Intelligent connected vehicles (ICVs) are believed to change people's life in the near future
by making the transportation safer, cleaner and more comfortable. Although many …

Reinforcement learning (RL) can learn from past failures and has the potential to provide
self-improvement ability and higher-level intelligence. However, the current RL algorithms …

We propose a robust calibration pipeline that optimises the selection of calibration samples
for the estimation of calibration parameters that fit the entire scene. We minimise user error …

Exiting from highways in crowded dynamic traffic is an important path planning task for
autonomous vehicles (AVs). This task can be challenging because of the uncertain motion of …

An automated vehicle operating in an urban environment must be able to perceive and
recognise objects and obstacles in a three-dimensional world for navigation and path …

Featured Application The algorithms proposed in this paper can be applied to a wide range
of infrastructure projects in the pre-survey process with the advantages of low cost and high …

In order to reduce the dimensionality of 3D point cloud representations, autoencoder
architectures generate increasingly abstract, compressed features of the input data …

A unified neural network structure is presented for joint 3D object detection and point cloud
segmentation in this paper. We leverage rich supervision from both detection and …

The main goal of this paper is to introduce the data collection effort at Mcity targeting
automated vehicle development. We captured a comprehensive set of data from a set of …

A typical autonomous driving system usually relies on the detected objects from an
environment perception module. Current research still cannot guarantee a perfect …