Automated driving systems (ADSs) promise a safe, comfortable and efficient driving
experience. However, fatalities involving vehicles equipped with ADSs are on the rise. The …

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 …

This article presents FAST-LIO2: a fast, robust, and versatile LiDAR-inertial odometry
framework. Building on a highly efficient tightly coupled iterated Kalman filter, FAST-LIO2 …

We present Argoverse, a dataset designed to support autonomous vehicle perception tasks
including 3D tracking and motion forecasting. Argoverse includes sensor data collected by a …

Rapid progress in machine learning and artificial intelligence (AI) has brought increasing
attention to the potential impacts of AI technologies on society. In this paper we discuss one …

Intelligent vehicles have increased their capabilities for highly and, even fully, automated
driving under controlled environments. Scene information is received using onboard …

With the emergence of Large Language Models (LLMs) and Vision Foundation Models
(VFMs), multimodal AI systems benefiting from large models have the potential to equally …

To model the indeterminacy of human behaviors, stochastic trajectory prediction requires a
sophisticated multi-modal distribution of future trajectories. Emerging diffusion models have …

Coherent ranging, also known as frequency-modulated continuous-wave (FMCW) laser-
based light detection and ranging (lidar) is used for long-range three-dimensional distance …

We demonstrate the first application of deep reinforcement learning to autonomous driving.
From randomly initialised parameters, our model is able to learn a policy for lane following in …