01515586

Component

https://doi.org/10.3141/2418-13

The prediction of bus arrival times is an important element for travel planning. This study used three weeks of Chicago, Illinois, Transit Authority bus route GPS data to compare the performance of several commonly used methods and algorithms. The use of implicit schedules in previous papers was inadequate. The use of additional information, such as recent travel times along the route, is unnecessary. In addition, the use of computationally intensive machine learning algorithms, such as support vector regression, k nearest neighbor regression, and neural networks, is unnecessary. The study used basis expansion functions at various resolutions with linear models and cross-validated the models to determine explicitly the approximate historical interstop travel times for any time of the day and any day of the week. Combining the estimated interstop travel times with the real-time GPS location of a bus resulted in a flex schedule that was independent of scheduled departure or arrival times. Using a flex schedule makes the use of additional GPS information or the use of the machine learning algorithms unnecessary.

01557108

14-5594

English

pp 110–115

2014

Transportation Research Record: Journal of the Transportation Research Board

9780309295635

Print

Figures (2) ; References (11) ; Tables (3)

Bus routes; Bus transit; Forecasting; Global Positioning System; Scheduling; Travel time

Chicago Transit Authority

Chicago (Illinois)

Planning and Forecasting; Public Transportation; I72: Traffic and Transport Planning

TRIS, TRB, ATRI

Jan 27 2014 3:57PM

• All Aboard at All Doors: Route Selection and Running-Time Savings Estimation for Multiscenario All-Door Bus Boarding
• Buses with High Level of Service in Nantes, France: Characteristics and Results of the BusWay Compared with Light Rail Transit
• Combinatorial Optimization for the Guangzhou, China, Bus Rapid Transit System: Multiple Bus Substops and Docking Bays
• Evaluation of Presignals at Oversaturated Signalized Intersections
• Examining the Characteristics of Intercity Bus Passengers in Michigan
• Factors Contributing to Bus Lane Obstruction and Usage in New York City: Does Design Matter?
• Jobs-Housing Balance of Bus Commuters in Beijing: Exploration with Large-Scale Synthesized Smart Card Data
• Modeling Bus Dwell Time with Decision Tree–Based Methods
• Operational Comparison of Transit Signal Priority Strategies
• Optimal Connected Urban Bus Network of Priority Lanes
• Quantifying the Effects of Modal Conflicts on Transit Reliability
• Regulating Intercity Bus Stops in New York City
• Transit Signal Priority with Connected Vehicle Technology
• User Behavior in Multiroute Bus Corridors: Analysis by a Web-Based Survey