Once you have selected land use density and vehicle use/ownership assumptions, we will suggest an appropriate land use context here.
Select from the below sets of options to identify the appropriate land use context. Some combinations of population density and vehicle use and ownership are not available; if a desired option from one category is disabled, select a different option in the other category.
Enter your predictions about trends between now and 2045 to estimate future vehicle miles traveled (VMT) per capita. Click the name of each prediction category to expand or collapse that category.
Land use density is highly correlated with VMT. Increased density and mixed use development effectively reduces VMT per capita, while less dense, single use development increases VMT per capita.
The future of vehicle technology, ownership, and use could significantly impact VMT. The deployment of autonomous vehicle (AV) technology for public use is expected to increase VMT. The degree to which it does so is highly dependent on cost and regulations around vehicle use, and the predominant ownership model (private or shared ownership).
Increased use of bicycling and walking as modes of transportation can reduce VMT. People's decision to walk or bike is influenced by the degree to which the bicycle and pedestrian environment is safe, comfortable, easy to use, and direct.
Increased transit use can reduce VMT. People's decision to use transit is dependent on the degree to which transit is reliable, convenient, and cost-effective. High-frequency service that competes with the cost and travel time of vehicle travel is the most influential in capturing ridership and reducing VMT.
Improvements to pedestrian and bicycle connections, transit passenger amenities, and access to trip-end mobility services all influence people's ability to travel by non-vehicular modes. Access to shared mobility options can increase the feasibility of relying on non-vehicular modes of travel.
Transportation demand management (TDM) includes a suite of programs, information sharing, and incentives to inform people about all transportation options. The level of effort and strategy put into transportation demand programs can impact commuter travel behavior, and travel behavior to key destinations, reducing VMT overall.
Labor force participation includes the number of people who could be working, who are employed or actively seeking employment. In auto-dependent areas, increases in labor force participation result in an increase in VMT, as a greater proportion of the population have regular commute trips by vehicle.
This considers the proportion of the population that is of driving age, and therefore can independently create VMT. VMT per capita increases when the proportion of people who can drive a vehicle increases, particularly so in auto-dependent areas. In a scenario with 100% Autonomous Vehicles, this factor does not have an impact.
The degree to which the economy grows and results in higher levels of household income influences VMT. Historically, economic growth and growth in household income result in a correlated increase in VMT.
This considers either the uptake or reduction of internet shopping, same-day delivery, on-demand service and food delivery will affect travel and VMT. An increase in deliveries is expected to increase overall VMT per capita, particularly when there is convenience and cost-effectiveness in making multiple, small orders.
This includes changes in people commuting to an office for work and changes in virtual forums that can substitute for in-person social encounters and entertainment. Increased telecommuting and social networking that substitutes for face-to-face encounters reduces VMT per capita.