Motion planning plays a significant role in enabling advances of autonomous vehicles in
saving lives and improving traffic efficiency. In a predictive motionplanning strategy, the ego …

This paper proposes an interaction-aware motion-planning method for an autonomous
vehicle in uncertain multi-vehicle traffic environments. An interaction-aware motion …

This article proposes an interaction and safety-aware motion-planning method for an
autonomous vehicle in uncertain multi-vehicle traffic environments. The method integrates …

Autonomous vehicles (AVs) must share the driving space with other drivers and often
employ conservative motion planning strategies to ensure safety. These conservative …

This paper investigates an integrated traffic environment modeling and model predictive
control (MPC) system to realize interaction-aware dynamic motion planning of an …

We propose a Stochastic MPC (SMPC) formulation for path planning with autonomous
vehicles in scenarios involving multiple agents with multi-modal predictions. The multi …

The predictive motion prediction of surrounding vehicles is an essential precondition for
precise collision risk assessment and path planning. In this paper, we propose a motion …

Model Predictive Control (MPC) has been widely applied to the motion planning of
autonomous vehicles. An MPC-controlled vehicle is required to predict its own trajectories in …

Motion planning in autonomous driving is a major challenge, as it needs to consider the
continuity between the actions output by internal modules and the need for consistency in …

Motion planning and decision-making while considering uncertainty is critical for an
autonomous vehicle to safely and efficiently drive on a highway. This paper presents a new …