Time division multiple access scheduling strategies for emerging vehicular ad hoc network medium access control protocols: a survey

[EN] Vehicular ad hoc network (VANET) is an emerging and promising technology, which allows vehicles while moving on the road to communicate and share resources. These resources are aimed at improving traffic safety and providing comfort to drivers and passengers. The resources use applications that have to meet high reliability and delay constraints. However, to implement these applications, VANET relies on medium access control (MAC) protocol. Many approaches have been proposed in the literature using time division multiple access (TDMA) scheme to enhance the efficiency of MAC protocol. Nevertheless, this technique has encountered some challenges including access and merging collisions due to inefficient time slot allocation strategy and hidden terminal problem. Despite several attempts to study this class of protocol, issues such as channel access and time slot scheduling strategy have not been given much attention. In this paper, we have relatively examined the most prominent TDMA MAC protocols which were proposed in the literature from 2010 to 2018. These protocols were classified based on scheduling strategy and the technique adopted. Also, we have comparatively analyzed them based on different parameters and performance metrics used. Finally, some open issues are presented for future deployment.Tambawal, AB.; Noor, RM.; Salleh, R.; Chembe, C.; Anisi, MH.; Michael, O.; Lloret, J. (2019). Time division multiple access scheduling strategies for emerging vehicular ad hoc network medium access control protocols: a survey. Telecommunication Systems. 70(4):595-616. https://doi.org/10.1007/s11235-018-00542-8S59561670

Vehicular Fog Computing Enabled Real-time Collision Warning via Trajectory Calibration

Vehicular fog computing (VFC) has been envisioned as a promising paradigm for enabling a variety of emerging intelligent transportation systems (ITS). However, due to inevitable as well as non-negligible issues in wireless communication, including transmission latency and packet loss, it is still challenging in implementing safety-critical applications, such as real-time collision warning in vehicular networks. In this paper, we present a vehicular fog computing architecture, aiming at supporting effective and real-time collision warning by offloading computation and communication overheads to distributed fog nodes. With the system architecture, we further propose a trajectory calibration based collision warning (TCCW) algorithm along with tailored communication protocols. Specifically, an application-layer vehicular-to-infrastructure (V2I) communication delay is fitted by the Stable distribution with real-world field testing data. Then, a packet loss detection mechanism is designed. Finally, TCCW calibrates real-time vehicle trajectories based on received vehicle status including GPS coordinates, velocity, acceleration, heading direction, as well as the estimation of communication delay and the detection of packet loss. For performance evaluation, we build the simulation model and implement conventional solutions including cloud-based warning and fog-based warning without calibration for comparison. Real-vehicle trajectories are extracted as the input, and the simulation results demonstrate that the effectiveness of TCCW in terms of the highest precision and recall in a wide range of scenarios

Optimization of vehicular networks in smart cities: from agile optimization to learnheuristics and simheuristics

Vehicular ad hoc networks (VANETs) are a fundamental component of intelligent transportation systems in smart cities. With the support of open and real-time data, these networks of inter-connected vehicles constitute an ‘Internet of vehicles’ with the potential to significantly enhance citizens’ mobility and last-mile delivery in urban, peri-urban, and metropolitan areas. However, the proper coordination and logistics of VANETs raise a number of optimization challenges that need to be solved. After reviewing the state of the art on the concepts of VANET optimization and open data in smart cities, this paper discusses some of the most relevant optimization challenges in this area. Since most of the optimization problems are related to the need for real-time solutions or to the consideration of uncertainty and dynamic environments, the paper also discusses how some VANET challenges can be addressed with the use of agile optimization algorithms and the combination of metaheuristics with simulation and machine learning methods. The paper also offers a numerical analysis that measures the impact of using these optimization techniques in some related problems. Our numerical analysis, based on real data from Open Data Barcelona, demonstrates that the constructive heuristic outperforms the random scenario in the CDP combined with vehicular networks, resulting in maximizing the minimum distance between facilities while meeting capacity requirements with the fewest facilities.Peer ReviewedPostprint (published version

A Survey on platoon-based vehicular cyber-physical systems

Vehicles on the road with some common interests can cooperatively form a platoon-based driving pattern, in which a vehicle follows another one and maintains a small and nearly constant distance to the preceding vehicle. It has been proved that, compared to driving individually, such a platoon-based driving pattern can significantly improve the road capacity and energy efficiency. Moreover, with the emerging vehicular adhoc network (VANET), the performance of platoon in terms of road capacity, safety and energy efficiency, etc., can be further improved. On the other hand, the physical dynamics of vehicles inside the platoon can also affect the performance of VANET. Such a complex system can be considered as a platoon-based vehicular cyber-physical system (VCPS), which has attracted significant attention recently. In this paper, we present a comprehensive survey on platoon-based VCPS. We first review the related work of platoon-based VCPS. We then introduce two elementary techniques involved in platoon-based VCPS: the vehicular networking architecture and standards, and traffic dynamics, respectively. We further discuss the fundamental issues in platoon-based VCPS, including vehicle platooning/clustering, cooperative adaptive cruise control (CACC), platoon-based vehicular communications, etc., and all of which are characterized by the tight coupled relationship between traffic dynamics and VANET behaviors. Since system verification is critical to VCPS development, we also give an overview of VCPS simulation tools. Finally, we share our view on some open issues that may lead to new research directions

Advances in Intelligent Vehicle Control

This book is a printed edition of the Special Issue Advances in Intelligent Vehicle Control that was published in the journal Sensors. It presents a collection of eleven papers that covers a range of topics, such as the development of intelligent control algorithms for active safety systems, smart sensors, and intelligent and efficient driving. The contributions presented in these papers can serve as useful tools for researchers who are interested in new vehicle technology and in the improvement of vehicle control systems

DESIGN OF EFFICIENT IN-NETWORK DATA PROCESSING AND DISSEMINATION FOR VANETS

By providing vehicle-to-vehicle and vehicle-to-infrastructure wireless communications, vehicular ad hoc networks (VANETs), also known as the “networks on wheels”, can greatly enhance traffic safety, traffic efficiency and driving experience for intelligent transportation system (ITS). However, the unique features of VANETs, such as high mobility and uneven distribution of vehicular nodes, impose critical challenges of high efficiency and reliability for the implementation of VANETs. This dissertation is motivated by the great application potentials of VANETs in the design of efficient in-network data processing and dissemination. Considering the significance of message aggregation, data dissemination and data collection, this dissertation research targets at enhancing the traffic safety and traffic efficiency, as well as developing novel commercial applications, based on VANETs, following four aspects: 1) accurate and efficient message aggregation to detect on-road safety relevant events, 2) reliable data dissemination to reliably notify remote vehicles, 3) efficient and reliable spatial data collection from vehicular sensors, and 4) novel promising applications to exploit the commercial potentials of VANETs. Specifically, to enable cooperative detection of safety relevant events on the roads, the structure-less message aggregation (SLMA) scheme is proposed to improve communication efficiency and message accuracy. The scheme of relative position based message dissemination (RPB-MD) is proposed to reliably and efficiently disseminate messages to all intended vehicles in the zone-of-relevance in varying traffic density. Due to numerous vehicular sensor data available based on VANETs, the scheme of compressive sampling based data collection (CS-DC) is proposed to efficiently collect the spatial relevance data in a large scale, especially in the dense traffic. In addition, with novel and efficient solutions proposed for the application specific issues of data dissemination and data collection, several appealing value-added applications for VANETs are developed to exploit the commercial potentials of VANETs, namely general purpose automatic survey (GPAS), VANET-based ambient ad dissemination (VAAD) and VANET based vehicle performance monitoring and analysis (VehicleView). Thus, by improving the efficiency and reliability in in-network data processing and dissemination, including message aggregation, data dissemination and data collection, together with the development of novel promising applications, this dissertation will help push VANETs further to the stage of massive deployment

TDMA-based MAC Protocols for Vehicular Ad Hoc Networks: A Survey, Qualitative Analysis and Open Research Issues

International audience—Vehicular Ad-hoc NETworks (VANETs) have attracted a lot of attention in the research community in recent years due to their promising applications. VANETs help improve traffic safety and efficiency. Each vehicle can exchange information to inform other vehicles about the current status of the traffic flow or a dangerous situation such as an accident. Road safety and traffic management applications require a reliable communication scheme with minimal transmission collisions, which thus increase the need for an efficient Medium Access Control (MAC) protocol. However, the design of the MAC in a vehicular network is a challenging task due to the high speed of the nodes, the frequent changes in topology, the lack of an infrastructure, and various QoS requirements. Recently several Time Division Multiple Access (TDMA)-based medium access control protocols have been proposed for VANETs in an attempt to ensure that all the vehicles have enough time to send safety messages without collisions and to reduce the end-to-end delay and the packet loss ratio. In this paper, we identify the reasons for using the collision-free medium access control paradigm in VANETs. We then present a novel topology-based classification and we provide an overview of TDMA-based MAC protocols that have been proposed for VANETs. We focus on the characteristics of these protocols, as well as on their benefits and limitations. Finally, we give a qualitative comparison, and we discuss some open issues that need to be tackled in future studies in order to improve the performance of TDMA-based MAC protocols for vehicle to vehicle (V2V) communications

Infrastructure-Assisted Message Dissemination for Supporting Heterogeneous Driving Patterns

With the advances of Internet of Things technologies, individual vehicles can now exchange information to improve traffic safety, and some vehicles can further improve safety and efficiency by coordinating their mobility via cooperative driving. To facilitate these applications, many studies have been focused on the design of inter-vehicle message dissemination protocols. However, most existing designs either assume individual driving pattern or consider cooperative driving only. Moreover, few of them fully exploit infrastructures, such as cameras, sensors, and road-side units. In this paper, we address the design of message dissemination that supports heterogeneous driving patterns. Specifically, we first propose an infrastructure-assisted message dissemination framework that can utilize the capability of infrastructures. We then present a novel beacon scheduling algorithm that aims at guaranteeing the timely and reliable delivery of both periodic beacon messages for cooperative driving and event-triggered safety messages for individual driving. To evaluate the performance of the protocol, we develop both theoretical analysis and simulation experiments. Extensive numerical results confirm the effectiveness of the proposed protocol

A self-learning intersection control system for connected and automated vehicles

This study proposes a Decentralized Sparse Coordination Learning System (DSCLS) based on Deep Reinforcement Learning (DRL) to control intersections under the Connected and Automated Vehicles (CAVs) environment. In this approach, roadway sections are divided into small areas; vehicles try to reserve their desired area ahead of time, based on having a common desired area with other CAVs; the vehicles would be in an independent or coordinated state. Individual CAVs are set accountable for decision-making at each step in both coordinated and independent states. In the training process, CAVs learn to minimize the overall delay at the intersection. Due to the chain impact of taking random actions in the training course, the trained model can deal with unprecedented volume circumstances, the main challenge in intersection management. Application of the model to a single-lane intersection with no turning movement as a proof-of-concept test reveals noticeable improvements in traffic measures compared to three other intersection control systems. A Spring Mass Damper (SMD) model is developed to control platooning behavior of CAVs. In the SMD model, each vehicle is assumed as a mass, coupled with its preceding vehicle with a spring and a damper. The spring constant and damper coefficient control the interaction between vehicles. Limitations on communication range and the number of vehicles in each platoon are applied in this model, and the SMD model controls intra-platoon and inter-platoon interactions. The simulation result for a regular highway section reveals that the proposed platooning algorithm increases the maximum throughput by 29% and 63% under 50% and 100% market penetration rate of CAVs. A merging section with different volume combinations on the main section and merging section and different market penetration rates of CAVs is also modeled to test inter-platoon spacing performance in accommodating merging vehicles. Noticeable travel time reduction is observed in both mainline and merging lanes and under all volume combinations in 80% and higher MPR of CAVs. For a more reliable assessment of the DSCLS, the model is applied to a more realistic intersection, including three approaching lanes in each direction and turning movements. The proposed algorithm decreases delay by 58%, 19%, and 13% in moderate, high, and extreme volume regimes, improving travel time accordingly. Comparison of safety measures reveals 28% improvement in Post Encroachment Time (PET) in the extreme volume regime and minor improvements in high and moderate volume regimes. Due to the limited acceleration and deceleration rates, the proposed model does not show a better performance in environmental measures, including fuel consumption and CO2 emission, compared to the conventional control systems. However, the DSCLS noticeably outperforms the other pixel-reservation counterpart control system, with limited acceleration and deceleration rates. The application of the model to a corridor of four interactions shows the same trends in traffic, safety, and environmental measures as the single intersection experiment. An automated intersection control system for platooning CAVs is developed by combining the two proposed models, which remarkably improves traffic and safety measures, specifically in extreme volume regimes compared to the regular DSCLS model

Cloud Computing in VANETs: Architecture, Taxonomy, and Challenges

Cloud Computing in VANETs (CC-V) has been investigated into two major themes of research including Vehicular Cloud Computing (VCC) and Vehicle using Cloud (VuC). VCC is the realization of autonomous cloud among vehicles to share their abundant resources. VuC is the efficient usage of conventional cloud by on-road vehicles via a reliable Internet connection. Recently, number of advancements have been made to address the issues and challenges in VCC and VuC. This paper qualitatively reviews CC-V with the emphasis on layered architecture, network component, taxonomy, and future challenges. Specifically, a four-layered architecture for CC-V is proposed including perception, co-ordination, artificial intelligence and smart application layers. Three network component of CC-V namely, vehicle, connection and computation are explored with their cooperative roles. A taxonomy for CC-V is presented considering major themes of research in the area including design of architecture, data dissemination, security, and applications. Related literature on each theme are critically investigated with comparative assessment of recent advances. Finally, some open research challenges are identified as future issues. The challenges are the outcome of the critical and qualitative assessment of literature on CC-V