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How will predictive analytics help public transportation?

By September 3, 2018 No Comments

Many parts of the public sector require advanced technology to make sound decisions outside the context of the political arena. This is never more important than in the field of public transportation. Whether it's bus service, commuter rail, subway or light rail, transit agencies have a keen interest in ensuring passengers reach their destination on time and safely. Considering the friction inherent in a lot of different services along with real-world elements such as cars and pedestrians, there is a need to keep efficient operations going in different ways. Performance analysis software that utilizes predictive analytics can help organizations deal with all these and keep things running smoothly.

Outside the trains run on time
Public transportation's pain points are many, as noted by Mass Transit magazine. Most agencies, especially those in the U.S., operate on deficits. Many of them are often forced to run their trains without supporting funds from state or municipal governments. Budgetary pressures are a constant, especially in an era of austere local government. At the same time, more people are taking the subway or bus to work. Since 1995, the number of passengers grew from 7.7 billion as noted by Mass Transit to 10.7 billion, according to the American Public Transportation Association.

Public transportation can benefit from predictive analytics.Public transportation can benefit from predictive analytics.

As a consequence, any technology that can improve efficiency on a "more is less" paradigm makes things a lot easier for both transit agencies and the passengers they serve. Predictive analytics can fill that role to some degree. It helps answer the question of "What's the best possible outcome?" instead of explaining prior history. In this regard, it can help with many different capacities, from vehicle fleet maintenance to planning new lines of service when possible. Wired suggested a few ideas that could help substantially improve operations by accounting for environmental factors.

One of these includes the impact of closures and construction on local transportation infrastructure. Another is taking into account labor actions such as a workers' strike. Most important of these is detecting issues on the transit infrastructure such as the rails. Such practices are already being developed around the world. Southeast Asian news site Today Online reported the deployment of predictive technology is under consideration at Singapore's Land Transport Authority, which handles the public transit system in the city-state. The goal of this system was to identify areas within the rail network that may cause problems so workers can fix them before they invoke a slowdown in efficiency or an accident.

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