Antonio Gschwender

Indirect Measurement of Level of Service Variables for the Public Transport System of Santiago Using Passive Data

Abstract Purpose — The introduction of new technology to public transport systems has provided an excellent opportunity for passive data collection. In this paper, we explore the possibility of automatically generating level of service indicators that could be used for operation planning and monitoring of Transantiago, the public transport system of Santiago, Chile. Design/methodology/approach — After basic processing of the raw automatic vehicle location (AVL) and automatic fare collection (AFC) data, we were able to generate bus speed indicators, travel time measurements and waiting time estimates using data from 1week. The results were compared with manual measures when available. Findings — The advantage is that these measurements and estimates are reliable because they are obtained from large samples and at nearly no cost. Moreover, they can be applied to any set of data with a selected periodicity. Research limitations — The scope of this research is limited to what can be observed with AVL and AFC data. Additional information is required to incorporate other dimensions, such as personal characteristics and/or more detail in the origin/destination (OD) of the trips. Practical implications — Nevertheless, these results are valuable for the planning and operation management of public transport systems because they provide large amounts of information that is difficult and expensive to obtain from direct measurements. Originality/value — This paper proposes tools to obtain valuable information at a low cost. These tools can be implemented in many cities that have certain technological devices incorporated into their public transport systems.

Transit Line Structures in a General Parametric City: The Role of Heuristics

The merits of selected heuristics to obtain transit line structures are analyzed, applying them on a synthetic parametric description of a symmetric city that allows representation of different city types (mostly monocentric, polycentric, or dispersed) and varying number of trips. Predetermined basic strategic designs are used as references for comparison considering operators and users costs. We show that (a) line structures that emerge from heuristics dominate the comparison for most types of cities; (b) these line structures are of the direct type; (c) the virtues of a heuristic depend on the level and, most importantly, the spatial structure of transport demand; and (d) new types of heuristics should take into account the structural characteristics of cities, allowing for potential non-direct-type solutions. The online appendix is available at https://doi.org/10.1287/trsc.2018.0833.

Modeling bus bunching using massive location and fare collection data

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.