Head of Product @ ClearSlide, ex- product @ Oracle Commerce Cloud, founder @ Strada.io and @ MagicLink.ai
In many major cities, public transportation has been suffering from the decrease in profitability and reliability, as well as poor customer experience. As the global economy continues to shift to an on-demand model, commuters expect more personalized services and more pleasant experience, that rely on technology. Meet Mobility-as-a-Service (MaaS) — a solution that integrates public and private transportation into one system.
Think of using one mobile app for multiple modes of transportation (bike, shared car, train…) to get to your destination and paying one fee for that journey. The payment will be distributed between all operators. The technology will connect vehicles, public transit, and infrastructure with the customers and will offer flexible and safe travel.
In 2019–2024, we will see broader use and adoption of MaaS due to the advancements in IoT and machine learning and the increasing adoption rates of unconventional transportation modes, such as bike- and car-sharing services.
According to ABI Research, MaaS will have a “disruptive impact on traditional transportation modes like car ownership, buses, trains, aviation, taxis and rental cars.”
This idea is being tested around the world and relies heavily on IoT technology. MaaS needs real-time vehicle connectivity and artificial intelligence to plan trips, optimize routes, and shorten travel times. Without knowing each vehicle’s precise location and status, in addition to other data, such as traffic and maintenance information, usability of MaaS will suffer. The mobility algorithm will calculate the most appropriate travel option from the user’s location to the destination and provide the optimal combination of transportation types. Travel options will account for scheduled maintenance (based on asset utilization) and unexpected breakdowns.
While artificial intelligence and route optimization are already at work at Google, Uber, and others, IoT in mass transit is in a nascent phase. Both AI and IoT will become much more widespread in the transportation sector in the next 2–3 years, with IoT accelerating its adoption rate even faster. For example, companies like DENSO use IoT to collect and analyze traffic data to anticipate traffic issues.
A journey planner will be an inherent part of the solution and will unite all means of transportation in a single network. The application will be always aware of each vehicle’s location and status and will provide the users with the precise arrival and departure times for each leg.
There’s a clear benefit to the end user: simplicity of journey planning, shorter travel, and, likely, a lower price. Helsinki rolled out a MaaS solution, which brings together public transportation, taxis, city bikes, and car-sharing services. The app enjoyed strong support from the city and the community.
MaaS future isn’t without caveats. Public transportation, subsidized by the local taxpayers, often has complicated cost structures that may make it difficult to figure out which part of the total fee should be attributed to each of the types of transportation used in a journey. Public mass transit can also be slow to adopt new technologies — and all that can hinder the development of MaaS. Nonetheless, public sector is the backbone of MaaS solutions, which will get people out of private cars into shared transportation mode and benefit economic activity by lowering transportation costs.
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