Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Waiting Time Estimation at Ferry Terminals Based on License Plate Recognition
https://orcid.org/0000-0001-8150-489X
https://orcid.org/0000-0002-0809-4924
https://orcid.org/0000-0001-6768-760X
https://orcid.org/0000-0003-4929-8613
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.
Waiting Time Estimation at Ferry Terminals Based on License Plate Recognition
https://orcid.org/0000-0001-8150-489X
https://orcid.org/0000-0002-0809-4924
https://orcid.org/0000-0001-6768-760X
https://orcid.org/0000-0003-4929-8613
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.
Waiting Time Estimation at Ferry Terminals Based on License Plate Recognition
https://orcid.org/0000-0001-8150-489X
https://orcid.org/0000-0002-0809-4924
https://orcid.org/0000-0001-6768-760X
https://orcid.org/0000-0003-4929-8613
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.
Waiting Time Estimation at Ferry Terminals Based on License Plate Recognition
J. Transp. Eng., Part A: Systems
Yang, Guangchuan (Autor:in) / Coble, Daniel (Autor:in) / Vaughan, Chris (Autor:in) / Peele, Catherine (Autor:in) / Morsali, Atefeh (Autor:in) / List, George F. (Autor:in) / Findley, Daniel J. (Autor:in)
01.09.2022
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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