The change of transportation landscape from car private ownership to Mobility as a Service (MaaS) is on the way, slowly but surely. Autonomous vehicles have been improved technically and their impact on reducing fatalities (and jobs) has been well documented. Nevertheless, impacts of autonomous vehicle adoption on build environment and land use is not getting enough attention, and urban planners seem to underestimate the importance of this technological shift as disruptive for the urban environment.
Driving Futures, an application developed in 2018 by our amazing collaborator / mentor Ira Winder on the behalf of Gensler, simulates how the transition to MaaS will change the shape of the city, and especially in terms of parking occupancy.
Indeed, it is sometimes said that the combined effect of app-based ride-sharing services and autonomous vehicles could reduce the need for parking spaces by 75 percent or more in the near future. Less parking lots and more "drop-off areas": this will definitely have major influence on city landscape, land use intensity and real estate profitability. How can those complex phenomenon be simulated?
Driving Futures aims at forecasting those trends in a specific urban environment. Taking the example of the city of Boston, the model simulates the evolution of passenger vehicles on a road network and their use of parking in various hypothetical scenarios through the years until the horizon 2030. The interactivity of the model allows participants to adjust numerous variables: years of analysis, annual vehicle trip growth, rides-share and AV equilibriums, and peak adoption years. The model includes projections for vehicle counts, vehicle types, parking space demand, and parking space vacancy.
This model can be reproduced in any other city, as long as specific data on mobility and parking are available. Do not hesitate to contact us to assess the feasibility of the model in your city and to obtain a detailed quote.
Boston, United States