Data-driven Semi-supervised Machine Learning with Surrogate Safety Measures for Abnormal Driving Behavior Detection

Detecting abnormal driving behavior is critical for road traffic safety and the evaluation of drivers' behavior. With the advancement of machine learning (ML) algorithms and the accumulation of naturalistic driving data, many ML models have been adopted for abnormal driving behavior detection. Most existing ML-based detectors rely on (fully)...

Editorial: Noise and vibrations in offshore wind farms and their impact on aquatic species

Multimode diagnosis for switched affine systems with noisy measurement

We study a diagnosis scheme to reliably detect the active mode of discrete-time, switched affine systems in the presence of measurement noise and asynchronous switching. The proposed scheme consists of two parts: (i) the construction of a bank of filters, and (ii) the introduction of a residual/threshold-based diagnosis rule. We develop an...

Relational model of accidents and vessel traffic using AIS Data and GIS: A case study of the Western port of Shenzhen City

Following the growth in global trade activities, vessel traffic has increased dramatically in some busy waterways and ports. However, such increments have made it more complex to manage the regional vessel traffic, which can increase the risk of an accident in the area. To model and analyze the relationship between vessel traffic and maritime...

Metrology for Inductive Charging of Electric Vehicles (MICEV)

The European Union funded project MICEV aims at improving the traceability of electrical and magnetic measurement at charging stations and to better assess the safety of this technology with respect to human exposure. The paper describes some limits of the instrumentation used for electrical measurements in the charging stations, and briefly...