{"title":"AMoDeus, a Simulation-Based Testbed for Autonomous Mobility-on-Demand Systems","authors":"Claudio Ruch, S. Hörl, Emilio Frazzoli","doi":"10.1109/ITSC.2018.8569961","DOIUrl":null,"url":null,"abstract":"In an autonomous mobility-on-demand (AMoD) system, customers are transported by autonomously driving vehicles in an on-demand fashion. Although these AMoD systems will soon be introduced to cities, their quantitative analysis from a fleet operational and city planning viewpoint remains challenging due to the lack of dedicated analysis tools. In this paper, we introduce AMoDeus, an open-source software package for the accurate and quantitative analysis of autonomous mobility-on-demand systems. AMoDeus uses an agent-based transportation simulation framework to simulate arbitrarily configured AMoD systems with static or dynamic demand. It includes standard benchmark algorithms, fleet efficiency and service level analysis methods and a dedicated graphical viewer that allows in-depth insights into the system. Together with AMoDeus, we publish a typical simulation scenario based on taxi traces recorded in San Francisco. It can be used to test novel fleet control algorithms or as a basis to model more complex transportation research scenarios.","PeriodicalId":395239,"journal":{"name":"2018 21st International Conference on Intelligent Transportation Systems (ITSC)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"59","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 21st International Conference on Intelligent Transportation Systems (ITSC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ITSC.2018.8569961","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 59
Abstract
In an autonomous mobility-on-demand (AMoD) system, customers are transported by autonomously driving vehicles in an on-demand fashion. Although these AMoD systems will soon be introduced to cities, their quantitative analysis from a fleet operational and city planning viewpoint remains challenging due to the lack of dedicated analysis tools. In this paper, we introduce AMoDeus, an open-source software package for the accurate and quantitative analysis of autonomous mobility-on-demand systems. AMoDeus uses an agent-based transportation simulation framework to simulate arbitrarily configured AMoD systems with static or dynamic demand. It includes standard benchmark algorithms, fleet efficiency and service level analysis methods and a dedicated graphical viewer that allows in-depth insights into the system. Together with AMoDeus, we publish a typical simulation scenario based on taxi traces recorded in San Francisco. It can be used to test novel fleet control algorithms or as a basis to model more complex transportation research scenarios.