July 27, 2018

Stuck in gridlock, or another train delay? These are problems faced by commuters daily. For decades our public transit systems haven’t been able to support the exponential growth in ridership. With urbanization, public transit and road infrastructure in large cities around the world can’t keep up with the influx of demand.

Take the Bay Area Rapid Transit (BART). In the year it was built, 1972, it carried approximately 170,000 passengers per week. Compare this to 2017 figures which show 429,000 trips each work day.

Investment in the physical infrastructure is lacking, understandably so given it takes vast amounts of money and planning to overhaul subways, train stations, parking lots and roads.

Much of the public transit revolution discussion centers around this upheaval of the physical infrastructure. Such a fear of an investment prevents conversation around finding a solution. Change is overlooked.

This is where the power of data can be leveraged. Faster technology updates and the introduction of smartphones and GPS has changed the way people consume mobility. Ride-sharing apps and transit apps that provide people with step-by-step guidance from point A to B have enabled an entirely new set of valuable data to be added to the picture.

The use of public transit mobility data and people movement data allows for more realistic and short term changes to be made so that commuters benefit from things like improved routes and schedules.

In the past, transit authorities employed people to stand at stations with a clipboard and survey riders about their usage, start and end points and their satisfaction levels. This laborious method doesn’t account for seasonal disparities or external factors. Bring in a company like Moovit, the world’s leading urban mobility data and analytics company with the #1 transit app, and we can directly reach users through app surveys and anonymous movement data and produce visual results in moments, instead of weeks of data gathering. These surveys can be done multiple times per year and repeated year after year to produce meaningful comparisons.

Moovit carried out a study in Boston, Massachusetts looking at traffic gridlock and underutilization of mass transit. Moovit’s proprietary data showed a 50 percent reduction in train travel and commensurate increase in auto traffic from the outlining town of Worcester to downtown Boston after 8:00 a.m. This was not caused by people preferring to drive instead of riding the train, but rather that all the train station parking lots are full by 7:30 a.m. Instead of building more parking lots, another solution is to subsidize and promote local shuttles or ride-sharing services to improve the first-mile transit.

If we use data in a smart way, governments, municipalities and transit authorities can better utilize systems that are already in place and allow for simple A/B testing for improved service to commuters before spending billions on new infrastructure.

No longer will riders expect a poor and delayed journey. Riders are likely to use public transit more and recommend it to others, getting more cars off the roads and ultimately helping the environment and the flow of people. This is why data is where the urban mobility revolution starts.

Roy Bick is the co-founder of Moovit.

The views expressed above are those of the author and do not necessarily reflect the views of the Eno Center for Transportation.