With the rise of the concept of Mobility as a Service (MaaS) taking ever more concrete shape as programs such as Helsinki’s Whim offer residents alternatives to traditional mobility options, the importance of the role played by data is becoming increasingly sizable. As these new models integrate different modes of transportation to offer residents service-based solutions to transportation, the interoperability of these once disparate elements of the urban transportation system becomes, for the first time, truly crucial. Shared data will be at the core of these new models, helping to ensure communication between the various modes of transportation, their operators, and users, as well as helping to ensure that the flow of traffic remains consistent and maximally predictable, while the MaaS systems receive up-to-date information enabling dynamic, context-specific changes as necessary.

The development of big data tools and their integration into city infrastructures is an area of much interest and the focus of considerable efforts everywhere from pioneering mobility companies such as Uber and Lyft, whose demand-responsive software employs advanced algorithms to plan journeys; to companies mapping urban environments for autonomous traffic, and cities looking to improve their traffic systems, such as the city of Pittsburgh, Pennsylvania which reduced travel time by 25% following the introduction of a new AI traffic system. 

These applications of big data in traffic systems and transportation are part of a new field dubbed by some as Intelligent Mobility, one which is expected, in an assessment by UK environmental consultancy Temple Group, to rise from its current valuation at over €305 billion to an estimated €1 trillion by 2025.

However, realizing this big data-enabled future of dynamic, efficient transportation will require broad acceptance of open and shared data standards that often continue to hinder the pace of advancement.

Pittsburgh’s Surtrac system

Temple Group report

Shared mobility researchers Susan Shaheen and Adam Cohen offer an overview of the various utilizations of big data in the future of transportation

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