In this article, a general introduction to the area of sensor array and multichannel signal processing is provided, including associated activities of the IEEE Signal Processing Society (SPS) Sensor Array and Multichannel (SAM) Technical Committee (TC). The main technological advances in five SAM subareas made in the past 25 years are then presented in detail, including beamforming, direction-of-arrival (DOA) estimation, sensor location optimization, target/source localization based on sensor arrays, and multiple-input multiple-output (MIMO) arrays. Six recent developments are also provided at the end to indicate possible promising directions for future SAM research, which are graph signal processing (GSP) for sensor networks; tensor-based array signal processing, quaternion-valued array signal processing, 1-bit and noncoherent sensor array signal processing, machine learning and artificial intelligence (AI) for sensor arrays; and array signal processing for next-generation communication systems.

In this paper, we present the enhanced human driver model (EHDM), a time-continuous microscopic car-following model, which considers numerous characteristics attributable to the human driver. It is based on the popular intelligent driver model and the human driver model (HDM), a meta-model which enables the integration of human driving behavior into classical follow-the-leader models. We extend the HDM by adding variable, situation-dependent reaction times, different types of driver distraction, and driving errors to the model. Furthermore, we show that the EHDM provides a more thorough representation of human driving behavior compared with the HDM by performing dynamic traffic simulations and by validating both models with the aid of real-word vehicle data captured in an extensive field test.