Automated vehicles are increasingly getting main-streamed and this has pushed
development of systems for autonomous manoeuvring (eg, lane-change, merge, and …

This paper presents a nonlinear model predictive control (MPC) formulation for obstacle
avoidance in high-speed, large-size autono-mous ground vehicles (AGVs) with high centre …

This paper develops an integrated safety-enhanced reinforcement learning (RL) and model
predictive control (MPC) framework for autonomous vehicles (AVs) to navigate unsignalized …

This work introduces the use of hard constraints to avoid moving obstacles for navigating a
large, high-speed autonomous ground vehicle in an unstructured environment using …

A path planning and tracking framework is presented to maintain a collision-free path for
autonomous vehicles. For path-planning approaches, a 3-D virtual dangerous potential field …

This paper focuses on the real-time trajectory planning problem for autonomous vehicles
driving in realistic urban environments. To solve the complex navigation problem, we adopt …

In this article, we propose a new approach to drive a vehicle at high speed along a
predetermined path using Model Predictive Control. Instead of modeling precise vehicle …

As a typical example of cyber-physical systems, intelligent vehicles are receiving increasing
attention, and the obstacle avoidance problem for such vehicles has become a hot topic of …

This paper presents a motion-planning framework for urban autonomous driving at
uncontrolled intersections. The intention and future state of the target vehicles are predicted …

Controlling the lateral dynamics of an autonomous vehicle confronting a sudden obstacle
requires optimal use of tires' force capacities. In these situations, autonomous steering may …