BusViz: Big Data for Bus Fleets

Abstract

Transit agencies in major cities make hundreds of decisions every day on how to best allocate scarce resources. How adequate and reliable is service on a given bus route? When should capacity be added to a popular route? How should a bus route serve a neighborhood? Transit planners make decisions by using whatever information is available. This information includes ground surveys, public feedback, and a large element of experience and intuition. This paper presents BusViz, a web-based application that helps bus service operators and transit regulators to make better decisions by using large streams of field data to monitor and visualize the performance of bus fleets. The paper describes the system architecture and user interface of the application and illustrates how the Singapore Land Transport Authority is using it to iterate and evaluate ideas with data-driven rigor and to share quality of service statistics with various stakeholders.

Role of Urban Big Data in Travel Behavior Research

“…A web-based application called BusViz was proposed to use passenger fare card data and large streams of sensor data to monitor and visualize the ridership dynamics of the bus system in Singapore. This will not only capture public transit usage but also highlight regional movement patterns visible to bus service operators for better public resource allocation ( 36 ). More recent research efforts have combined smart card information with other types of data, such as vehicle GPS data, to conduct more comprehensive and scalable TB studies ( 37 ).…”

Big Data for transportation and mobility: recent advances, trends and challenges

“…If we rather focus on the application areas where Big Data Analytics has been put to practice, two noted recent contributions evince the increasing relevance of these models in public transport. In [97] a web‐based application called BusViz is proposed to help bus service operators and transit regulators to make better decisions by using large streams of field data aimed to monitor and visualise the performance of bus fleets. The latter work in [98] also focuses on data generated by the bus transport service, analysing 45 million of bus arrival samples to get insights on the urban traffic in the area of Helsinki (Finland).…”

The visual analytics of big, open public transport data – a framework and pipeline for monitoring system performance in Greater Sydney

“…The reporting of real-time vehicle movement data has well-known, significant benefits for many types of transport system userssuch as for emergency response, road authorities/users and public transport agencies/users. The field of transport monitoring from real-time data is well-established, and numerous commercial and academic initiatives have looked at developing these systems in the past few decades (Anwar, Odoni, & Toh, 2016;Marsden & Bonsall, 2006;Mesbah, Currie, Lennon, & Northcott, 2012). Studies with the focus on visual analytics of more volumetric spatiotemporal transport data have had fewer instances or are underdeveloped.…”