Modeling bus bunching using massive location and fare collection data
Document Type
Journal Article
Publication Date
2019
Subject Area
place - north america, place - south america, mode - bus, operations - frequency, planning - service quality, ridership - demand, infrastructure - bus/tram lane, infrastructure - stop, technology - geographic information systems
Keywords
Bus bunching, bus lane, public transport, travel time
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 analyze which factors are associated to the phenomenon, using massive data from high-frequency services available in Santiago (Chile) and common-route services in Gatineau (Canada). The data is obtained from the bus GPS and AFC systems and are processed to obtain headways between buses. Using data from one week, we develop models to explain the variation of the continuous and discrete indicators of bus bunching as a function of variables related to the operation, variables related to the demand structure, and variables related to the infrastructure. Some of the factors that contribute to increase bus bunching are: stops located toward the end of the route, high scheduled frequency, irregular bus dispatch headways, non-homogeneous fleet, high demand, and high variability of demand. The results are useful for the design of quality indexes to measure bunching in bus operations, and for the design and operation of bus routes, taking into consideration the potential bus bunching problems.
Rights
Permission to publish the abstract has been given by Taylor&Francis, copyright remains with them.
Recommended Citation
Arriagada, J., Gschwender, A. Munizaga, M., & Trépanier, M. (2019). Modeling bus bunching using massive location and fare collection data. Journal of Intelligent Transportation Systems, Vol. 23, pp. 332-344.
