How big data drives intelligent transportation

America has been built and shaped by its ability to move people and goods freely and quickly, fueled by oil. But this “freedom” comes at a cost. Transportation is America’s number-two consumer cost after housing. American drivers pay $8,000 a year for an auto they drive only 4 percent of the time.

According to RMI research, using vehicles more productively can provide the same or better access to transportation services with 46–84 percent less driving. Fortunately, we can now access and share detailed transportation data on an unprecedented scale, allowing creative software app developers to expand and enhance our mobility options. It all amounts to an emerging new transportation paradigm.

Imagine, for example, this scenario:

While eating breakfast, you receive a notification on your smartphone alerting you to weather-induced traffic delays along your normal route to work. You decide to take the suggested alternative route that will save you 15 minutes. You then reserve parking in a nearby garage at a fraction of the cost because you received a half-price push notification coupon.

While walking to your car, you notice a street lamp with a burnt-out light bulb. You snap a photo with your smartphone and place a work order with the city, and in doing so, qualify yourself for a monthly cash prize drawing.

On your drive, your car alerts you to two potential rideshares along your current route who have five-star ratings, so you agree to pick them up and make a few bucks. When you drop the passengers off, their mobile phones automatically complete the payment transaction.

In the parking garage, you redeem your coupon and pay the discounted daily rate, all on your smartphone, which then automatically logs the location of your parking spot so that it can help you find it later.

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