By Chris Spahr
A unique approach to collecting and distributing transit data was recently unveiled. Publicly launched on May 15, Urban Engines uses spatial analytics and behavioral economics theory to improve city planning and operations. Urban Engines uses the concept of “crowd sensing,” a method of using technology to understand where people congregate and how they move. For example, card swipes at a subway provide basic information on rider location and total travel time. Using algorithms and supplemental data, such as real-time transit schedules, Urban Engines can deduce what is happening at any subway station or on any train at a given time.
The founders of Urban Engines, Shiva Shivakumar and Balaji Prabhakar, believe that congestion is a problem of supply and demand. Supply is the capacity on city buses, trains, and roads. Demand is the share of metro area commuters who want to ride transit or drive cars. Peak hour congestion is a sign of demand overwhelming supply. Using the information supplied by Urban Engines, transportation planners can more successfully meet the demands during peak hours and offer incentives for commuters to travel at different times.
The idea for Urban Engines started in Bangalore, India. While stuck in a huge traffic jam there, Prabhakar, a professor of electrical engineering and computer science, began to think about solutions to congestion. This led him to conduct an experiment with the Indian company, Infosys, and 20,000 of its employees in the city. By offering incentives through a lottery system, many employees of the company adjusted their commute to off-peak hours causing a 17 percent shift in traffic from peak travel times to slightly before or after.
In a later effort by Prabhakar to cut down on morning rush hour travel at Stanford University, his workplace, he conducted an experiment that involved a voluntary enrollment program that used radio-frequency identification tags attached to vehicles to track participants’ arrival times on campus. Incentives for adjusting arrival times, including entry into a raffle that could win participants up to $50, were used to entice people to participate.
Urban Engines is currently working in three cities. In Sao Paulo, Urban Engines has been deployed to help reduce congestion in the city’s bus system. Singapore is implementing incentives to shift commuter travel to off-peak hours on the MRT Railway System. And Washington, D.C. is in the initial phases of deploying Urban Engines for the DC Metro.
Urban Engines offers great promise for reducing congestion while avoiding unnecessary highway expansion and political challenges to congestion pricing. A new service could even correlate the weather with Urban Engines’ commuter data. “When it rains heavily, no one travels. Then when it stops, everyone arrives at once. Cities can use the system to plan for these events,” said Prabhakar.
Chris Spahr is a Graduate Assistant with SSTI.
By Chris Spahr