Simulation Framework for Rebalancing of Autonomous Mobility on Demand Systems

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ID: 55498
2016
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Abstract
We are observing a disruption in the urban transportation worldwide. The number of cities offering shared-use on-demand mobility services is increasing rapidly. They promise sustainable and affordable personal mobility without a burden of owning a vehicle. Despite growing popularity, on-demand services, such as carsharing, remain niche products due to small scale and rebalancing issues. We are proposing an extension to the traditional carsharing, which is Autonomous Mobility on Demand (AMOD). AMOD provides a one-way carsharing with self- driving electric vehicles. Autonomous vehicles can make the carsharing more attractive to customers as they (i) reduce the operating cost, which is incurred when a manually driven system is unbalanced, and (ii) release people from the burden of driving. This study is built upon our previous work on Autonomous Mobility on Demand (AMOD) systems. Our methodology is simulation-based and we make use of SimMobility, an agent-based microscopic simulation platform. In the current work we focus on the framework for testing different rebalancing policies for the AMOD systems. We compare three different rebalancing methods: (i) no rebalancing, (ii) offline rebalancing, and (iii) online rebalancing. Simulation results indicate that rebalancing reduces the required fleet size and shortens the customers’ wait time.
Reference Key
a2016simulationmatec Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors A., Marczuk Katarzyna;S.H., Soh Harold;M.L., Azevedo Carlos;Der-Horng, Lee;Emilio, Frazzoli;
Journal matec web of conferences
Year 2016
DOI
DOI not found
URL
http://dx.doi.org/10.1051/matecconf/20168101005
Keywords
Engineering (General). Civil engineering (General) Technology business

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