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Parallel Best-First Heuristic Search applied to Cooperative Planning for Automated Vehicles

Agamirzov, Evgeny (2016) Parallel Best-First Heuristic Search applied to Cooperative Planning for Automated Vehicles. Master's, Technische Universität München.

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Abstract

This paper studies the utilization of multi-core processors for path planning algorithms. A* best-first heuristic search algorithm is used for path finding, where the state space is a search tree that is built from discrete trajectory paths (motion primitives). Particularity of the given search problem is computationally expensive expansion step and large branching factor of the tree. Most recent parallelization techniques has been evaluated to identify which one fits best for the existing planning problem (considering significant differences between A* parallelization approaches). Finally, two schemes were chosen to be tested in real life scenarios - PA* and PRA* (HDA*). These algorithms represent two basic strategies of the best-first search parallelization that are shared OPEN list (PA*) and private OPEN lists (PRA*, HDA*). Both approaches has been tested for execution time and memory usage, and eventually compared head to head. Experiments were conducted for different road scenarios with various complexity. The main goal of this work was to show that multi-core machines can be successfully applied to path finding (planning) problems for automated vehicles. The thesis was funded and supported by Deutsches Zentrum für Luft- und Raumfahrt (DLR), Institut für Verkehrssystemtechnik. All implemented algorithms were embedded into DLR’s simulation environment where real car models and road scenarios are being tested.

Item URL in elib:https://elib.dlr.de/105063/
Document Type:Thesis (Master's)
Title:Parallel Best-First Heuristic Search applied to Cooperative Planning for Automated Vehicles
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Agamirzov, EvgenyUNSPECIFIEDUNSPECIFIED
Date:1 July 2016
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Number of Pages:95
Status:Published
Keywords:Automated Vehicles, Motion Planning, Cooperative Driving
Institution:Technische Universität München
Department:Computational Science and Engineering
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Transport
HGF - Program Themes:Terrestrial Vehicles (old)
DLR - Research area:Transport
DLR - Program:V BF - Bodengebundene Fahrzeuge
DLR - Research theme (Project):V - Fahrzeugintelligenz (old)
Location: Braunschweig
Institutes and Institutions:Institute of Transportation Systems
Deposited By: Heß, Daniel
Deposited On:18 Jul 2016 07:57
Last Modified:18 Jul 2016 12:33

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