Probabilistic Motion Planning For Automated Vehicles
Download Probabilistic Motion Planning For Automated Vehicles PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Probabilistic Motion Planning For Automated Vehicles book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages.
Probabilistic Motion Planning for Automated Vehicles
Author: Naumann, Maximilian
language: en
Publisher: KIT Scientific Publishing
Release Date: 2021-02-25
In motion planning for automated vehicles, a thorough uncertainty consideration is crucial to facilitate safe and convenient driving behavior. This work presents three motion planning approaches which are targeted towards the predominant uncertainties in different scenarios, along with an extended safety verification framework. The approaches consider uncertainties from imperfect perception, occlusions and limited sensor range, and also those in the behavior of other traffic participants.
Motion Planning for Autonomous Vehicles in Partially Observable Environments
Author: Taş, Ömer Şahin
language: en
Publisher: KIT Scientific Publishing
Release Date: 2023-10-23
This work develops a motion planner that compensates the deficiencies from perception modules by exploiting the reaction capabilities of a vehicle. The work analyzes present uncertainties and defines driving objectives together with constraints that ensure safety. The resulting problem is solved in real-time, in two distinct ways: first, with nonlinear optimization, and secondly, by framing it as a partially observable Markov decision process and approximating the solution with sampling.
Path Planning for Autonomous Vehicle
Author: Umar Zakir Abdul Hamid
language: en
Publisher: BoD – Books on Demand
Release Date: 2019-10-02
Path Planning (PP) is one of the prerequisites in ensuring safe navigation and manoeuvrability control for driverless vehicles. Due to the dynamic nature of the real world, PP needs to address changing environments and how autonomous vehicles respond to them. This book explores PP in the context of road vehicles, robots, off-road scenarios, multi-robot motion, and unmanned aerial vehicles (UAVs ).