Abstract
Intelligent transportation systems (ITSs) have become increasingly popular because they support effective coordination in connected vehicles. ITSs present an integrated approach for exchanging relevant information in order to improve the safety, efficiency, and reliability of road transportation systems. A variant of mobile ad-hoc networks (MANETs) called vehicular ad-hoc networks (VANETs) are an integral component of ITSs. VANETs consist of interconnected vehicles with sensing abilities that exchange information related to traffic, positioning, weather, and emergency services. In general, vehicle-to-everything (V2X) refers to communications between any entity and a vehicle, where the entity may be a vehicle, a cloud-based network, a pedestrian, or equipment installed along a road. One of the crucial challenges in V2X is the reliable and timely circulation of information among vehicular nodes to allow drivers to make decisions that increase road safety. In this context, efficient V2X routing protocols play a key role in supporting reliability and safety, and enhancing the overall quality of service (QoS) in VANETs. However, VANETs have distinct characteristics, such as high vehicular node mobility, unsteady connectivity, rapid changes in network topology, and unbounded network size, that can significantly affect routing in the network. Various routing protocols for V2X communication exist in the open technical literature. In this survey, we categorize the routing mechanisms as non-learning- and learning-based approaches, and discuss existing V2X routing protocols and their contributions to and impacts on VANET performance. Here, the learning-based approach implies the use of machine learning algorithms. This survey also summarizes open challenges in designing effective V2X routing protocols and future research directions to consider when developing smart routing mechanisms for next-generation intelligent VANET technologies.
Highlights
I NTELLIGENT transportation systems (ITSs) aim to provide learning-based innovative services for transportation and traffic management and enable more coordinated, safer, and ’smarter’ utilization of transport networks [1]–[3]
Contributions Selects nodes considering available bandwidth Designs geographic routing based on a spider model for urban Vehicular ad-hoc networks (VANETs) Divides urban spaces into multiple zones, where relay node selection is applied to forward packets An ant-based algorithm is used to discover the route with an optimum network connectivity Presents a comparison between position and geographical protocols, with the integration of mobility models and realistic physical layer Geographic routing protocols are investigated for multilevel VANET scenarios Analyzes the shortcomings of geographic routing Designs a beacon information independent routing that reduces the number of broadcasts and uses information collected from vehicles during previous attempts at route discoveries
Works focus on different directions, such as high node mobility, geographic and position-based routing, Software-defined networking (SDN)-based approaches, clustering, named data network-based approaches, intersectionbased distribution routing, quality of service (QoS), high vehicular speed, security and privacy, probabilistic routing, and congestion
Summary
I NTELLIGENT transportation systems (ITSs) aim to provide learning-based innovative services for transportation and traffic management and enable more coordinated, safer, and ’smarter’ utilization of transport networks [1]–[3]. Over the last few years, several works, such as [6], [33]–[49], have addressed the challenges of V2X routing and proposed routing protocols to improve road safety, security issues, and QoS by considering high mobility, irregular traffic patterns, frequent changes in network topology, and repeat exchanges of different types of information These routing protocols focus on discovering and maintaining routes between two VANET nodes using non-learning- or learning-based approaches. We study existing works that deal with non-learningbased routing protocols in V2X and highlight their contributions The impacts of such routing protocols on VANET performance are discussed in light of high node mobility, high vehicle speed, QoS improvement, network topology, security and privacy, etc. The AU is connected to the OBU using a wireless or wired connection and can reside with the OBU on a single physical unit
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