Scenario Planning Can Help Prepare for a Hard-to-Predict Future
Anthony Flint asks the question: In a time when "new forms of transportation are creating many unknowns," are contemporary streetscape designs fully anticipating the future?
After presenting the example of a development at a prominent corner of Kenmore Square in Boston—a hotel development that "hinges on a complete re-routing of traffic to favor bicyclists and pedestrians, adding big swaths of public space in the process—Flint goes on to pose the significant unknowns challenging all current transportation thinking.
For example, the imminent arrival of autonomous cars may allow narrower streets because driverless cars can essentially tailgate each other. Timed traffic signals, guided by artificial intelligence, will keep things flowing in ways far superior to the red light, green light system of today. Downtowns everywhere won’t have to devote prized urban land for big parking garages or surface lots.
But shared autonomous vehicles may also end up exacerbating Boston’s first-in-the-nation congestion problems. One study predicts that driverless Ubers and Lyfts will be in such continual use, circling the block looking for rides, key streets in major metropolitan areas will see more gridlock than ever before.
Additional technologically advanced mobility mechanisms will also operate in the public realm of the future, like electric scooters and delivery robots. Both are already are already operating in some corners of the United States.
As a tool to anticipate these challenges, Flint suggests scenario planning, described here as allowing planners "to map out multiple scenarios, leaving room for unknowns."
"When conditions on the ground indicate that one of the scenarios is more likely, that’s the trigger for going all-in on infrastructure, policies, and placemaking," according to Flint.