Impacts of Shared Autonomous Vehicles on the Travelers’ Mobility

Abstract

In this paper agent-based modeling was used, and simulation of activities were conducted to study both the existing behavior of travelers and the behavior of travelers considering shared autonomous vehicles (SAV). In the modeling framework distance, travel time, travel cost, fleet size and capacities of vehicle types were used as main parameters. Additionally, we created user groups (long commute drivers, car rider, high class income), who are more willing to use SAV. Simulations of the daily plan of activities were performed using Multi-agent Transport simulation tool (MATSim), which applies the concept of co-evolutionary algorithm. Travel plans of around 3000 persons were simulated, and fleet sizes of 20, 50, 100 SAVs were examined. The results showed that 1 SAV can replace 8 conventional vehicles with acceptable average waiting time ranging from 7-10 minutes and usage of 4-seats (shared trip). The utility function that were used in the study showed that the travel time decreased by 17% and the travel distance decreased by 20% after 100 iterations performed on the existing plans. Moreover, the long commuter and high-income travelers can be served by 20 SAV with waiting time of 10 minutes and trip duration of 20 minutes. In this case 1 SAV can replace 6 conventional cars with acceptable average waiting time 10-15 minutes.