References of "IEEE Transactions on Vehicular Technology"
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See detailSafety-aware Location Privacy in VANET: Evaluation and Comparison
Emara, Karim Ahmed Awad El-Sayed UL

in IEEE Transactions on Vehicular Technology (in press)

VANET safety applications broadcast cooperative awareness messages (CAM) periodically to provide vehicles with continuous updates about the surrounding traffic. The periodicity and the spatiotemporal ... [more ▼]

VANET safety applications broadcast cooperative awareness messages (CAM) periodically to provide vehicles with continuous updates about the surrounding traffic. The periodicity and the spatiotemporal information contained in these messages allow a global adversary to track vehicle movements. Many privacy schemes have been proposed for VANET, but only few schemes consider their impact on safety applications. Also, each scheme is evaluated using inconsistent metrics and unrealistic vehicle traces, which makes comparing the actual performance of different schemes in the wild more difficult. In this paper, we aim to fill this gap and compare different privacy schemes not only in terms of the privacy gained but also their impact on safety applications. A distortion-based privacy metric is initially proposed and compared with other popular privacy metrics showing its effectiveness in measuring privacy. A practical safety metric which is based on Monte Carlo analysis is then proposed to measure the QoS of two safety applications: forward collision warning and lane change warning. Using realistic vehicle traces, six state-of-the-art VANET privacy schemes are evaluated and compared in terms of the proposed privacy and safety metrics. Among the evaluated schemes, it was found that the coordinated silent period scheme achieves the best privacy and QoS levels but fully synchronized silence among all vehicles is a practical challenge. The CAPS and CADS schemes provide a practical compromise between privacy and safety since they employ only the necessary silence periods to prevent tracking and avoid changing pseudonyms in trivial situations. [less ▲]

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See detailArchitectures and Key Technical Challenges for 5G Systems Incorporating Satellites
Giudotti, A.; Vanelli-Coralli, A.; Conti, M. et al

in IEEE Transactions on Vehicular Technology (2018)

Satellite Communication systems are a promising solution to extend and complement terrestrial networks in unserved or under-served areas. This aspect is reflected by recent commercial and standardisation ... [more ▼]

Satellite Communication systems are a promising solution to extend and complement terrestrial networks in unserved or under-served areas. This aspect is reflected by recent commercial and standardisation endeavours. In particular, 3GPP recently initiated a Study Item for New Radio-based, i.e., 5G, Non-Terrestrial Networks aimed at deploying satellite systems either as a stand-alone solution or as an integration to terrestrial networks in mobile broadband and machine-type communication scenarios. However, typical satellite channel impairments, as large path losses, delays, and Doppler shifts, pose severe challenges to the realisation of a satellite-based NR network. In this paper, based on the architecture options currently being discussed in the standardisation fora, we discuss and assess the impact of the satellite channel characteristics on the physical and Medium Access Control layers, both in terms of transmitted waveforms and procedures for enhanced Mobile BroadBand (eMBB) and NarrowBand-Internet of Things (NB-IoT) applications. The proposed analysis shows that the main technical challenges are related to the PHY/MAC procedures, in particular Random Access (RA), Timing Advance (TA), and Hybrid Automatic Repeat reQuest (HARQ) and, depending on the considered service and architecture, different solutions are proposed. [less ▲]

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See detailRecent Trends in Driver Safety Monitoring Systems: State of the Art and Challenges
Koesdwiady, Arief; Soua, Ridha UL; Karray, Fakhri et al

in IEEE Transactions on Vehicular Technology (2017), 66(6), 4550-4563

Driving in busy highways and roads is becoming complex and challenging, as more cars are hitting the roads. Safe driving requires attentive drivers, quality perception of the environment, awareness of the ... [more ▼]

Driving in busy highways and roads is becoming complex and challenging, as more cars are hitting the roads. Safe driving requires attentive drivers, quality perception of the environment, awareness of the situation, and critical decision making to react properly in emergency situations. This paper provides an overview on driver safety monitoring systems. We study various driver sources of inattention while providing a comprehensive taxonomy. Then, different safety systems that tackle driver inattention are reported. Furthermore, we present the new generation of driver monitoring systems within the context of Internet of Cars. Thus, we introduce the concept of integrated safety, where smart cars collect information from the driver, the car, the road, and, most importantly, the surrounding cars to build an efficient environment for the driver. We conclude by highlighting issues and emerging trends envisioned by the research community [less ▲]

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See detailCharacterizing the Topology of an Urban Wireless Sensor Network for Road Traffic Management
Faye, Sébastien UL; Chaudet, Claude

in IEEE Transactions on Vehicular Technology (2016), 65(7), 5720-5725

In a near future, wireless networks will be one of the key technologies for road traffic management in smart cities. Vehicles and dedicated roadside units should be interconnected through wireless ... [more ▼]

In a near future, wireless networks will be one of the key technologies for road traffic management in smart cities. Vehicles and dedicated roadside units should be interconnected through wireless technologies such as IEEE 802.11p (WAVE). Traffic light and road signs may also take their place in this architecture, forming a large-scale network of small devices that report measurements, take orders from a control center, and are able to take decisions autonomously based on their local perception. Such a network shares many similarities with classical wireless sensor and actuator networks, starting with its distributed organization and with the role of the control center. However, its topology, and subsequently the appropriate selection of protocols and algorithms, will be strongly influenced by each city's characteristics. In this article, we characterize and discuss probable topologies of these networks. The aim of this work is to provide network models that can be used to evaluate protocols and algorithms using realistic scenarios in place of generic random graphs. We deploy such networks over 52 city maps extracted from OpenStreetMap and characterize the resulting graphs, with a particular focus on connectivity aspects (degree distribution and connected components). The tools, the complete datasets, OMNeT++ network models are available freely online. [less ▲]

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See detailEigenvalue Based Sensing and SNR Estimation for Cognitive Radio in Presence of Noise Correlation
Sharma, Shree Krishna UL; Chatzinotas, Symeon UL; Ottersten, Björn UL

in IEEE Transactions on Vehicular Technology (2013), 62(8), 3671-3684

Herein, we present a detailed analysis of an eigenvalue based sensing technique in the presence of correlated noise in the context of a Cognitive Radio (CR). We use a Standard Condition Number (SCN) based ... [more ▼]

Herein, we present a detailed analysis of an eigenvalue based sensing technique in the presence of correlated noise in the context of a Cognitive Radio (CR). We use a Standard Condition Number (SCN) based decision statistic based on asymptotic Random Matrix Theory (RMT) for decision process. Firstly, the effect of noise correlation on eigenvalue based Spectrum Sensing (SS) is studied analytically under both the noise only and the signal plus noise hypotheses. Secondly, new bounds for the SCN are proposed for achieving improved sensing in correlated noise scenarios. Thirdly, the performance of Fractional Sampling (FS) based SS is studied and a method for determining the operating point for the FS rate in terms of sensing performance and complexity is suggested. Finally, a Signal to Noise Ratio (SNR) estimation technique based on the maximum eigenvalue of the received signal’s covariance matrix is proposed. It is shown that proposed SCN-based threshold improves sensing performance in correlated noise scenarios and SNRs up to 0 dB can be reliably estimated with less than 1 % normalized Mean Square Error (MSE) in the presence of correlated noise without the knowledge of noise variance. [less ▲]

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See detail3D Skeleton based Head Detection and Tracking using Range Images
Devarakota, Pandu UL; Castillo-Franco, Marta; Ginhoux, Romuald et al

in IEEE Transactions on Vehicular Technology (2009), 58(8), 4064-4077

Vision-based 3-D head detection and tracking systems have been studied in several applications like video surveillance, face-detection systems, and occupant posture analysis. In this paper, we present the ... [more ▼]

Vision-based 3-D head detection and tracking systems have been studied in several applications like video surveillance, face-detection systems, and occupant posture analysis. In this paper, we present the development of a topology-based framework using a 3-D skeletal model for the robust detection and tracking of a vehicle occupant's head position from low-resolution range image data for a passive safety system. Unlike previous approaches to head detection, the proposed approach explores the topology information of a scene to detect the position of the head. Among the different available topology representations, the Reeb graph technique is chosen and is adapted to low-resolution 3-D range images. Invariance of the graph under rotations is achieved by using a Morse radial distance function. To cope with the particular challenges such as the noise and the large variations in the density of the data, a voxel neighborhood connectivity notion is proposed. A multiple-hypothesis tracker (MHT) with nearest-neighbor data association and Kalman filter prediction is applied on the endpoints of the Reeb graph to select and filter the correct head candidate out of Reeb graph endpoints. A systematic evaluation of the head detection framework is carried out on full-scale experimental 3-D range images and compared with the ground truth. It is shown that the Reeb graph topology algorithm developed herein allows the correct detection of the head of the occupant with only two head candidates as input to the MHT. Results of the experiments demonstrate that the proposed framework is robust under the large variations of the scene. The processing requirements of the proposed approach are discussed. It is shown that the number of operations is rather low and that real-time processing requirements can be met with the proposed method. [less ▲]

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