2010Transportation Research Record Journal of the Transportation Research BoardRequires access

Development of Data-Processing Framework for Transit Performance Analysis

Chen-Fu Liao, Henry Liu

Open publisher page 15 citations

Abstract

A methodological data-processing framework is developed to process a massive amount of transit data, including vehicle location, passenger count, and electronic fare transactions. The developed data analysis methodology can allow a number of applications, such as transit route performance measurement, to support decision making for transit planning and operation. The data analysis methodology is demonstrated by the use of 1 month of archived transit data obtained from Metro Transit in the Twin Cities of Minnesota. A route-based transit performance analysis at time point level is discussed to evaluate route running time and schedule adherence. An application interface was developed to analyze bus adherence at time points and link travel time performance. The data-processing framework has the capability to support studies on transfer activities and transit rider's origin and destination inference. The developed data analysis methodology has demonstrated its capability to analyze transit performance and to support further research on other intelligent transit applications.

About this research paper

What this paper is about

A methodological data-processing framework is developed to process a massive amount of transit data, including vehicle location, passenger count, and electronic fare transactions. The developed data analysis methodology can allow a number of applications, such as transit route performance measurement, to support decision making for transit planning and operation. The data analysis methodology is demonstrated by the use of 1 month of archived transit data obtained from Metro Transit in the Twin Cities of Minnesota. A route-based transit performance analysis at time point level is discussed to evaluate route running time and schedule adherence. An application interface was developed to analyze bus adherence at time points and link travel time performance. The data-processing framework has the capability to support studies on transfer activities and transit rider's origin and destination inference. The developed data analysis methodology has demonstrated its capability to analyze transit performance and to support further research on other intelligent transit applications.

Why it matters

OpenAlex reports 15 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

A methodological data-processing framework is developed to process a massive amount of transit data, including vehicle location, passenger count, and electronic fare transactions. The developed data analysis methodology can allow a number of applications, such as transit route performance measurement, to support decision making for transit planning and operation. The data analysis methodology is demonstrated by the use of 1 month of archived transit data obtained from Metro Transit in the Twin Cities of Minnesota. A route-based transit performance analysis at time point level is discussed to evaluate route running time and schedule adherence. An application interface was developed to analyze bus adherence at time points and link travel time performance. The data-processing framework has the capability to support studies on transfer activities and transit rider's origin and destination inference. The developed data analysis methodology has demonstrated its capability to analyze transit performance and to support further research on other intelligent transit applications.

Key concepts: Transit (satellite), Schedule, Transport engineering, Computer science, Process (computing), Public transport, Data processing, Data collection

Related papers

Back to paper searchBrowse research topicsOriginal source
Development of Data-Processing Framework for Transit Performance Analysis — Research Paper | ScholarLens