we provide a region-oriented fog management model based on the connectivity through vehicular heterogeneous network environment via V2X and C-V2X. A fog management strategy dynamically monitors nearby vehicles to determine distinct regions in urban centres. The model enables a software-defined vehicular network (\Gls{SDVN}) controller to coordinate data flows. The vehicular connectivity described by our model assesses the potential for vehicle communication and conducts dynamic vehicle clustering. From the stochasticity of the environment, our model is based on Markov Decision Process (MDP), tracking the status of vehicle clusters and their potential for provisioning services. The model for vehicular clustering is supported by 5G and DSRC heterogeneous networks. Simulated analyses have shown the capability of our proposed model to estimate cluster reliability in real-time urban scenarios and support effective vehicular fog management

Vehicular Networks: A Survey on Architecture, Communication Technologies and Applications

The Intelligent Transportation System (ITS) provides wireless and mobile communication between vehicles and infrastructure to improve the safety of transportation and make the journey more enjoyable. This system consists of many fixed and mobile nodes (Vehicles, Trains, Vessels, Air planes), Wireless and Wired Telecommunication Technologies to exchange information between mobile nodes or between mobile nodes and fixed stations. The most common transportation tools are cars. Vehicular Ad-hoc Networks as an Application of Mobile Ad-hoc Networks and one of the subsets of Intelligent Transportation System provides wireless Ad-hoc communication between vehicles. VANET is a mobile wireless technology which is designed to improve safety of transportation with exchanging real time data between vehicles and providing different services to the users. It has special characteristics like high mobility and provides a broad range of services to the users, so it has been emerged as one of the research interests in the field of computer and telecommunication networks. In This paper we present different aspects of ITS and VANET to help the researchers to understand the Architecture, Communication Technologies and Applications of these networks

Role of smart vehicles concept in reducing traffic congestion on the road

The aim of this simple qualitative review was to provide an overview of how smart vehicles concept facilitates reducing traffic congestion on the road. Google Scholar was searched for literature sources using the topic itself as the search term. The search yielded 40 usable papers for this review. Many elements of smart city are inter-mixed with the smart vehicles concept. On the other hand in the smart vehicle concept, enabling technologies like VANET, IoV, SDN, use of mobiles and even use of electric poles on the road as IoT gateway were tested in the different frameworks proposed by different researchers. Many other traffic management systems have also been tested especially in Japan and India. In general, two scenarios have been considered-one of current types of roads and the other automated highways. Understandably, the requirements and approaches are different for the two scenarios. Some limitations of this review have also been listed at the end. Maximum of works dealt with VANET technolog

Traffic congestion prevention system

Transport is one of the key elements in the development of any country; it can be a powerful catalyst for economic growth. However, the infrastructure does not give enough to the huge number of vehicles which produces several problems, particularly in terms of road safety, and loss of time and pollution. One of the most significant problems is congestion, this is a major handicap for the road transport system. An alternative would be to use new technologies in the field of communication to send traffic information such as treacherous road conditions and accident sites by communicating, for a more efficient use of existing infrastructure.  In this paper, we present a CPS system, which can help drivers in order to have a better trip. For this raison we find the optimal way to reduce travel time and fuel consumption. This system based on our recent work [1]. It´s new approach aims to avoid congestion and queues, hat assure more efficient and optimal use of the existing road infrastructure. For that we concentrate by analyzing the useful and reliable traffic information collected in real time. The system is simulated in several conditions, Experimental result show that our approach is very effective. In the future work, we try to improve our system by adding more complexity in our system