Future Destinations 2028
A story about the effect of semi-automated transit planning
A New Day
The electric bus rattled softly as it traversed the outer suburbs of the city, making its way downtown. Alicia rode the bus since she was a small child, in a time when buses had steering wheels, and people to drive them. As she participated in her normal morning commute, she read a news article on her smartphone:
The automation of public transit systems in 2028 was one of the most transformative events for urban transit since ridesharing started in 2015. In the United States, private mobility firms have been forced to share data with municipalities, in order to bolster declining public transit ridership and foster tighter public-private transit integration. Today, Remix, the largest firm in public transit automation, has flipped the technological switch to allow transit planners to create new routes instantly, with the help of a new deep learning A.I. called Bolt.
Alicia’s wearable device vibrated, and she lifted her wrist to see the notification. Bolt had found a new bus route to create, based on ridership data from the previous week. It automatically added the notification to her task list for the day and she put her wrist down to enjoy the view of the city as the bus sped on.
A new system
In the past year, Remix created an integrated transit planning and operations software for public transit agencies who had typically been working with spreadsheets and outdated software. With assistance from the federal government to force private mobility firms to give public agencies access to their data, Remix became the ultimate tool for transit planners — operations, optimization, feedback collection, and planning, in one package.
This set a new precedent for transit agencies who were facing continually-declining ridership in the age of autonomous, private ridesharing services. Transit agencies have always been great at one thing: moving large amounts of people in a short amount of time, for relatively low cost. Ultra-optimization was the means to keeping many cities from switching to private companies as a replacement to their aging public transit systems.
Instead of partnering with agencies to solve their optimization problems, Remix started its own open-source toolkit for transit agencies to use and build powerful products. The ability to integrate all types of systems, sensors, and vehicles became the industry standard in just a few years. No other company could compete with their speed of innovation.
In addition, the toolkit was built with the expectation that machine learning would eventually optimize every piece of connected equipment. Combined with private ridesharing information, traffic data, and passenger sensors — public transit agencies were able to apply tactical methods, test new routes on the same day, and deploy vehicles during periods of extra congestion. Buses came on time more often, trains rarely faced crush loads, and major events seemed to have minimal impacts on service. Thanks to Remix, public transit made a comeback after a decade of withdrawal.
A new route
Alicia stood at her desk, ready to tackle her list of tasks for the day. After replying to a few quick messages, she immediately got to work on creating the new bus route that Bolt suggested she examined. It was a new route based on recent downtown construction causing traffic delays, combined with a new housing development in a nearby suburb that required more transit coverage. Without hesitation, she sent out the new route to her supervisors in an internal message, as well as to potential riders through a Google Maps notification, to gauge their interest.
Within minutes, she received positive feedback from her supervisors as well as some mixed reviews from potential riders. Based on her data, she adjusted some parameters to the route: changing the schedule to operate during rush-hour only. She gathered additional feedback and completed the new route in under an hour. And within seconds of submitting the new line to Remix, Bolt had assigned two test vehicles from the autonomous vehicle pool to run on the trial line starting that afternoon.
A new commute home
The new route started running from the downtown core at 4pm, avoiding the new construction and saving riders 20 minutes each way. It would operate for the next week as a trial line to gather data for Bolt to determine if the agency should turn the new line into a regular route. Regardless of data collection, the ultra-optimization of transit lines, combined with tactical transit strategies, had saved critical time for daily workers and allowed new passengers to use public transit in favor of ridesharing.
In the days following the launch of the Bolt A.I., public transit agencies became stronger players in a highly-segmented urban transportation industry. Remix undercut the market with reduced pricing and their competitors were forced out of play. Remix was the first tool to enable the mass triumph of public transit over private ridesharing, during an era where most people believed “riding the bus” would be a thing of the past.
This is a futurecasting story—read about the project below.
