Vehicular communication systems

About: Vehicular communication systems is a research topic. Over the lifetime, 2532 publications have been published within this topic receiving 64775 citations. The topic is also known as: V2V & vehicle-to-vehicle.

Risk analysis study of ITS communication architecture

Abstract: Intelligent Transportation Systems (ITS) are cooperative systems based on vehicular communications. They involve different actors like manufacturers, transportations authorities and users and enable diverse ITS applications to enhance safety in transportation systems. One of the ultimate design goals of ITS is to have a robust system that resists to various security attacks. Thus, security remains a major challenge before the deployment of such systems. In this paper, we present the ITS framework and communication architecture in Europe. Then, we identify inherent threats in this architecture. Finally, and using ETSI threat analysis methodology, we propose a risk analysis of ITS.

VACaMobil: VANET Car Mobility Manager for OMNeT++

Abstract: The performance of communication protocols in vehicular networks highly depends on the mobility pattern. Therefore, one of the most important issues when simulating this kind of protocols is how to properly model vehicular mobility. In this paper we present VACaMobil, a VANET Car Mobility Manager for the OMNeT++ simulator which allows researchers to completely define vehicular mobility by setting the desired average number of vehicles along with its upper and lower bounds. We compare VACaMobil against other common methods employed to generate vehicular mobility. Results clearly show the advantages of the VACaMobil tool when distributing vehicles in a real scenario, becoming one of the best mobility generators to evaluate the performance of different communication protocols and algorithms in VANET environments.

Vehicle-infrastructure integration (vii) and safety: rubber and radio meets the road in california

Abstract: Vehicle-Infrastructure Integration (VII), which embraces the concept of vehicle-roadside cooperative systems, has significant applications in Intelligent Transportation Systems (ITS). This article relates how the California Partners for Advanced Transit and Highways (PATH) is examining cooperative active safety systems, in which vehicle-vehicle and vehicle-roadside communications would inform other vehicles or the infrastructure about road conditions. Two projects sponsored by the California Department of Transportation (Caltrans) are currently underway at PATH. These include the Expedited VII (EVII) project which is studying the application of vehicles as traffic probes that would send data to a Traffic Management Center (TMC), and a slippery road warning system where vehicle sensors would transmit safety-critical messages indicating road surface conditions at curves. The second project involves developing, demonstrating and deploying VII technologies in a VII multi-modal, multi-application testbed in a key corridor in Northern California.

Fuzzy-Based Distributed Protocol for Vehicle-to-Vehicle Communication

Abstract: This article models the multihop data-routing in vehicular ad-hoc networks as multiple criteria decision making (MCDM) in four steps. First, the criteria that have impact on the performance of the network layer are captured and transformed into fuzzy sets. Second, the fuzzy sets are characterized by fuzzy membership functions (FMFs), which are interpolated (curve fitting) based on the data collected from massive experimental simulations. Third, the analytical hierarchy process (AHP) is exploited to identify the relationships among the criteria. Fourth, multiple fuzzy rules are determined and the Takagi–Sugeno–Kang (TSK) inference system is employed to infer and aggregate the final forwarding decision. Through integrating techniques of MCDM, FMF, AHP, and TSK, we design a distributed and opportunistic data routing protocol, namely, vehicular environment fuzzy router which targets vehicle-to-vehicle (V2V) communication and runs in two main processes—road segment selection (RSS) and relay vehicle selection (RVS). RSS is intended to select multiple successive junctions through which the packets should travel from the source to the destination, while RVS process is intended to select relay vehicles within the selected road segment. The experimental results show that our protocol performs and scales well with both network size and density, considering the combined problem of end-to-end packet delivery ratio and end-to-end latency.

Data-Driven Optimal Throughput Analysis for Route Selection in Cognitive Vehicular Networks

Abstract: To meet the dramatically increasing demands for vehicular communications, cognitive vehicular networks have been proposed to broaden the vehicular communication bandwidth by using cognitive radio technology. Meanwhile, the nationwide Super Wi-Fi project that allows the TV white space frequencies to be used for free, makes the concept of cognitive vehicular networks realistic. Recently, lots of technical issues of cognitive vehicular networks have been studied from the network designers' perspective, e.g., vehicular spectrum sensing and access, applications with different vehicular QoS, etc. Different from the existing works, in this paper, we consider from the vehicular users' perspective by optimizing throughput via route selection in cognitive vehicular networks using TV white space. By employing the attainable data rate as route selection metric, we propose two schemes: instantaneous route selection and long-term route selection. To evaluate the expected data rate on the route, we analyze the cognitive vehicular network throughput under two spectrum sharing models: spectrum overlay and spectrum underlay. In the experiments, we use Google spectrum dataset to estimate the intensity of TV base stations in the United States and evaluate the cognitive vehicular network throughput performance, which shows that the spectrum overlay model is more suitable for most of states in current United States, except New Jersey, Delaware and Utah. Moreover, we conduct a case study regarding the route I-88E and I-90E selection between Cortland and Schenectady in New York State. The traffic intensities and traffic intensity transition probabilities of these two routes are estimated using the real-world traffic volume dataset of New York State. Based on the estimated traffic information, we calculate the attainable instantaneous and long-term data rates of each vehicular user, which shows that route I-88E is preferable to route I-90E in most cases.