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Title:

Modeling Bus Bunnching Using Massive Location and Fare Collection Data

Accession Number:

01590922

Record Type:

Component

Abstract:

Bus bunching is a well-known phenomenon for operators, users and regulators of high-frequency bus services. Bus operations are usually affected by increasing differences in the time intervals (headways) between consecutive buses. The effect of this variability is that buses tend to group into bunches of two or more, which severely affects the quality of service and the operational efficiency. The aim of this paper is to contribute to the understanding of the phenomenon, using massive data from high-frequency services available in Santiago (Chile). The data are obtained from the bus GPS and are processed to obtain the headways between buses. The authors define a continuous indicator of bus bunching based on the variability of the observed headways and a discrete indicator that detects bunching when the proximity of two consecutive buses is below a threshold. Using data from one week, they build bus bunching maps. The authors also develop models to explain the variation of the continuous and discrete indicators as a function of variables related to the operation (distance, frequency, fleet composition, and variability of dispatching headways), variables related to the demand structure (boarding and alighting passengers), and variables related to the infrastructure (right of way, traffic signals, and distance between bus stops).

Supplemental Notes:

This paper was sponsored by TRB committee AP050 Standing Committee on Bus Transit Systems.

Monograph Accession #:

01584066

Report/Paper Numbers:

16-5915

Language:

English

Corporate Authors:

Transportation Research Board

500 Fifth Street, NW
Washington, DC 20001 United States

Authors:

Munizaga, Marcela
Arriagada, Jacqueline
Gschwender, Antonio

Pagination:

18p

Publication Date:

2016

Conference:

Transportation Research Board 95th Annual Meeting

Location: Washington DC, United States
Date: 2016-1-10 to 2016-1-14
Sponsors: Transportation Research Board

Media Type:

Digital/other

Features:

Figures; References; Tables

Geographic Terms:

Subject Areas:

Data and Information Technology; Planning and Forecasting; Public Transportation; I72: Traffic and Transport Planning

Source Data:

Transportation Research Board Annual Meeting 2016 Paper #16-5915

Files:

TRIS, TRB, ATRI

Created Date:

Jan 12 2016 6:37PM