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Monitoring Transit On-Time Performance Real Time Using a Web-Service Dataset

Fabian Cevallos, Xiaobo Wang, Albert Gan

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Abstract

Transit agencies have the opportunity to improve the delivery of services by using data from Intelligent Transportation Systems (ITS). Different ITS technologies and datasets are currently being used by transit agencies for different purposes. However, there is still the need for more sophisticated software applications to leverage the value of current ITS technologies. On-time performance is an important measure to almost every transit agency. Yet, there are still missing opportunities for improving on-time performance. This paper presents a method for monitoring on-time performance real time. It uses Automatic Vehicle Location (AVL) data and a web service that publishes a dataset directly from the database. An extended service is also included for system administrators. The paper describes the methodologies used to set up the data management, reporting services, web service, web application, and Skype software technology, which is used to process requests and to make the phone calls. This system can be used to notify transit staff automatically when the on-time performance for the whole system or a particular route is below a desired threshold. A case study conducted using data from Miami-Dade Transit (MDT) is also presented in this paper. It is expected that the methodology used and the findings from this research can be applied by transit agencies to help improve operational efficiencies and quality of service.

About this research paper

What this paper is about

Transit agencies have the opportunity to improve the delivery of services by using data from Intelligent Transportation Systems (ITS). Different ITS technologies and datasets are currently being used by transit agencies for different purposes. However, there is still the need for more sophisticated software applications to leverage the value of current ITS technologies. On-time performance is an important measure to almost every transit agency. Yet, there are still missing opportunities for improving on-time performance. This paper presents a method for monitoring on-time performance real time. It uses Automatic Vehicle Location (AVL) data and a web service that publishes a dataset directly from the database. An extended service is also included for system administrators. The paper describes the methodologies used to set up the data management, reporting services, web service, web application, and Skype software technology, which is used to process requests and to make the phone calls. This system can be used to notify transit staff automatically when the on-time performance for the whole system or a particular route is below a desired threshold. A case study conducted using data from Miami-Dade Transit (MDT) is also presented in this paper. It is expected that the methodology used and the findings from this research can be applied by transit agencies to help improve operational efficiencies and quality of service.

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Available abstract

Transit agencies have the opportunity to improve the delivery of services by using data from Intelligent Transportation Systems (ITS). Different ITS technologies and datasets are currently being used by transit agencies for different purposes. However, there is still the need for more sophisticated software applications to leverage the value of current ITS technologies. On-time performance is an important measure to almost every transit agency. Yet, there are still missing opportunities for improving on-time performance. This paper presents a method for monitoring on-time performance real time. It uses Automatic Vehicle Location (AVL) data and a web service that publishes a dataset directly from the database. An extended service is also included for system administrators. The paper describes the methodologies used to set up the data management, reporting services, web service, web application, and Skype software technology, which is used to process requests and to make the phone calls. This system can be used to notify transit staff automatically when the on-time performance for the whole system or a particular route is below a desired threshold. A case study conducted using data from Miami-Dade Transit (MDT) is also presented in this paper. It is expected that the methodology used and the findings from this research can be applied by transit agencies to help improve operational efficiencies and quality of service.

Key concepts: Computer science, Leverage (statistics), Web service, Software, Turnaround time, Web application, Transit (satellite), Service (business)

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