Want to transform urban transit? Take a cue from Google, and invent a better algorithm. Service-based transportation networks offer a key for cities to address urban traffic congestion, encourage adoption of alternative transit and slash greenhouse gas emissions from the transportation sector, says Ryan Chin, a PhD candidate in the Smart Cities research group at MIT. And it will likely be the company with the best algorithm for managing fleets of cars, bicycles, scooters and other transit options, and up to millions of users, that finds a way to cash in on the “Mobility on Demand” trend.
As Chin explained to me for an article on GigaOM Pro this week (our subscription-based research service), the MoD concept involves a comprehensive system in which city residents would be able to rent an electric car, scooter or bicycle when and where they need it in order to bridge the “last mile” gap in many public transit systems (e.g. getting between the subway station and your final destination).
Rather than having to return a vehicle borrowed from a car-sharing network to the station where you picked it up (two-way car sharing, which is what ZipCar offers), you’d be able to drop it off at a station close to your destination (one-way car sharing), and likewise for bikes.
Daimler has a pilot program called car2go in Germany and Austin, Texas, in which registered members can rent a Smart Fortwo car by the minute, hour or day, and then return it to any unoccupied parking space within a set operation area, and there are also examples of MoD-type services run by advertisers through public-private partnerships, explained Chin.
But we have yet to see a company do for MoD, what Zipcar, U-Haul, Hertz and other companies are now doing for 2-way car sharing: build a lasting business out of it, and push it toward the mainstream.
Here’s where the algorithm comes in: Google won the search business by building a better engine than anyone else. The company that outperforms competitors in MoD — always having a vehicle available within a reasonable time, using the least number of vehicles for the largest number of users — said Chin, will be the one that “builds a better engine based on historic and current data than anyone else.”
As we move into the era of Car 2.0 — in which vehicles are connected to the power grid as well as communication networks — an unprecedented amount of data will be collected regarding about where, when and how we drive, fuel up and get around. The trick is to analyze and manage that data, and turn it into something useful.
With processing power in the arsenal, a company could find itself holding a valuable technology for not only consumer transit networks, but also, we’ve explained over on Pro, corporate fleet managers, electric vehicle charging infrastructure providers and even smartphone app developers.