An Adaptive Motion Planning Technique for On-Road Autonomous Driving

On-Road Motion Planning for Autonomous Vehicles

We present a motion planner for autonomous on-road driving, especially on highways. It adapts the idea of a on-road state lattice. A focused search is performed in the previously identified region in which the optimal trajectory is most likely to exist. The main contribution of this paper is a computationally efficient planner which handles dynamic environments generically. The Dynamic Programm...

Safe Motion Planning for Autonomous Driving

Self-driving cars have the potential to revolutionize transportation by making it cheaper, safer, and more efficient. In this thesis we describe a novel motion planning system, which translates high-level navigation goals into low-level actions for controlling a vehicle. Specifically, the motion planning system is responsible for choosing at each time step an appropriate velocity and steering a...

Real-Time Motion Planning 
 and
 Autonomous Driving

An Incremental Stochastic Motion Planning Technique for Autonomous Underwater Vehicles

This paper presents a variant of an incremental stochastic motion planning technique for autonomous underwater vehicles (AUVs) that considers both the algebraic constraints, caused by the environment obstacles, and differential constraints, induced by the vehicle dynamics. The term kinodynamic planning is used to describe this type of motion planning. The majority of AUV path planners tend to a...

A Lightweight Simulator for Autonomous Driving Motion Planning Development

A good simulation environment will facilitate motion planning algorithm development for urban autonomous driving. The first requirement of such a simulator is to be able to replicate a complex urban environment, including road network, curb, general objects, etc. The second requirement is to simulate a realistic host vehicle, which includes perception, control and vehicle dynamics, to recreate ...