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Perfectly coordinated travel in and around cities is everybody’s dream. Could an intelligent multimodal system make it a reality?

Urban transport networks are diverse and complex ecosystems. In most cities, there are several different types of transport to choose from. Metros, buses, trams and main line rail are the core. Meanwhile, the number of new “on-demand” modes – from ride-hailing to e-scooters – increases every day. 

There’s certainly no shortage of choice. But what’s missing is overall coordination of the transport offer. While public modes of transport – such as metro lines – are actively supervised by their operators, real-time orchestration of transport at the level of an entire city is much harder to achieve. 

Intelligent multimodal supervision could hold the key to solving this problem – and delivering many extra benefits as well.

New mobility challenges

The huge task of managing city and regional transport is typically carried out by public transport authorities (PTAs). As well as taking care of governance, PTAs often have significant operational responsibilities. These include providing passenger information, improving the reliability of services and adapting transport to real-time demand.

The ability to centrally coordinate transport resources is increasingly valuable. First, it holds the key to delivering low-carbon mobility with attractive public transport at the core. Second, seamless mobility stimulates economic growth – and this includes making it easier to stage large cultural and sporting events. Finally, coordination and centralisation of transport data helps PTAs to maintain their relationship with passengers in the face of competition from big tech players. 

How could an intelligent multimodal system help?

To meet the need for enhanced coordination of urban transport resources, transport authorities need a bird’s eye view of the entire transport system of a city in real time. 
Not just metros, but all modes of public transport, including buses, trams and main line trains.

There’s also a need to take the impact of road traffic into account, because this has an impact on overall mobility. For example, a major traffic accident could block roads and bus routes, forcing travellers onto other modes of transport and creating congestion elsewhere in the city. In short, there is a need to understand the full complexity of the transport ecosystem.

An intelligent multimodal system would allow you to monitor every mode, and more. For example, it could provide insights into train occupancy, road congestion, travel times and delays. And thanks to big data tools, it would even allow you to make predictions, so you could anticipate problems before they occur.

The beauty of this approach is that it taps into data that is already available. For example, data streams from existing metro, main line and tram control centres. It could also extract value from real-time traffic information, weather reports, live video data and passenger density levels on trains and platforms, ticketing data and even anonymised mobile phone data. In fact, there is no limit to the type of data that could be integrated.

Could this approach benefit my city?

An intelligent multimodal system would make it possible to orchestrate transport across cities and regions to an extent that has never been possible before. A system of this sort could be implemented one step at a time – it would not all have to be done at once. And it would not require a complex central system, or huge investment. 

You could start with multimodal monitoring to get a clear picture of mobility. Then add data correlation, big data tools and video analytics. Finally, you could make the transition to real-time service optimisation with forecasts, demand analysis and crowd monitoring.

Here are some of the ways an intelligent multimodal system could transform your network:

Decision making tools

Intuitive dashboards and KPIs would provide easy performance monitoring with real-time visibility of transport operations for you and your stakeholders.

Better coordination across all transport modes

New tools would make it possible to adapt your transport offer to real-time demand by making the best use of all available transport resources – boosting resilience and increasing passenger satisfaction.

Enhanced passenger information

Integration of data from all modes of transport would provide you with an unprecedented ability to provide accurate, real-time journey planning. This could be tailored to the individual needs and preferences of each passenger and delivered via smartphone.

Crisis and incident management

It would be possible for you to identify incidents easily anywhere in the city and to resolve them rapidly – for example, by steering passenger flows from one mode of transport to another.

Simulate, optimise and plan

Artificial intelligence could be used to bring your data to life. For example, you could use a digital twin of your network to explore “what if” scenarios and create simulations based on real data. And you could learn from the past with action replays, with big data tools to help you improve operations.