Title

Data-Driven Support Tools for Transit Data Analysis, Scheduling and Planning

Authors

Chen-fu Liao

Document Type

Report

Publication Date

7-2011

Subject Area

mode - bus, place - north america, operations - scheduling, operations - performance, mode - bus rapid transit

Keywords

Public transit, Structural equation modeling, Time point, Travel time, On time performance, Route model, Data analysis, TSP, Bus rapid transit, Trip tables, Traffic models, Data processing, Bus priority

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.

Rights

Permission to publish the abstract and link to the report has been given by the University of Minnesota, Center for Transportation Studies

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