Transport networks in cities and regional centres are under increasing pressure from escalating customer demand. Fuelled by population growth, increasing urbanisation and expanding customer expectations, governments and private sector transport operators are facing new challenges.
However, despite renewed investment, travel times in most cities continue to increase as our roads become more congested. Our public transport services – buses, trains, trams and ferries – are more frequently crowded. And many transport modes – be it road or rail – are displaying signs of stress as journey times become more unpredictable in the face of unplanned incidents and ever-present maintenance requirements.
A new wave of innovation is now emerging to address these challenges. This will focus on providing end-to-end mobility experiences. This wave of change – labelled as Mobility-as-a-Service (MaaS) – is focused on:
- Providing customers with personalised journey options, based on up-to-minute service and disruption information.
- Integrating journey planning, service booking and payments into a seamless experience.
- Bundling transport services into convenient and cost-effective ‘mobility plans’ – similar to a mobile phone plan for your travel needs.
- Filling gaps in the transport network by offering innovative new transport services for first- and last-mile connectivity.
Edge and Fog computing offers the potential to understand latent transport demand in real-time, and to rapidly assemble insights which can allow MaaS networks to quickly deploy services and get people moving.
Adding edge computing capabilities to MaaS networks and therefore building an IoT Data Fabric has the potential to unlock a new approach to optimising transport networks. The objective here is to deliver a demand-responsive transport ecosystem, where the MaaS network enables multiple mobility operators to detect and understand customer demand in real-time.
The University of New South Wales (UNSW) and Cisco collaborated on a research investigation to explore the utility of real-time transport demand data in the context of emerging Mobility-as-a-Service (MaaS) networks.
The research team captured and measured transport customer experience in terms of waiting time at transit hubs (such as bus stops) and overall journey time (incorporating waiting time and trip times from origin to destination).
The developed framework has shown how improvement in performance and efficiency of future mobility systems can be achieved – delivering benefits for individual travellers and the broader transport network. The outcomes of the project shed light on a promising direction for future exploration and investment that could enable transport agencies and MaaS operators (large and small) to exchange information through a secure IoT data platform.
Learn more in the report: Enabling MaaS Through a Distributed IoT Data Fabric.
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