Microsimulation Study Evaluated the Travel, Environment, and Equity Impacts of Single- and Multiple-passenger Automated Taxis in Western Los Angeles.
How Can Automated Vehicles Increase Access to Marginalized Populations and Reduce Congestion, Vehicle Miles Traveled, and Greenhouse Gas Emissions? A Case Study in the City of Los Angeles
Small and low-income areas within major urban regions may be suitable candidates for early deployment of automated shared vehicles because of high demand for low-cost travel alternatives. This study used an open-sourced dynamic agent-based microsimulation model, adopted from the framework originally created by other researchers in 2016, to evaluate the travel, greenhouse gas (GHGs), and equity impacts of single- and multiple-passenger automated taxi scenarios, including free transit fares and a Vehicle Miles Traveled (VMT) tax in the Westside Cities area in Western Los Angeles (LA).
For the LA dynamic agent-based model developed in this study, data from LA Metropolitan Planning Organization’s current activity-based travel demand model were used to obtain person-specific travel plans corresponding to person-specific socio-economic attributes, including household income, household size, ethnicity, gender, employment, educational attainment, and access to personal vehicles. Four policy scenarios were considered. These were: (1) a single-passenger automated taxi service with a minimum fare of four dollars and a distance-based fare of $0.55 per mile, (2) a multiple-passenger automated taxi service that allows up to four people to share a ride with a minimum fare of two dollars and a distance-based fare of $0.15 per mile, (3) a free transit by reducing the daily cost of transit from seven dollars in the base case scenario to free ride, (4) a VMT tax policy by doubling the distance-based fee for personal vehicle travel ($0.16 per mile) in the base case scenario to $0.32 per mile. In the end, three specific scenarios were tested based on the policy scenarios described. These were Scenario A: automated taxis only (Auto-Taxi Scenario), Scenario B: automated taxis plus free transit (+Free Transit Scenario), and Scenario C: automated taxis plus free transit and the VMT tax (+VMT Tax Scenario). The size of the automated taxi fleet in the model was dynamically re-adjusted to keep 90 percent of all wait times for single-passenger and multiple-passenger below 10 minutes and 15 minutes, respectively.
- The simulation results indicated that automated taxis increased VMT by about 20 percent across scenarios.
- The simulation results showed that transit travel in Scenario A (automated taxis only) decreased by about 50 percent. However, the addition of free transit fares reversed this decline and increased transit use by about eight percent compared to the base case. Scenario C further increased transit travel (about 51 percent increase compared to the base case).
- GHGs declined by 23 to 26 percent when automated taxis are battery electric vehicles. However, GHG emissions could increase from 16 to 18 percent across scenarios when automated taxis are non-battery electric vehicles.
- The equity analysis showed that Scenario A provided more accessibility benefits for travelers in three low-income classes (i.e., low, very low, extremely low income classes) than total benefits and benefits for the middle- and high-income travelers. For the extremely low-income category, travel accessibility benefits increased by 394 percent. Scenario B further increased benefits for extremely low income class. It is worth noting that the VMT tax eliminated almost all of the benefits brought by the automated taxi and free transit scenarios, led to losses for all three low-income groups.