01626056

Component

https://doi.org/10.3141/2652-06

The public transport industry faces challenges in catering to the variety of mobility patterns and corresponding needs and preferences of passengers. Travel habit surveys provide information on overall travel demand as well as its spatial variation. However, that information often does not include information on temporal variations. By applying data fusion to smartcard and Global System for Mobile Communications (GSM) data, researchers were able to examine spatial and temporal patterns of public transport usage versus overall travel demand. The analysis was performed by contrasting different spatial and temporal levels of smartcard and GSM data. The methodology was applied to a case study in Rotterdam, Netherlands, to analyze whether the current service span is adequate. The results suggested that there is potential demand for extending public transport service on both ends. In the early mornings, right before transit operations are resumed, an hourly increase in visitor occupancy of 33% to 88% was observed in several zones, showing potential demand for additional public transport services. The proposed data fusion method was shown to be valuable in supporting tactical transit planning and decision making and can easily be applied to other origin-destination transport data.

01628042

17-01967

English

pp 50–58

2017

Transportation Research Record: Journal of the Transportation Research Board

9780309441933

Digital/other

Figures (5) ; Maps; References (24) ; Tables (2)

Case studies; Data fusion; Mobile communication systems; Origin and destination; Public transit; Ridership; Smart cards

Global System for Mobile Communications

Rotterdam (Netherlands)

Data and Information Technology; Planning and Forecasting; Public Transportation

TRIS, TRB, ATRI

Dec 8 2016 10:41AM

• Applications of Inferred Origins, Destinations, and Interchanges in Bus Service Planning
• Constructing Transit Origin–Destination Matrices with Spatial Clustering
• Estimating Fare Noninteraction and Evasion with Disaggregate Fare Transaction Data
• Estimation of Platform Waiting Time Distribution Considering Service Reliability Based on Smart Card Data and Performance Reports
• Exploratory Method for Practitioners Analyzing the Impact of Integrated Fare Structures in Decentralized Metropolitan Regions: A Toronto Region Case Study
• Fare System of Urban Public Transportation Services in Davao City, Philippines
• Inference of Public Transportation Trip Destinations by Using Fare Transaction and Vehicle Location Data: Dynamic Programming Approach
• Modeling the Impact of Transit Fare Change on Passengers’ Accessibility
• Perceived Reality: Understanding the Relationship Between Customer Perceptions and Operational Characteristics
• Quantile Regression Analysis of Transit Travel Time Reliability with Automatic Vehicle Location and Farecard Data
• Statistical Inference of Transit Passenger Boarding Strategies from Farecard Data
• The Youth Pass: A Study of the Conflicts Between Ideal and Practical Research Design in a Pilot Social Program
• Transit Trip Itinerary Inference with GTFS and Smartphone Data