Feature Papers in Vehicular Sensing.

This Special Issue compiles papers submitted by the Editorial Board Members of the Vehicular Sensing Section and outstanding scholars in this field. Thus, this paper proposes a deep learning approach, which consists of a two-stage process using an autoencoder and long short-term memory, to detect anomalies in electrical power steering sensor data. The presented topics range from physical models and components to advanced control systems for automated vehicles, including driver monitoring, comfort considerations, communication and cooperative systems, perception sensors and solutions to issues related to electric vehicles. The authors test these types of sensors under different weather conditions and employ fake targets between the sensor and the tracked vehicle. [Extracted from the article]