Public transport interchanges facilitate transfers between a wide range of motorised and nonmotorised transport modes, allowing users to move from feeder modes such as walking, cycling, private vehicles and local feeder buses to rapid transit, high volume modes such as heavy rail, light rail and busways. The efficiency of this transfer, and the size of the catchment, impact the effectiveness of the broader transport network.
The increasing importance of public transport interchanges is linked to the limited opportunity for the growth of single-mode trips in low-density Australian cities. Most public transport interchanges in Australia are attracting passengers from large catchment areas around their stations, through ‘park and ride’, feeder buses, and nonmotorised forms. Understanding these catchment areas is important in interchange planning and public transport integration.
There is a dearth of information on the catchment areas of public transport interchanges, especially in the Australian context. One of the key objectives of this study is to develop a method of determining the access distances, and in delineating the service area, using a network approach.
In this study, the service areas of all the ‘park and ride’ users are delineated using network data analysis, and feeder bus accessibility is assessed. These access distances and catchment area delineation will assist public transport operators in the refinement of existing feeder bus services. This will, in turn, attract an increased segment of the ‘park and ride’ users to the feeder buses.
This research project also provides an opportunity to trial the innovative use of Bluetooth technology implemented in enter/exit restricted areas to better understand the movement of people within public transport interchanges, and compare the results with traditional methods of monitoring.
The study was undertaken at the Paradise O-Bahn busway interchange in suburban Adelaide, using both face-to-face and Bluetooth surveys. The origins of private cars were retrieved and visualised using GIS. This study also made use of Omnia technology Bluetooth devices and ‘Addinsight‘ to track the vehicles parked in the interchange, to extract travel pattern. Using the geocoded data, the trip distances were calculated for the corresponding networks.
This study extracted Origin and Destination (OD) patterns of passengers arriving at the interchange and compared it with the actual OD pattern obtained from a face-to-face survey. An accurate estimation of public transport OD will significantly aid public agencies involved in route rationalisation, with the potential to lead to higher usage of public transport, and deliver a lower carbon outcome. The geocoded service areas identified in this work will also help to identify the appropriate feeder routes to the interchange and to enhance connectivity.
The study shows there is a spatial mismatch of the bus feeder network and the homes of ‘park and ride’ users of Adelaide’s Paradise O-Bahn busway interchange; that is, only 37% live within 400 metres (walkable areas) of the existing bus feeder service. This finding highlights the need for improving the feeder coverage to increase the usefulness of the interchange and to reduce car parking demand at the interchange.
This study makes several key contributions by identifying different mode catchment areas, using both traditional and new technology tools:
The analysis shows that ‘park and ride’ users travel significant distances to reach interchanges where high-frequency public transport is available. As per the traditional survey, the average distance and 85th percentile distances are 5.1 and 6.9 kilometres, respectively.
The analysis of Bluetooth probe data, using Addinsight tracking stations, reveals a lower average distance of 3.5 km; however, the 85th percentile distance from Bluetooth analysis shows a higher value of 7.75 km.
This discrepancy can be attributed to the need to ensure complete coverage of Addinsight tracking stations; however, the travel patterns from both studies match closely. It is concluded that to determine the interchange catchment area, Bluetooth technology can be applied to replace traditional face-to-face surveys if adequate Addinsight stations are installed.
The study also used smartcard (MetroCard) data to determine the catchment area of feeder bus users of the interchange. The analysis shows that, on average, users are travelling 4 km, and the 85th percentile distance is 6.4 km.
Parking accumulation profiles developed from both traditional and Bluetooth technology methods matched.
This study shows that 85th percentile of the number of hours parking is nine hours, indicating that the ‘park and ride’ users in this interchange are long-term parkers.
This research considers various aspects of the role of public transport interchanges in improving public transport patronage, and lowering mobility related greenhouse gas emissions. It also analysed MetroCard data to extract OD pattern of people using the feeder buses and draws conclusions and informs policies regarding effectiveness of the interchange and types of interchange. The results of the research can also inform the design of interfaces to make them more convenient and attractive to users.