Programs & Labs
Advanced System Analysis for Public Transit (ASAPT) - Using Data-Driven Transit Performance Measures for Transit Network Analysis
Principal Investigator:
- Chen-Fu Liao, CTS Research Scholar/Sr. Systems Engineer, MTO/Civil Engineering
Co-Investigator:
- Henry Liu, Assistant Professor, Civil Engineering
Project Summary
Metro Transit has deployed Automatic Vehicle Location (AVL) and Automatic Passenger Count (APC) systems to collect bus data for their fleet operation and management. The AVL/APC systems allow transit analysts and planners to analyze and identify problems with operations and route schedules and make the appropriate adjustments. However, these data are currently queried on ‘as needed’ basis or used for quarterly schedule planning due to the tremendous amount of data collected and limited human resources. Improved data mining, data fusion and data visualization tools are necessary to extract from the huge volume of available data, the essential information that is needed for transit system performance analysis. This research will extend our on-going development of integrated transit database for AVL and APC data, which is funded by the Digital Technology Center, to develop effective and efficient data mining and fusion methodology for generating transit performance measures systematically. The proposed study will will streamline transit data analysis and help transit managers in identifying the causes, characteristics and variables associated with transit service problems network wide. With the AVL and APC data, we will also investigate the possibility of optimizing transit schedule automatically. Because AVL data can provide a more realistic estimate of travel time between stops and APC data can provide the day-to-day variations of travel demand, it allow us to formulate an optimization model so that transit schedule along a route or in a network can be improved.
Sponsors:
- ITS Institute (RITA)