A traffic demand forecasting model for internal junction in a multi-level bus terminal with RFID monitoring systems

Chien-Hung Wei, Steven I.Jy Chien, Ming Jeng Hsu, De Jun Wang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Taipei Bus Station is the first multi-level bus terminal and hub launched in the heart of Taipei metropolitan area. Different from OASIS21 in Nagoya and Port Authority Bus Terminal in New York City, significant congestion has been experienced during peak hours at a T-junction in the terminal due to the three-level structure in the high-density district. Based on the findings of an earlier study by the authors for a signal control model, a traffic demand forecasting model is needed to upgrade the existing pre-timed control strategy to adaptive control level. The artificial neural network approach is employed for constructing the demand forecasting model taking into account the relevant traffic flow information provided by the RFID readers embedded in the terminal monitoring systems. The results show that separate forecasting models for peak and non-peak periods would be desirable for both approaches at the T-junction.

Original languageEnglish
Title of host publication20th ITS World Congress Tokyo 2013
PublisherIntelligent Transportation Society of America
Publication statusPublished - 2013
Event20th Intelligent Transport Systems World Congress, ITS 2013 - Tokyo, Japan
Duration: 2013 Oct 142013 Oct 18

Other

Other20th Intelligent Transport Systems World Congress, ITS 2013
CountryJapan
CityTokyo
Period13-10-1413-10-18

Fingerprint

Bus terminals
Radio frequency identification (RFID)
traffic
monitoring
Monitoring
demand
Level control
information flow
Telecommunication traffic
neural network
agglomeration area
district
Neural networks

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Automotive Engineering
  • Control and Systems Engineering
  • Electrical and Electronic Engineering
  • Mechanical Engineering
  • Transportation
  • Computer Networks and Communications
  • Computer Science Applications

Cite this

Wei, C-H., Chien, S. I. J., Hsu, M. J., & Wang, D. J. (2013). A traffic demand forecasting model for internal junction in a multi-level bus terminal with RFID monitoring systems. In 20th ITS World Congress Tokyo 2013 Intelligent Transportation Society of America.
Wei, Chien-Hung ; Chien, Steven I.Jy ; Hsu, Ming Jeng ; Wang, De Jun. / A traffic demand forecasting model for internal junction in a multi-level bus terminal with RFID monitoring systems. 20th ITS World Congress Tokyo 2013. Intelligent Transportation Society of America, 2013.
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abstract = "Taipei Bus Station is the first multi-level bus terminal and hub launched in the heart of Taipei metropolitan area. Different from OASIS21 in Nagoya and Port Authority Bus Terminal in New York City, significant congestion has been experienced during peak hours at a T-junction in the terminal due to the three-level structure in the high-density district. Based on the findings of an earlier study by the authors for a signal control model, a traffic demand forecasting model is needed to upgrade the existing pre-timed control strategy to adaptive control level. The artificial neural network approach is employed for constructing the demand forecasting model taking into account the relevant traffic flow information provided by the RFID readers embedded in the terminal monitoring systems. The results show that separate forecasting models for peak and non-peak periods would be desirable for both approaches at the T-junction.",
author = "Chien-Hung Wei and Chien, {Steven I.Jy} and Hsu, {Ming Jeng} and Wang, {De Jun}",
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Wei, C-H, Chien, SIJ, Hsu, MJ & Wang, DJ 2013, A traffic demand forecasting model for internal junction in a multi-level bus terminal with RFID monitoring systems. in 20th ITS World Congress Tokyo 2013. Intelligent Transportation Society of America, 20th Intelligent Transport Systems World Congress, ITS 2013, Tokyo, Japan, 13-10-14.

A traffic demand forecasting model for internal junction in a multi-level bus terminal with RFID monitoring systems. / Wei, Chien-Hung; Chien, Steven I.Jy; Hsu, Ming Jeng; Wang, De Jun.

20th ITS World Congress Tokyo 2013. Intelligent Transportation Society of America, 2013.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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PY - 2013

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N2 - Taipei Bus Station is the first multi-level bus terminal and hub launched in the heart of Taipei metropolitan area. Different from OASIS21 in Nagoya and Port Authority Bus Terminal in New York City, significant congestion has been experienced during peak hours at a T-junction in the terminal due to the three-level structure in the high-density district. Based on the findings of an earlier study by the authors for a signal control model, a traffic demand forecasting model is needed to upgrade the existing pre-timed control strategy to adaptive control level. The artificial neural network approach is employed for constructing the demand forecasting model taking into account the relevant traffic flow information provided by the RFID readers embedded in the terminal monitoring systems. The results show that separate forecasting models for peak and non-peak periods would be desirable for both approaches at the T-junction.

AB - Taipei Bus Station is the first multi-level bus terminal and hub launched in the heart of Taipei metropolitan area. Different from OASIS21 in Nagoya and Port Authority Bus Terminal in New York City, significant congestion has been experienced during peak hours at a T-junction in the terminal due to the three-level structure in the high-density district. Based on the findings of an earlier study by the authors for a signal control model, a traffic demand forecasting model is needed to upgrade the existing pre-timed control strategy to adaptive control level. The artificial neural network approach is employed for constructing the demand forecasting model taking into account the relevant traffic flow information provided by the RFID readers embedded in the terminal monitoring systems. The results show that separate forecasting models for peak and non-peak periods would be desirable for both approaches at the T-junction.

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Wei C-H, Chien SIJ, Hsu MJ, Wang DJ. A traffic demand forecasting model for internal junction in a multi-level bus terminal with RFID monitoring systems. In 20th ITS World Congress Tokyo 2013. Intelligent Transportation Society of America. 2013