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This paper offers a technique for estimating collision risk for automated ground vehicles engaged in cooperative sensing. The technique allows quantification of (i) risk reduced due to cooperation, and (ii) the increased accuracy of risk…

Perception is a critical component of high-integrity applications of robotics and autonomous systems, such as self-driving vehicles. In these applications, failure of perception systems may put human life at risk, and a broad adoption of…

Communication between vehicles with varying degrees of automation is increasingly challenging as highly automated vehicles are unable to interpret the non-verbal signs of other road users. The lack of understanding on roads leads to lower…

With the increasing need to strengthen vehicle safety and detection, the availability of pre-existing methods of catching criminals and identifying vehicles manually through the various traffic surveillance cameras is not only…

In autonomous driving, perception systems are piv otal as they interpret sensory data to understand the envi ronment, which is essential for decision-making and planning. Ensuring the safety of these perception systems is fundamental for…

As IoT becomes omnipresent vast amounts of data are generated, which can be used for building innovative applications. However,interoperability issues and security concerns, prevent harvesting the full potentials of these data. In this…

This paper investigates runtime monitoring of perception systems. Perception is a critical component of high-integrity applications of robotics and autonomous systems, such as self-driving cars. In these applications, failure of perception…

Intelligent transportation systems (ITS) have revolutionized modern road infrastructure, providing essential functionalities such as traffic monitoring, road safety assessment, congestion reduction, and law enforcement. Effective vehicle…

Cooperative Adaptive Cruise Control (CACC) is an autonomous vehicle-following technology that allows groups of vehicles on the highway to form in tightly-coupled platoons. This is accomplished by exchanging inter-vehicle data through…

We propose a perception imitation method to simulate results of a certain perception model, and discuss a new heuristic route of autonomous driving simulator without data synthesis. The motivation is that original sensor data is not always…

Roadside perception systems are increasingly crucial in enhancing traffic safety and facilitating cooperative driving for autonomous vehicles. Despite rapid technological advancements, a major challenge persists for this newly arising…

Federated learning (FL) enables multiple participants to collaboratively train machine learning models while ensuring their data remains private and secure. Blockchain technology further enhances FL by providing stronger security, a…

In this paper, we study how to secure the platooning of autonomous vehicles when an unknown vehicle is under attack and bounded system uncertainties exist. For the attacked vehicle, its position and speed measurements from GPS can be…

To ensure safe operation of autonomous vehicles in complex urban environments, complete perception of the environment is necessary. However, due to environmental conditions, sensor limitations, and occlusions, this is not always possible…

Modern vehicles accumulate fragmented lifecycle records across OEMs, owners, and service centers that are difficult to verify and prone to fraud. We propose VehiclePassport, a GAIA-X-aligned digital passport anchored on blockchain with…

Cooperative perception offers several benefits for enhancing the capabilities of autonomous vehicles and improving road safety. Using roadside sensors in addition to onboard sensors increases reliability and extends the sensor range.…

Existing data collection methods for traffic operations and control usually rely on infrastructure-based loop detectors or probe vehicle trajectories. Connected and automated vehicles (CAVs) not only can report data about themselves but…

Federated learning combined with blockchain empowers secure data sharing in autonomous driving applications. Nevertheless, with the increasing granularity and complexity of vehicle-generated data, the lack of data quality audits raises…

Autonomous driving is a widely researched technology that is frequently tested on public roads. The data generated from these tests represent an essential competitive element for the respective companies moving this technology forward. In…

Zero Trust is the new cybersecurity model that challenges the traditional one by promoting continuous verification of users, devices, and applications, whatever their position or origin. This model is critical for reducing the attack…