東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Linked to FindBook

Google Book

Amazon

博客來

Optimizing the Placement of Multiple UAV--LiDAR Units Under Road Priority and Resolution Requirements.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Optimizing the Placement of Multiple UAV--LiDAR Units Under Road Priority and Resolution Requirements./
Author:	Osterwisch, Zachary Michael.
Description:	1 online resource (63 pages)
Notes:	Source: Masters Abstracts International, Volume: 85-01.
Contained By:	Masters Abstracts International85-01.
Subject:	Computer engineering. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30419010click for full text (PQDT)
ISBN:	9798379920784

Optimizing the Placement of Multiple UAV--LiDAR Units Under Road Priority and Resolution Requirements.
Osterwisch, Zachary Michael.

Optimizing the Placement of Multiple UAV--LiDAR Units Under Road Priority and Resolution Requirements. - 1 online resource (63 pages)

Source: Masters Abstracts International, Volume: 85-01.

Thesis (M.S.)--Missouri University of Science and Technology, 2023.

Includes bibliographical references

Real-time road traffic information is crucial for intelligent transportation systems (ITS) applications, like traffic navigation or emergency response management, but acquiring such data is tremendously challenging in practice because of the high costs and inefficient placement of sensors. Some modern ITS applications contribute to this problem by equipping vehicles with multiple light detection and ranging (LiDAR) sensors, which are expensive and gather data inefficiently; one solution that avoids vehicle-mounted LiDAR acquisition has been to install elevated LiDAR instruments along roadways, but this approach remains unrefined. The eventual development of sixth-generation (6G) wireless communication will enable new, creative solutions to solve these challenges. One new solution is to deploy multiple multirotor unmanned aerial vehicles (UAVs) outfitted with LiDAR sensors (ULiDs) to acquire data remotely. These ULiDs can capture accurate and real-time road traffic information for ITS applications while maximizing the capabilities of LiDAR sensors, which in turn reduces the number of sensors required. Accordingly, this thesis aims to find the optimal 3D placement of multiple ULiDs to maximize road coverage efficiency for ITS purposes. The formulated optimization problem is constrained by unique ULiD specifications, including field-of-view (FoV), point cloud resolution, geographic information system location, and road segment coverage priorities. A computational intelligent algorithm based on particle swarm optimization is proposed to solve the designed optimization problem. Furthermore, this thesis illustrates the benefits of using the proposed algorithm over existing baselines.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2023

Mode of access: World Wide Web

ISBN: 9798379920784Subjects--Topical Terms:

621879
Computer engineering.
Subjects--Index Terms:

Intelligent transportation systemsIndex Terms--Genre/Form:

542853
Electronic books.

Optimizing the Placement of Multiple UAV--LiDAR Units Under Road Priority and Resolution Requirements.
LDR:03081nmm a2200373K 4500 001 2360078
005 20230925052818.5
006 m o d
007 cr mn ---uuuuu
008 241011s2023 xx obm 000 0 eng d
020 $a 9798379920784
035 $a (MiAaPQ)AAI30419010
035 $a AAI30419010
040 $a MiAaPQ $b eng $c MiAaPQ $d NTU
100 1 $a Osterwisch, Zachary Michael. $3 3700689
245 1 0 $a Optimizing the Placement of Multiple UAV--LiDAR Units Under Road Priority and Resolution Requirements.
264 0 $c 2023
300 $a 1 online resource (63 pages)
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
500 $a Source: Masters Abstracts International, Volume: 85-01.
500 $a Advisor: Alsharoa, Ahmad.
502 $a Thesis (M.S.)--Missouri University of Science and Technology, 2023.
504 $a Includes bibliographical references
520 $a Real-time road traffic information is crucial for intelligent transportation systems (ITS) applications, like traffic navigation or emergency response management, but acquiring such data is tremendously challenging in practice because of the high costs and inefficient placement of sensors. Some modern ITS applications contribute to this problem by equipping vehicles with multiple light detection and ranging (LiDAR) sensors, which are expensive and gather data inefficiently; one solution that avoids vehicle-mounted LiDAR acquisition has been to install elevated LiDAR instruments along roadways, but this approach remains unrefined. The eventual development of sixth-generation (6G) wireless communication will enable new, creative solutions to solve these challenges. One new solution is to deploy multiple multirotor unmanned aerial vehicles (UAVs) outfitted with LiDAR sensors (ULiDs) to acquire data remotely. These ULiDs can capture accurate and real-time road traffic information for ITS applications while maximizing the capabilities of LiDAR sensors, which in turn reduces the number of sensors required. Accordingly, this thesis aims to find the optimal 3D placement of multiple ULiDs to maximize road coverage efficiency for ITS purposes. The formulated optimization problem is constrained by unique ULiD specifications, including field-of-view (FoV), point cloud resolution, geographic information system location, and road segment coverage priorities. A computational intelligent algorithm based on particle swarm optimization is proposed to solve the designed optimization problem. Furthermore, this thesis illustrates the benefits of using the proposed algorithm over existing baselines.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2023
538 $a Mode of access: World Wide Web
650 4 $a Computer engineering. $3 621879
650 4 $a Automotive engineering. $3 2181195
650 4 $a Transportation. $3 555912
653 $a Intelligent transportation systems
653 $a Real-time road traffic information
653 $a Unmanned aerial vehicles
655 7 $a Electronic books. $2 lcsh $3 542853
690 $a 0464
690 $a 0709
690 $a 0540
710 2 $a ProQuest Information and Learning Co. $3 783688
710 2 $a Missouri University of Science and Technology. $b Computer Engineering. $3 3182167
773 0 $t Masters Abstracts International $g 85-01.
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30419010 $z click for full text (PQDT)