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Understanding occupant-vehicle interactions by modeling control transitions is important to ensure safe approaches to passenger vehicle automation. Models which contain contextual, semantically meaningful representations of driver states…
Understanding human driving behavior is crucial to develop autonomous vehicles' algorithms. However, most low level automation, such as the one in advanced driving assistance systems (ADAS), is based on objective safety measures, which are…
Lacking security awareness, sensor fusion in systems with multi-agent networks such as smart cities is vulnerable to attacks. To guard against recent threats, we design security-aware sensor fusion that is based on the estimates of…
Connected and automated vehicles (CAVs) have attracted more and more attention recently. The fast actuation time allows them having the potential to promote the efficiency and safety of the whole transportation system. Due to technical…
This paper introduces a novel approach to tackle the challenges of preserving and transferring tacit knowledge--deep, experience-based insights that are hard to articulate but vital for decision-making, innovation, and problem-solving.…
As autonomous driving technology evolves, ensuring the stability and safety of Autonomous Driving Systems (ADS) through alignment with human values becomes increasingly crucial. While existing research emphasizes the adherence of AI to…
Novice pilots find it difficult to operate and land unmanned aerial vehicles (UAVs), due to the complex UAV dynamics, challenges in depth perception, lack of expertise with the control interface and additional disturbances from the ground…
Noise robustness is critical when applying automatic speech recognition (ASR) in real-world scenarios. One solution involves the used of speech enhancement (SE) models as the front end of ASR. However, neural network-based (NN-based) SE…
Transient stability assessment is a critical tool for power system design and operation. With the emerging advanced synchrophasor measurement techniques, machine learning methods are playing an increasingly important role in power system…
Can drivers' situation awareness during automated driving be maintained using haptic cues that provide information about road and traffic scenarios while the drivers are engaged in a secondary task? And can this be done without disengaging…
Driver drowsiness is one of the main causes of road accidents and is recognized as a leading contributor to traffic-related fatalities. However, detecting drowsiness accurately remains a challenging task, especially in real-world settings…
Significant progress has been made in anomaly detection and run-time monitoring to improve the safety and security of cyber-physical systems (CPS). However, less attention has been paid to hazard mitigation. This paper proposes a combined…
Understanding passenger intents and extracting relevant slots are important building blocks towards developing contextual dialogue systems for natural interactions in autonomous vehicles (AV). In this work, we explored AMIE…
This paper offers a formal framework for the rare collision risk estimation of autonomous vehicles (AVs) with multi-agent situation awareness, affected by different sources of noise in a complex dynamic environment. In our proposed setting,…
Despite the continual advances in Advanced Driver Assistance Systems (ADAS) and the development of high-level autonomous vehicles (AV), there is a general consensus that for the short to medium term, there is a requirement for a human…
In-vehicle sensing technology has gained tremendous attention due to its ability to support major technological developments, such as connected vehicles and self-driving cars. In-vehicle sensing data are invaluable and important data…
The investigation of factors contributing at making humans trust Autonomous Vehicles (AVs) will play a fundamental role in the adoption of such technology. The user's ability to form a mental model of the AV, which is crucial to establish…
Compared to a manual driving vehicle (MV), an automated driving vehicle lacks a way to communicate with the pedestrian through the driver when it interacts with the pedestrian because the driver usually does not participate in driving…
Many research papers have recently focused on behavioral-based driver authentication systems in vehicles. Pushed by Artificial Intelligence (AI) advancements, these works propose powerful models to identify drivers through their unique…
This paper investigates the passive detection problem in multi-static integrated sensing and communication (ISAC) systems, where multiple sensing receivers (SRs) jointly detect a target using random unknown communication signals transmitted…