Autonomous driving in public roads requires precise localization within the range of few
centimeters. Even the best localization systems based on GNSS cannot always reach this …

This paper surveys a number of recent developments in modern Global Navigation Satellite
Systems (GNSS) and investigates the possible impact on autonomous driving architectures …

Trajectory prediction is confronted with the dilemma to capture the multi-modal nature of
future dynamics with both diversity and accuracy. In this paper, we propose a distribution …

Automated vehicles (AVs) promise to improve road safety, reduce traffic congestion and
emissions, and enhance mobility. However, evidence regarding their safety benefits has not …

Autonomous vehicles (AVs) are the latest trend in the automobile industry. Although the
concept has existed since the beginning of the last century, recent technological …

Autonomous perception requires high-quality environment sensing in the form of 3D
bounding boxes of dynamic objects. The primary sensors used in automotive systems are …

Nowadays, computer vision with 3D (dimension) object detection and 6D (degree of
freedom) pose assumptions are widely discussed and studied in the field. In the 3D object …

We present a new practical framework based on deep reinforcement learning and decision-
time planning for real-world vehicle repositioning on ride-hailing (a type of mobility-on …

Autonomous Vehicles (AVs) have the potential to solve many traffic problems, such as
accidents, congestion and pollution. However, there are still challenges to overcome, for …

The inevitable upcoming technology of autonomous vehicles (AVs) will affect our cities and
several aspects of our lives. The widespread adoption of AVs repose at crossing distinct …