Title
Data-Driven Support Tools for Transit Data Analysis, Scheduling and Planning
Publisher
Intelligent Transportation Systems Institute Center for Transportation Studies
Abstract
Many transit agencies in the U.S. have instrumented their fleet with Automatic Data Collection Systems (ADCS) to
monitor the performance of transit vehicles, support schedule planning and improve quality of services. The
objective of this study is to use an urban local route (Metro Transit Route 10 in Twin Cities) as a case study and
develop a route-based trip time model to support scheduling and planning while applying different transit
strategies. Usually, timepoints (TP) are virtually placed on a transit route to monitor its schedule adherence and
system performance. Empirical TP time and inter-TP link travel time models are developed. The TP-based models
consider key parameters such as number of passengers boarding and alighting, fare payment type, bus type, bus
load (seat availability), stop location (nearside or far side), traffic signal and volume that affect bus travel time. TP
time and inter-TP link travel time of bus route 10 along Central Avenue between downtown Minneapolis and
Northtown were analyzed to describe the relationship between trip travel time and primary independent variables.
Regression models were calibrated and validated by comparing the simulation results with existing schedule using
adjusted travel time derived from data analyses. The route-based transit simulation model can support Metro
Transit in evaluating different schedule plans, stop consolidations, and other strategies. The transit model provides
an opportunity to predict and evaluate potential impact of different transit strategies prior to deployment.
Funding information
Intelligent Transportation Systems Institute, Center for Transportation Studies, University of Minnesota
Suggested Citation
Liao, Chen-Fu.
(2011).
Data-Driven Support Tools for Transit Data Analysis, Scheduling and Planning.
Intelligent Transportation Systems Institute Center for Transportation Studies.
Retrieved from the University of Minnesota Digital Conservancy,
https://hdl.handle.net/11299/149402.