Autonomous mobility on demand in SimMobility: Case study of the central business district in Singapore

—Autonomous mobility on demand (AMOD) has emerged as a promising solution for urban transportation. Compared to prevailing systems, AMOD promises sustainable, affordable personal mobility through the use of self-driving shared vehicles. Our ongoing research seeks to design AMOD systems that maximize the demand level that can be satisfactorily served with a reasonable fleet size. In this paper, we introduce an extension for SimMobility—a high-fidelity agent-based simulation platform— for simulating and evaluating models for AMOD systems. As a demonstration case study, we use this extension to explore the effect of different fleet sizes and stations locations for a station-based model (where cars self-return to stations) and a free-floating model (where cars self-park anywhere). Simulation results for evening peak hours in the Singapore Central Business District show that the free-floating model performed better than the station-based model with a “small number” of station...

• Type: Journal
• Year: 2015
• Where: RAM
• Authors: Katarzyna Anna Marczuk, Harold Soh Soon Hong, Carlos Miguel Lima Azevedo, Muhammad Adnan, Scott Drew Pendleton, Emilio Frazzoli, Der-Horng Lee
• Keywords: RAM 2015, Robotics