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Title:

Simulation and Evaluation of Using Unmanned Aerial Vehicle to Detect Low-Volume Road Traffic Incident

Accession Number:

01557789

Record Type:

Component

Availability:

Transportation Research Board Business Office

500 Fifth Street, NW
Washington, DC 20001 United States

Abstract:

Traffic monitoring with infrastructure-based sensors is effective and reliable for improving traffic safety and traffic monitoring on high-volume roads, but not on low-volume roads. Low-volume roads in remote areas lack traffic monitoring sensors and thus traffic incidents are difficult to detect in a timely manner. Hence, this paper focused on low-volume road, and introduced Unmanned Aerial Vehicle (UAV) to detect traffic incident and analyzed its feasibility. Firstly, the research aim and definition of traffic incident were presented. Then, a numerical simulation method of using UAV to detect traffic incident was proposed, and a simulation case study with sensitivity analysis was implemented. Next, a UAV flight experiment was conducted. Finally, the cost-benefit analysis of using UAV to detect incident was given. The simulation results showed: (1) the theoretical UAV incident detection rate of the given scenario was 8.80%; (2) extending incident detection time, conducting UAV shuttling flight can increase incident detection rate significantly; and (3) some factors, such as UAV detection range, UAV flight speed and road incident occurrence rate, had little impact on incident detection result. The experiment and cost-benefit analysis showed that it’s cost efficient to use UAV to detect incident for low-volume road.

Supplemental Notes:

This paper was sponsored by TRB committee ABJ50 Information Systems and Technology. Alternate title: Simulation and Evaluation of Using Unmanned Aerial Vehicle to Detect Low-Volume Road Traffic Incidents.

Monograph Accession #:

01550057

Report/Paper Numbers:

15-2110

Language:

English

Corporate Authors:

Transportation Research Board

500 Fifth Street, NW
Washington, DC 20001 United States

Authors:

Liu, Xiaofeng
Peng, Zhong-Ren
Hou, Haijing
Wang, Longzhi

Pagination:

16p

Publication Date:

2015

Conference:

Transportation Research Board 94th Annual Meeting

Location: Washington DC, United States
Date: 2015-1-11 to 2015-1-15
Sponsors: Transportation Research Board

Media Type:

Digital/other

Features:

Figures; Photos; References; Tables

Geographic Terms:

Xinjiang (China)

Subject Areas:

Highways; Operations and Traffic Management; Planning and Forecasting; I72: Traffic and Transport Planning

Source Data:

Transportation Research Board Annual Meeting 2015 Paper #15-2110

Files:

TRIS, TRB, ATRI

Created Date:

Dec 30 2014 12:45PM