Recent substantial advancements in computational techniques, particularly in artificial
intelligence (AI) and machine learning (ML), have raised the demand for smart self-powered …

This contribution provides a review of fundamental goals, development and future
perspectives of driver assistance systems. Mobility is a fundamental desire of mankind …

In this paper, we provide a survey of the traffic sign detection literature, detailing detection
systems for traffic sign recognition (TSR) for driver assistance. We separately describe the …

In this paper the various driving style analysis solutions are investigated. An in-depth
investigation is performed to identify the relevant machine learning and artificial intelligence …

Anticipating the future actions of a human is a widely studied problem in robotics that
requires spatio-temporal reasoning. In this work we propose a deep learning approach for …

Abstract We propose a Dynamic-Spatial-Attention (DSA) Recurrent Neural Network (RNN)
for anticipating accidents in dashcam videos (Fig. 1). Our DSA-RNN learns to (1) distribute …

In this paper, we study how to test the intelligence of an autonomous vehicle.
Comprehensive testing is crucial to both vehicle manufactories and customers. Existing …

Visual surveillance of dynamic objects, particularly vehicles on the road, has been, over the
past decade, an active research topic in computer vision and intelligent transportation …

Abstract Advanced Driver Assistance Systems (ADAS) have made driving safer over the last
decade. They prepare vehicles for unsafe road conditions and alert drivers if they perform a …

In recent years, the deep learning object detection algorithms using 2D images have
become the powerful tools for road object detection in autonomous driving. In fact, the deep …