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原文传递 Waiting Time Estimation at Ferry Terminals Based on License Plate Recognition

题名：	Waiting Time Estimation at Ferry Terminals Based on License Plate Recognition
正文语种：	eng
作者：	Guangchuan Yang;Daniel Coble;Chris Vaughan;Catherine Peele;Atefeh Morsali;George F. List;Daniel J. Findley
作者单位：	Institute for Transportation Research and Education (ITRE) North Carolina State Univ. Centennial Campus Raleigh NC 27695-8601;Institute for Transportation Research and Education (ITRE) North Carolina State Univ. Centennial Campus Raleigh NC 27695-8601;Institute for Transportation Research and Education (ITRE) North Carolina State Univ. Centennial Campus Raleigh NC 27695-8601;Ferry Div. North Carolina Department of Transportation Manns Harbor NC 27953;Dept. of Civil Construction and Environmental Engineering North Carolina State Univ. Centennial Campus Box 8601 Raleigh NC 27695-8601;Dept. of Civil Construction and Environmental Engineering North Carolina State Univ. Centennial Campus Box 8601 Raleigh NC 27695-8601;Institute for Transportation Research and Education (ITRE) North Carolina State Univ. Centennial Campus Raleigh NC 27695-8601
关键词：	Ferry terminal; Waiting time; Queue; License plate recognition (LPR); Tourism demand
摘要：	The ferry transit system provides a critical transportation link in coastal areas for both residents and tourists. Like signals in a road network, queuing and waiting are unavoidable at ferry terminals. However, a reliable technology does not exist to measure and communicate waiting times. This research tested the feasibility of applying license plate recognition (LPR) technology to track vehicles and estimate waiting times at ferry terminals. The LPR camera sampling rate, capture rate, read rate, and match rate were adopted as measurements of effectiveness. Based on field data collected over a week at one of the busiest ferry terminals in North Carolina, this research revealed that the tested LPR camera had a sampling rate of 84.2%; the average capture rate and read rate were 84.3% and 87%, respectively. The match rate was found to be 79.4%, which is significantly higher than other commonly used data collection technologies such as Bluetooth devices. For the waiting time distribution, this research found that travelers tended to experience long waiting times during midweek days, particularly during the midday period. Additionally, the demand was found to be the primary factor for wait times during the midday peak period, and travelers' arrival time in terms of proximity to the scheduled ferry departure time was recognized as the key factor for waiting time during early morning and later evening nonpeak periods.
出版年：	2022
期刊名称：	Journal of Transportation Engineering
卷：	148
期：	9
页码：	04022064.1-04022064.10