Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userSurvey of Spectrum Regulation for Intelligent Transportation Systems
145
0
0.0
(
0
)
Added by
Junsung Choi
Publication date
2020
fields
Informatics Engineering
and research's language is
English
Ask ChatGPT about the research
No Arabic abstract
As 5G communication technology develops, vehicular communications that require high reliability, low latency, and massive connectivity are drawing increasing interest from those in academia and industry. Due to these developing technologies, vehicular communication is not limited to vehicle components in the forms of Vehicle-to-Vehicle (V2V) or Vehicle-to-Infrastructure (V2I) networks, but has also been extended to connect with others, such as pedestrians and cellular users. Dedicated Short-Range Communications (DSRC) is the conventional vehicular communication standard for Intelligent Transportation Systems (ITS). More recently, the 3rd Generation Partnership Project introduced Cellular-Vehicle-to-Everything (C-V2X), a competitor to DSRC. Meanwhile, the Federal Communications Commission (FCC)issued a Notice of Proposed Rulemaking (NPRM) to consider deploying Unlicensed National Information Infrastructure (U-NII)devices in the ITS band with two interference mitigation approaches: Detect-and-Vacate (DAV)and Re-channelization (Re-CH). With multiple standard options and interference mitigation approaches, numerous regulatory taxonomies can be identified and notification of relevant technical challenges issued. However, these challenges are much broader than the current and future regulatory taxonomies pursued by the different countries involved. Because their plans differ, the technical and regulatory challenges vary. This paper presents a literature survey about the technical challenges, the current and future ITS band usage plans, and the major research testbeds for the U.S., Europe, China, Korea, and Japan. This survey shows that the most likely deployment taxonomies are (1) DSRC, C-V2X, and Wi-Fi with Re-CH; (2) DSRC and C-V2X with interoperation, and (3) C-V2X only. The most difficult technical challenge is the interoperability between the Wi-Fi-like DSRC and 4G LTE-like C-V2X.
rate research
Read More
The operation of future intelligent transportation systems (ITSs), communications infrastructure (CI), and power grids (PGs) will be highly interdependent. In particular, autonomous connected vehicles require CI resources to operate, and, thus, communication failures can result in non-optimality in the ITS flow in terms of traffic jams and fuel consumption. Similarly, CI components, e.g., base stations (BSs) can be impacted by failures in the electric grid that is powering them. Thus, malicious attacks on the PG can lead to failures in both the CI and the ITSs. To this end, in this paper, the security of an ITS against indirect attacks carried out through the PG is studied in an interdependent PG-CI-ITS scenario. To defend against such attacks, the administrator of the interdependent critical infrastructure can allocate backup power sources (BPSs) at every BS to compensate for the power loss caused by the attacker. However, due to budget limitations, the administrator must consider the importance of each BS in light of the PG risk of failure, while allocating the BPSs. In this regard, a rigorous analytical framework is proposed to model the interdependencies between the ITS, CI, and PG. Next, a one-to-one relationship between the PG components and ITS streets is derived in order to capture the effect of the PG components failure on the optimality of the traffic flow in the streets. Moreover, the problem of BPS allocation is formulated using a Stackelberg game framework and the Stackelberg equilibrium (SE) of the game is characterized. Simulation results show that the derived SE outperforms any other BPS allocation strategy and can be scalable in linear time with respect to the size of the interdependent infrastructure.
This paper reports a detailed experimental characterization of optical performances of Visible Light Communication (VLC) system using a real traffic light for ultra-low latency, infrastructure-to-vehicle (I2V) communications for intelligent transportation systems (ITS) protocols. Despite the implementation of long sought ITS protocols poses the crucial need to detail how the features of optical stages influence the overall performances of a VLC system in realistic configurations, such characterization has rarely been addressed at present. We carried out an experimental investigation in a realistic configuration where a regular traffic light (TX), enabled for VLC transmission, sends digital information towards a receiving stage (RX), composed by an optical condenser and a dedicated amplified photodiode stage. We performed a detailed measurements campaign of VLC performances encompassing a broad set of optical condensers, and for TX-RX distances in the range 3 - 50 m, in terms of both effective field of view (EFOV) and packet error rate (PER). The results show several nontrivial behaviors for different lens sets as a function of position on the measurement grid, highlighting critical aspects as well as identifying most suitable optical configurations depending on the specific application and on the required EFOV. In this paper we also provide a theoretical model for both the signal intensity and the EFOV as a function of several parameters, such as distance, RX orientation and focal length of the specific condenser. Our results could be very relevant in the near future to assess a most suited solution in terms of acceptance angle when designing a VLC system for real applications, where angle-dependent misalignment effects play a non-negligible role, and we argue that it could have more general implications with respect to the pristine I2V case mentioned here.
Fog computing has been advocated as an enabling technology for computationally intensive services in smart connected vehicles. Most existing works focus on analyzing the queueing and workload processing latencies associated with fog computing, ignoring the fact that wireless access latency can sometimes dominate the overall latency. This motivates the work in this paper, where we report on a five-month measurement study of the wireless access latency between connected vehicles and a fog/cloud computing system supported by commercially available LTE networks. We propose AdaptiveFog, a novel framework for autonomous and dynamic switching between different LTE networks that implement a fog/cloud infrastructure. AdaptiveFogs main objective is to maximize the service confidence level, defined as the probability that the latency of a given service type is below some threshold. To quantify the performance gap between different LTE networks, we introduce a novel statistical distance metric, called weighted Kantorovich-Rubinstein (K-R) distance. Two scenarios based on finite- and infinite-horizon optimization of short-term and long-term confidence are investigated. For each scenario, a simple threshold policy based on weighted K-R distance is proposed and proved to maximize the latency confidence for smart vehicles. Extensive analysis and simulations are performed based on our latency measurements. Our results show that AdaptiveFog achieves around 30% to 50% improvement in the confidence levels of fog and cloud latencies, respectively.
With the incoming introduction of 5G networks and the advancement in technologies, such as Network Function Virtualization and Software Defined Networking, new and emerging networking technologies and use cases are taking shape. One such technology is the Internet of Vehicles (IoV), which describes an interconnected system of vehicles and infrastructure. Coupled with recent developments in artificial intelligence and machine learning, the IoV is transformed into an Intelligent Transportation System (ITS). There are, however, several operational considerations that hinder the adoption of ITS systems, including scalability, high availability, and data privacy. To address these challenges, Federated Learning, a collaborative and distributed intelligence technique, is suggested. Through an ITS case study, the ability of a federated model deployed on roadside infrastructure throughout the network to recover from faults by leveraging group intelligence while reducing recovery time and restoring acceptable system performance is highlighted. With a multitude of use cases and benefits, Federated Learning is a key enabler for ITS and is poised to achieve widespread implementation in 5G and beyond networks and applications.
Cooperative Intelligent Transportation Systems (cITS) are a promising technology to enhance driving safety and efficiency. Vehicles communicate wirelessly with other vehicles and infrastructure, thereby creating a highly dynamic and heterogeneously managed ad-hoc network. It is these network properties that make it a challenging task to protect integrity of the data and guarantee its correctness. A major component is the problem that traditional security mechanisms like PKI-based asymmetric cryptography only exclude outsider attackers that do not possess key material. However, because attackers can be insiders within the network (i.e., possess valid key material), this approach cannot detect all possible attacks. In this survey, we present misbehavior detection mechanisms that can detect such insider attacks based on attacker behavior and information analysis. In contrast to well-known intrusion detection for classical IT systems, these misbehavior detection mechanisms analyze information semantics to detect attacks, which aligns better with highly application-tailored communication protocols foreseen for cITS. In our survey, we provide an extensive introduction to the cITS ecosystem and discuss shortcomings of PKI-based security. We derive and discuss a classification for misbehavior detection mechanisms, provide an in-depth overview of seminal papers on the topic, and highlight open issues and possible future research trends.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
