MmWave System for Future ITS: A MAC-Layer Approach for V2X Beam Steering

Road-to-vehicle communication (RVC) system will support multiple services in future intelligent transportation systems (ITS). To meet different QoS requirements especially on delay, it is important to differentiate data frames of different applications. However the upcoming Northern American DSRC standard based on IEEE 802.11a specification uses legacy DCF MAC and it lacks support for different QoS which is crucial in future multi-service RVC system. In This work we analyze different QoS requirements of the various possible applications in ITS and propose to use enhanced DCF (EDCF) for future RVC systems to give QoS enhancement. Through simulation, we are sure EDCF is much more suitable for future typical ITS applications.

Backbone Technologies for the Exchange of Traffic and Travel Information

Great progress of technologies makes intelligent transportation system (ITS) services increasingly desirable. It becomes essential to seamlessly connecting to the Internet for accessing high quality Internet-enabled ITS services. In this context, gateway is recognized as the logical portal to the Internet. The efficiency of gateway regulation hence significantly sways the quality of ITS services. To seamlessly access the Internet in ITSs, a cloud-supported gateway model is proposed in this paper. Accordingly, the weighty load of gateway government, including gateway registration, discovery, selection, dispatching, and handoff, is offloaded from the clients to the appointed cloud servers. Numerical analyses and simulation results suggest that the gateway model proposed in this paper effectively improves the system performance in terms of the packet delivery rate, end-to-end delay, signaling overhead, and gateway connectivity; and, correspondingly enhances the usage experience of Internet-enabled ITS services.

Current transportation systems face great challenges due to the increasing mobility. Traffic accidents, congestion, air pollution, etc., are all calling for new methods to improve the transportation system. With the US legislation in progress over vehicle communications and EU’s finalization of the basic set of standards over cooperative intelligent transportation systems (C-ITS), vehicular ad hoc network (VANET) based applications are expected to address those challenges and provide solutions for a safer, more efficient and sustainable future intelligent transportation systems (ITS). In this chapter, transportation challenges are firstly summarized in respect of safety, efficiency, environmental threat, etc. A brief introduction of the VANET is discussed along with state of the art of VANET-based applications. Based on the current progress and the development trend of VANET, a number of new features of future VANET are identified, together with a set of potential future ITS applications. The on-going research and field operational test projects, which are the major enabling efforts for the future VANET-based C-ITS, are presented. The chapter is of great interest to readers working within ITS for current development status and future trend within the C-ITS area. It is also of interest to general public for an overview of the VANET enabled future transportation system.

Gigabit-per-second connectivity among vehicles is expected to be a key enabling technology for sensor information sharing, in turn, resulting in safer Intelligent Transportation Systems (ITSs). Recently proposed millimeter-wave (mmWave) systems appear to be the only solution capable of meeting the data rate demand imposed by future ITS services. In this poster, we assess the performance of a mmWave device-to-device (D2D) vehicular network by investigating the impact of system and communication parameters on end-users.

With the rapid maturation in automotive industry, intelligent sensing has been emerged as a vital research field for fast paced future intelligent transportation system. After the progressive integration of advanced driver assistance system and the rapid growth in next generation Internet of Vehicles (IoV), diver’s identification constitutes an indispensable aspect for the authorization in next generation internet-connected smart vehicles. Real-time driver identification is crucial in next generation smart vehicles. The presented solution is based on channel state information (CSI) of WiFi signals. In this proposed framework, an innovative WiFi- based low cost driver identification system is proposed which can recognize driver with good accuracy and less computational burden. The core idea is based on analyzing the steering wheel maneuver, exploiting CSI of WiFi signal. In the era of advanced information and communication in intelligent transportation system, this driver identification system may incorporate various intelligent means that are beneficial in many applications including safety, security, fleet management, ride hailing, insurance telematics, and customized vehicles. The proposed framework can recognize the activities with an average accuracy of 92.5% and identification with an average accuracy of 91.8%.

Optimizing traffic performance using artificial intelligence (AI) has consistently been a prominent direction in the development of intelligent transportation systems. While numerous studies have proposed methodologies for integrating cooperative connected and autonomous vehicles (CCAVs) with traffic signal systems via V2X communication, they often rely on simplified control strategies or lack effective coordination between signal timing and vehicle behavior. In this study, we propose a novel, integrated traffic signal control strategy combined with CAVs using deep reinforcement learning. Our key differentiation lies in the simultaneous optimization of signal phases using the Soft Actor–Critic (SAC) algorithm and the regulation of CCAVs via cooperative adaptive cruise control and Green Light Optimal Speed Advisory. This dual approach allows the signal controller to leverage rich state information from CAVs and the road infrastructure, enabling more anticipatory and cooperative decisions. The proposed approach is implemented and evaluated through various scenarios using the Simulation of Urban MObility (SUMO) platform. The results demonstrate the superior learning performance and robustness of the proposed model. Specifically, our proposed model achieves a significant reduction in average vehicle waiting time by up to over 80% compared to baseline models under high-demand scenarios (4800–6000 veh/h). These findings underscore the critical importance of joint optimization in future intelligent transportation systems, paving the way for more resilient urban traffic management.

Recent years have seen a more intensified deployment of Intelligent Transport Systems (ITS) in Polish cities. Work is also underway on the implementation of ITS on the national roads within the National Traffic Management System (KSZR). The research project RID-4D (part of Road Innovations), is designed to fill the gap, which is the lack of systematics of ITS services in Poland. The paper presents a proposal of ITS services systematics, which was developed based on an analysis of key international standards. FRAME architecture and American standards were the basis for the preparation of a standard scheme of ITS services. The results of the work on the KSZR architecture as well as local and regional architectures of urban systems were also taken into account.

Multimedia communications over vehicular ad hoc networks (VANET) will play an important role in the future intelligent transport system (ITS). QoS support for VANET therefore becomes an essential problem. In this paper, we first study the QoS performance in multi-hop VANET by using the standard IEEE 802.11e EDCA MAC and our proposed triple-constraint QoS routing protocol, Delay-Reliability-Hop (DeReHQ). In particular, we evaluate the DeReHQ protocol together with EDCA in highway and urban areas. Simulation results show that end-to-end delay performance can sometimes be achieved when both 802.11e EDCA and DeReHQ extended AODV are used. However, further studies on cross-layer optimization for QoS support in multi-hop environment are required.

The development of a mobile network to provide intelligent transport system (ITS) services is underway as a national project in Japan called the Smart Gateway, responding to nationwide needs for such a network. System issues for implementation include the necessity of measures for phased system expansion and efficient system maintenance. In addition, a data transmission method must be established to provide uninterrupted communication across microcells following radio signal environment changes to deliver information to fast-moving vehicles. To cope with these issues, this system uses an autonomous decentralized system architecture and supports online extendibility, online maintainability and fault tolerance that are critical to set up a system that operates non-stop. Thus, the authors developed microcell mobility management to enable uninterrupted communication across microcells. The authors developed a prototype incorporating the above methods and made an evaluation.

Vehicular communication is regarded as a backbone for the development of intelligent transportation system (ITS). Recently vehicular communication has attracted researchers from both academia and industry all over the world, notably, in the United States of America, Japan and European Union. The rapid advances in wireless technologies provide opportunities to utilize them in vehicular communication in advanced road safety applications. The most important feature of vehicular communication is to improve the road traffic safety, efficiency, comfort and quality of everyday road travel. Networking in particular and communication in general are important rudiments in the development of ITS. Generally, in vehicular communication, the information exchange occurs among vehicles not only in an ad-hoc based vehicle-to-vehicle networking but also in a vehicle-to-infrastructure with possible intermediate infrastructure-to-infrastructure networking. Therefore, the infrastructure plays major role in order to realize the full potential of vehicular communications. This chapter provides an in-depth survey of the infrastructures and technologies that are recently proposed as part of future ITS developments as well as tested for vehicular communications in mobile environment. Specifically, we provide an in-depth analysis of wireless technology-applications such as ad-hoc networking and wireless local area network (WLAN), dedicated short-range communication (DSRC), cellular technology and NOTICE Architecture, and compare their characteristics in terms of their abilities to support vehicular communications for development of ITS.

Understanding the demand for access information

The growth of technical revolution towards 5G Next generation networks is expected to meet various communication requirements of future Intelligent Transportation Systems (ITS). Motivated by the consumer needs for variety of ITS applications, bandwidth, high speed and ubiquity, researches are currently exploring different network architectures and techniques, which could be employed in Next generation ITS. To provide flexible network management, control and high resource utilization in Vehicular Ad-hoc Networks (VANETs) on large scale, a new hierarchical 5G Next generation VANET architecture is proposed. The key idea of this holistic architecture is to integrate the centralization and flexibility of Software Defined Networking (SDN) and Cloud-RAN (CRAN), with 5G communication technologies, to effectively allocate resources with a global view. Moreover, a fog computing framework (comprising of zones and clusters) has been proposed at the edge, to avoid frequent handovers between vehicles and RSUs. The transmission delay, throughput and control overhead on controller are analyzed and compared with other architectures. Simulation results indicate reduced transmission delay and minimized control overhead on controllers. Moreover, the throughput of proposed system is also improved.

Vehicular ad-hoc network (VANET) plays a significant role in future intelligent transportation systems. The main objective of vehicular ad hoc networks (VANETs) is to improve driver safety and traffic efficiency. Many researchers proposed different schemes to improve communication efficiency. It is quite challenging where vehicles’ speed, Direction, and density of neighbors on the move are not consistent. Although several routing protocols have been introduced to manage data exchange among vehicles in VANETS, they still suffer from many drawbacks such as lost packets or time penalties. This paper introduced a new Fog Based Routing Strategy, which constructs a reliable system of adaptive, stable, and efficient routing networks. FBRS consists of two main phases: System Setup Phase (SSP) and System Operation Phase (SOP). SSP creates a cluster network, collects its nodes’ data, mining routes between them, and ranking paths using Dijkstra’s algorithm into a simplified table. Although, SOP generates a reliable route between the request of any two nodes for a communication channel and maintains the route against any simultaneous crashes. Recent VANET routing protocols have been compared against FBRS. Experimental results have proven the outperforming of the proposed algorithm against recent routing protocols in terms of packet delivery ratio and routing overhead.

Integrity monitoring (IM) is essential if GNSS positioning technologies are to be fully trusted by future intelligent transport systems. A tighter and conservative stochastic model can shrink protection levels in the position domain and therefore enhance the user-level integrity. In this study, the stochastic models for vehicle-based GNSS positioning are refined in three respects: (1) Gaussian bounds of precise orbit and clock error products from the International GNSS Service are used; (2) a variable standard deviation to characterize the residual tropospheric delay after model correction is adopted; and (3) an elevation-dependent model describing the receiver-related errors is adaptively refined using least-squares variance component estimation. The refined stochastic models are used for positioning and IM under the Advanced Receiver Autonomous Integrity Monitoring (ARAIM) framework, which is considered the basis for multi-constellation GNSS navigation to support air navigation in the future. These refinements are assessed via global simulations and real data experiments. Different schemes are designed and tested to evaluate the corresponding enhancements on ARAIM availability for both aviation and ground vehicle-based positioning applications.