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The recent development of integrated sensing and communications (ISAC) technology offers new opportunities to meet high-throughput and low-latency communication as well as high-resolution localization requirements in vehicular networks.…
Integrated Sensing and Communication (ISAC) technology plays a critical role in future intelligent transportation systems, by enabling vehicles to perceive and reconstruct the surrounding environment through reuse of wireless signals,…
Distributed Acoustic Sensing (DAS) technology is advancing seismic monitoring by providing dense observations near earthquake sources. However, the resulting data volumes often limit real-time processing capability, with most seismological…
Distributed Acoustic Sensing (DAS) using fiber optic cables is a promising new technology for pipeline monitoring and protection. In this work, we applied and compared two approaches for event detection using DAS: Classic machine learning…
Optical fiber sensing is a technology wherein audio, vibrations, and temperature are detected using an optical fiber; especially the audio/vibrations-aware sensing is called distributed acoustic sensing (DAS). In DAS, observed data, which…
Existing works mainly rely on the far-field planar-wave-based channel model to assess the performance of reconfigurable intelligent surface (RIS)-enabled wireless communication systems. However, when the transmitter and receiver are in…
Obtaining data on active travel activities such as walking, jogging, and cycling is important for refining sustainable transportation systems (STS). Effectively monitoring these activities not only requires sensing solutions to have a joint…
mmWave networks promise high bandwidth but face significant challenges in maintaining reliable connections for users moving at high speed. Frequent handovers, complex beam alignment, and signal blockage from car bodies lead to service…
In this paper, we propose sensing-assisted beamforming designs for vehicles on arbitrarily shaped roads by relying on integrated sensing and communication (ISAC) signalling.Specifically, we aim to address the limitations of conventional…
To date, VANET research efforts have relied heavily on simulations, due to prohibitive costs of deploying real world testbeds. Existing channel models implemented in discrete-event VANET simulators are by and large simple stochastic radio…
The technology of Shared Automated Vehicles (SAVs) has advanced significantly in recent years. However, existing SAV studies primarily focus on the system design while limited studies have examined the impacts of exogenous variables,…
This paper studies the physical layer security (PLS) of a vehicular network employing reconfigurable intelligent surfaces (RISs). RIS technologies are emerging as an important paradigm for the realisation of next-generation smart radio…
Ensuring traffic safety is crucial, which necessitates the detection and prevention of road surface defects. As a result, there has been a growing interest in the literature on the subject, leading to the development of various road surface…
Traffic congestion and violations pose significant challenges for urban mobility and road safety. Traditional traffic monitoring systems, such as fixed cameras and sensor-based methods, are often constrained by limited coverage, low…
Surface Acoustic Wave gas sensors have garnered increasing attention as highly sensitive, miniaturized, and wireless compatible platforms for molecular detection. Their unique ability to convert surface perturbations into measurable…
We introduce a recurrent neural network architecture for automated road surface wetness detection from audio of tire-surface interaction. The robustness of our approach is evaluated on 785,826 bins of audio that span an extensive range of…
Diffusing wave spectroscopy (DWS) can be employed as an optical rheology tool with numerous applications for studying the structure, dynamics and linear viscoelastic properties of complex fluids, foams, glasses and gels. To carry out DWS…
Sensor-based perception on vehicles are becoming prevalent and important to enhance the road safety. Autonomous driving systems use cameras, LiDAR, and radar to detect surrounding objects, while human-driven vehicles use them to assist the…
We present a framework for simulating realistic inverse synthetic aperture radar images of automotive targets at millimeter wave frequencies. The model incorporates radar scattering phenomenology of commonly found vehicles along with…
Evaluating the performance of autonomous vehicles (AV) and their complex subsystems to high precision under naturalistic circumstances remains a challenge, especially when failure or dangerous cases are rare. Rarity does not only require an…