國立虎尾科技大學 |

Applications in Traffic Analysis from Automatically Extracted Road User Interactions with Roadside LiDAR Trajectories.

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Applications in Traffic Analysis from Automatically Extracted Road User Interactions with Roadside LiDAR Trajectories./
作者:	Whitley, Trevor.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2022,
面頁冊數:	52 p.
附註:	Source: Masters Abstracts International, Volume: 84-01.
Contained By:	Masters Abstracts International84-01.
標題:	Civil engineering. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=29166464
ISBN:	9798834054252

Applications in Traffic Analysis from Automatically Extracted Road User Interactions with Roadside LiDAR Trajectories.
Whitley, Trevor.

Applications in Traffic Analysis from Automatically Extracted Road User Interactions with Roadside LiDAR Trajectories. - Ann Arbor : ProQuest Dissertations & Theses, 2022 - 52 p.

Source: Masters Abstracts International, Volume: 84-01.

Thesis (M.S.)--University of Nevada, Reno, 2022.

This item must not be sold to any third party vendors.

Traffic trajectory data extracted from sensors such as LiDAR and camera has birthed new research areas in the field of transportation. Traffic trajectories is defined at the ability to track road users through time and space at high frequency, typically every tenth of a second. Given this higher granularity of micro traffic data, the behavior of road users can be explored to understand the operational and safety performances on the roads. Therefore, researchers have been stretching the limits to what this type of data can be applied to. Most studies look into the interactions of road users as a surrogate safety measure (SSM) to identify potentially dangerous situation using measures such as post encroachment time (PET) or time to collision(TTC); however, not much applications have been explored outside this. This paper seeks to stretch the imagination for what this type of data can be used for using trajectories generated from roadside LiDARcloud point data. The first application presented in this paper introduces the first automated method to extract headways and determine capacities at roundabouts entry legs. The method provided accurate capacity results when compared to other standard methods. The second application proposes an automated method to extract pedestrian-vehicle yield rates at uncontrolled crosswalks Pedestrian-vehicle interaction(PVI) analyses from trajectory data has been studied using the SSMs mentioned, but an analysis on yield rates using trajectory data has seldom been performed. This research in traffic trajectory applications paves the way for further applications in traffic safety, operations, and planning.

ISBN: 9798834054252Subjects--Topical Terms:

561339
Civil engineering.
Subjects--Index Terms:

Capacity

Applications in Traffic Analysis from Automatically Extracted Road User Interactions with Roadside LiDAR Trajectories.
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245 1 0 $a Applications in Traffic Analysis from Automatically Extracted Road User Interactions with Roadside LiDAR Trajectories.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2022
300 $a 52 p.
500 $a Source: Masters Abstracts International, Volume: 84-01.
500 $a Advisor: Xu, Hao.
502 $a Thesis (M.S.)--University of Nevada, Reno, 2022.
506 $a This item must not be sold to any third party vendors.
520 $a Traffic trajectory data extracted from sensors such as LiDAR and camera has birthed new research areas in the field of transportation. Traffic trajectories is defined at the ability to track road users through time and space at high frequency, typically every tenth of a second. Given this higher granularity of micro traffic data, the behavior of road users can be explored to understand the operational and safety performances on the roads. Therefore, researchers have been stretching the limits to what this type of data can be applied to. Most studies look into the interactions of road users as a surrogate safety measure (SSM) to identify potentially dangerous situation using measures such as post encroachment time (PET) or time to collision(TTC); however, not much applications have been explored outside this. This paper seeks to stretch the imagination for what this type of data can be used for using trajectories generated from roadside LiDARcloud point data. The first application presented in this paper introduces the first automated method to extract headways and determine capacities at roundabouts entry legs. The method provided accurate capacity results when compared to other standard methods. The second application proposes an automated method to extract pedestrian-vehicle yield rates at uncontrolled crosswalks Pedestrian-vehicle interaction(PVI) analyses from trajectory data has been studied using the SSMs mentioned, but an analysis on yield rates using trajectory data has seldom been performed. This research in traffic trajectory applications paves the way for further applications in traffic safety, operations, and planning.
590 $a School code: 0139.
650 4 $a Civil engineering. $3 561339
650 4 $a Transportation. $3 558117
653 $a Capacity
653 $a Roadside LiDAR
653 $a Surrogate safety measure
653 $a Trajectories
653 $a Yield rate
690 $a 0709
690 $a 0543
710 2 $a University of Nevada, Reno. $b Civil and Environmental Engineering. $3 1413496
773 0 $t Masters Abstracts International $g 84-01.
790 $a 0139
791 $a M.S.
792 $a 2022
793 $a English
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