This study will use an agent-based simulation model (MATSim) for Los Angeles County developed and calibrated with socio-economic and travel data from the South Coast Association of Government (SCAG) new activity-based travel demand model. This is the first application of this dataset since it has become available, and the model will be completed by February of 2020. The SCAG data set provides extensive socio-demographic data at a fine level of geographic detail. This includes continuous data on household income. Travel time and cost influence travel time of day, mode choice, and assignment. The model represents truck travel and all external travel. It also represents owned vehicles, carpooling, transit, ride-hailing, and shared-ride-hailing. The study will use the dynamic ride-sharing module for MATSim. The development of this module was completed just three months ago. The following scenarios will be simulated for and compared to the 2016 model base year:
(1) County-wide dynamic ridesharing with and without automation;
(2) County-wide dynamic ridesharing with and without automation with fleet electrification;
(3) Pricing policies on non-shared vehicle travel (at various price levels, e.g., 50% to 200%) and county-wide dynamic ridesharing with and without automation; and
(4) Pricing policies on non-shared vehicle travel (at various price levels, e.g., 50% to 200%) and county-wide dynamic ridesharing with and without automation with fleet electrification.
Pricing policies may take the form of vehicle miles traveled (VMT) pricing or congestion pricing. The scenarios will be evaluated against the following criteria: VMT, congestion (e.g., average travel time), mode share, and GHGs. Equity analyses will examine the change in accessibility (travel time and cost) for households that are low-income (200% of the poverty level), in disadvantaged areas (as defined by CalEnviroscreen), lack vehicle availability, and in areas with diverse populations.