We survey research on self-driving cars published in the literature focusing on autonomous
cars developed since the DARPA challenges, which are equipped with an autonomy system …

Understanding the complex urban infrastructure with centimeter-level accuracy is essential
for many applications from autonomous driving to mapping, infrastructure monitoring, and …

随着城市汽车保有量的稳步增长, 道路交通拥堵问题日益凸显, 给城市发展带来了巨大压力.
为了有效应对这一挑战, 开发能够提高交通效率并降低能源消耗的方法显得至关重要 …

Autonomous driving systems have emerged with the promise of preventing accidents. The
first critical aspect of these systems is perception, where the regular practice is the use of top …

This paper addresses the problem of building augmented metric representations of scenes
with semantic information from RGB-D images. We propose a complete framework to create …

We present a new framework for creating lane-level detailed HD-maps at scale for
autonomous vehicles (AVs). In order to overcome scaling challenges of ground survey …

By providing rich context of lane information on roads, lane-level maps play a vital role in
intelligent transportation systems. Since Global Positioning Systems (GPS) have been …

In this paper, we propose a framework to build an improved metric representation of the
environment with semantic information. We explore some of the recent advances of deep …

Deep Learning (DL) systems are increasingly being used in many safety-critical automotive
applications such as traffic sign recognition. Despite the great success of DL systems in …

Object recognition, object detection, and semantic segmentation are fundamental
components of the intelligent vehicle. Recently, there have been various methods proposed …