Spatial and temporal visualization of transit operations performance data at a network level

Document Type

Journal Article

Publication Date


Subject Area

technology - automatic vehicle monitoring, technology - geographic information systems, place - australasia, mode - tram/light rail, operations - performance


Public transport, Automatic Vehicle Location (AVL), Automatic Vehicle Monitoring (AVM), Tram, Transit


The operational performance of public transport networks is an important aspect of urban planning and development. Despite the network focus of services and delays which are often focused spatially, little research has examined the spatial pattern of operational performance of urban public transport.

This paper explores the operational performance of on-road public transport using spatial and historical analysis at a network wide level. Operational performance is investigated through analysis of stop level Automatic Vehicle Location (AVL) data and utilizes visualization techniques in geographical information systems (GISs) to explore spatial and temporal patterns of change. The network in question is the Melbourne tram (streetcar) network, which has a large historical dataset of AVL data since 2001 providing information on scheduled arrival times, actual arrival times, times of departure, and more.

Statistical analysis is undertaken to determine average travel times and the standard deviation of travel times. The statistical analysis is then imported into a GIS package for further analysis; the Inverse Distance Weighted (IDW) methodology is used to explore spatial variations in data. Outputs include observation of travel times across the network, a reliability analysis investigating actual vs. scheduled travel times and coefficients of variation, and trend analyses to observe the change in tram travel time and change in coefficient of variation.

Through this analysis, various changes in travel time and reliability were observed between 2001 and 2010. Vast areas saw improvements in travel time and reliability, while some areas were identified to have deteriorated performance. This paper identifies that the spatial representation of large datasets is of great value in an ongoing monitoring of the network and a powerful reporting tool on a network level basis. Moreover, the results identify transit issues for the Melbourne tram network planners for further investigation.


Permission to publish the abstract has been given by Elsevier, copyright remains with them.


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