A LUTI microsimulation framework to evaluate long-term impacts of automated mobility on the choice of housing-mobility bundles

Land use–transportation interaction models can be useful planning support systems to assess the long-term implications of emerging transportation technologies like mobility-on-demand and automated vehicles. We propose an agent-based simulation framework ( SimMobility Long-Term ) that uses econometrically robust behavioral models to model the potential impacts of accessibility changes in “car-lite†communities on the choice of housing-mobility bundles. Residential relocation and private mobility holding decisions are jointly considered in a sequential simulation modeling approach. Different types of market responses to the car-lite pilot are modeled through various scenarios via assumptions of changes in model parameters, and compared to a baseline where the car-lite pilot is never implemented. A comparatively vehicle-free study area with a low vacancy rate is chosen to obtain conservative estimates of policy impacts. Our findings indicate that initial awareness of the pilot is quite effective in making the study area more vehicle-free relative to the baseline. However, as market effects start impacting housing prices and bidding results, the vehicle-free gains are significantly reduced due to neighborhood gentrification. In conclusion, we highlight how land use–transportation interaction models can be used to explore market dynamics to see where market pressures matter, along with the need to align car-lite policies with market conditions regarding vacancy and car ownership rates.