May 2022 | Volume 23 No. 2
All Systems Go
Transport systems often don’t talk to each other – ferry schedules don’t necessarily link up with train times, buses don’t stop in the exact location you want, ticket deals may be lacking – but now, using a unique combination of data from the government and private service providers, the pioneering Intermodal Transport Data-Sharing Programme could pave the way for transport operators and payment providers to cooperate and share data to optimise transportation systems.
Dr John Ure, former Director of Telecommunications Research Project (TRP) and research consultant for HKU, came up with the initial idea for the study, and invited the Faculty of Architecture’s Department of Urban Planning and Design to collaborate. The six-month study was funded by the Innovation and Technology Fund, and HKU took on the role of a trusted third party supported by contributions from transport stakeholders such as MTR Corporation Limited, The Kowloon Motor Bus Company (1933) Limited, Citybus Limited and New World First Bus Limited, Octopus Cards Limited and Arup.
“A vital factor underpinning the whole project was HKU’s establishment of a Data Trust, created in compliance with the Personal Data Protection Ordinance and best practices on data security, enabling the University to access and analyse aggregate data on passenger journeys, times of day and routes into and out of Exchange Square in Central,” said Dr Zhou Jiangping, Associate Professor in the Department of Urban Planning and Design.
He explained that HKU’s roles in the project included: compiling data sharing Memorandums of Understanding among different stakeholders, which acted as necessary ‘software’ for the programme; utilising IT mechanisms (such as data hashing algorithms and a secure data transferring software package) and hardware (for example, a secure and dedicated workstation to store the data) that allowed the team to pool, link, share, and analyse the data contributed by different stakeholders, especially local transit operators; and undertaking a pilot research project on intermodal travel at Exchange Square, which demonstrated the value of intermodal data sharing.
Value of intermodal data
The findings have now been published and revealed some interesting facts about – and gaps in – the city’s transport systems and the way data is currently used. “Much of the transport data, especially the value of intermodal transport data had not been fully recognised by the local transit operators,” said Dr Zhou. “For instance, X bus operator did not know how many of its riders also use services of Y bus operators, nor when and where.
“In addition, many transit operators do not have the time and human resources, especially staff with sufficient and up-to-date technological capacities, to fully exploit the various data that they do have.
“Finally, only by putting data from different stakeholders – for example Octopus data from different local transit operators – did we learn better how many local people ride different modes of public transit and how local public transit system can better serve them. Most notably, if we had only Octopus data from one transit operator, for example X bus operator, we found many riders to Exchange Square made only one bus or metro trip on a weekday. We would not know why unless we had trip records of these riders’ Octopus journeys across all modes of transit in Hong Kong. Our collaborators from Arup did a lot to help in this regard.”
A majority of bus boarding (around 78 per cent) for rail-to-bus interchanges occurred at the Exchange Square public transport interchange. Furthermore, almost 90 per cent of these interchanging passengers walked along the north-south corridor of the MTR Central and Hong Kong stations to transfer between the two modes, as indicated by the translucent green arrow.
Proof of concept
The overall aim of the programme was to develop a proof of concept to show that data sharing is possible using a trusted third party model to replace the siloed approach whereby each transport operator or service provider only shares a limited amount of data with government or for the purposes of limited scope, mode-specific research. “Data sharing enables data analytics to reveal insights into travel behaviour where different modes of public transport are involved and to identify where service needs are not being met or where service quality could be improved and when,” said Dr Zhou.
“Many public transport trips involve using services provided by more than one local transit operator. The pooled data from different operators enables us to know better about these trips, and is indispensable for designing and improving a multimodal transport/transit system. Such a system would be beneficial to both individual transit operators and passengers. Of course, it would also have economic and environmental benefits for society too.
“In fact, there has been an emerging system called ‘Mobility as a Service’ (MaaS) in the transport field,” he added. “MaaS is believed to create more win-win situations for different stakeholders such as the government (regulators of transit), transit operators, shared-bike companies, ride-hailing companies, businesses and passengers. A streamlined and convenient intermodal transit trip would entice more people to use public transport, which would be much cleaner and greener than private cars when there are an ever-increasing number of riders.”
Asked how this method of data collection across entities could also be put to use in other areas, Dr Zhou said: “Businesses (for example, credit card data across businesses), environmental protection (such as the different pollutants being expelled by different entities), housing, and infrastructure development.”
Only by putting data from different stakeholders – for example Octopus data from different local transit operators – did we learn better how many local people ride different modes of public transit and how local public transit system can better serve them.
DR ZHOU JIANGPING