The Impact of Autonomous Vehicles on Land Use: A Scenario Discovery Approach

Authors: Daniel Engelberg*, Massachusetts Institute of Technology
Topics: Urban and Regional Planning, Transportation Geography, Regional Geography
Keywords: uncertainty, land use, autonomous vehicles, scenarios
Session Type: Paper
Day: 4/3/2019
Start / End Time: 8:00 AM / 9:40 AM
Room: Washington 4, Marriott, Exhibition Level
Presentation File: No File Uploaded


Autonomous vehicles are on the horizon and prognosticators across field are projection how this technology will have on the way we travel and live. There is disagreement as to whether autonomous vehicles will encourage concentration of land uses by removing vehicle storage facilities from the core or if autonomous vehicles will encourage continued sprawl by increasing the comfort and functionality of long commutes. This paper argues that urban planning shouldn't attempt to determine which statement is likely to occur; rather, planners should account for all plausible autonomous futures. Using scenario discovery techniques developed in computer science and operations research I examine a wide variety of potential futures. Rather than pre-assuming land use impact, I adjust parameters of such as levels of vehicle adoption, changes in value of time, and changes in roadway capacity to understand how potential implementations of autonomous vehicles are likely to impact the urban landscape. Subsequently, I examine policies to manage the land use impact of autonomous vehicles through each of the scenarios. This includes transportation policies, such as VMT tax, and land use oriented policies, such as urban growth boundaries. The impacts are measured not just in terms of regional urban form, but also in housing prices changes across incomes. This all builds on the work of Gross, which utilized scenarios discovery to understand transportation specific impacts of autonomous vehicles.

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