Grid-centric perception is a crucial field for mobile robot perception and navigation.
Nonetheless, grid-centric perception is less prevalent than object-centric perception for …

Environmental perception with the multi-modal fusion is crucial in autonomous driving to
increase accuracy, completeness, and robustness. This paper focuses on utilizing millimeter …

Deep neural network algorithms have achieved impressive performance in object detection.
Real-time evaluation of perception uncertainty from deep neural network algorithms is …

Risk assessment is important for intelligent vehicles to make safe driving decisions. In some
researches, the risk is modeled as the effect of each environment element on the ego …

The increased use of smartphones and in-vehicle infotainment systems leads to more
distraction related accidents. Although numerous deep learning techniques have been …

Path tracking for autonomous vehicles is one of the most critical tasks in intelligent
transportation systems (ITS). The ITS performance, including efficiency, safety, flexibility, and …

An ideal driving behavior model should be able to adapt to constantly changing
environments. Most of the existing models are proposed for specific traffic scenarios, so their …

Over the past decades, an Autonomous Vehicles (AVs) driving functions have obtained the
more interests from both the industry and academia. The AVs needed a basic planner for all …