EcoRacer: Game-based optimal electric vehicle design and driver control using human players

Yi Ren, Alparslan Emrah Bayrak, Panos Y. Papalambros

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    5 Scopus citations

    Abstract

    We investigate the cost and benefit of crowdsourcing solutions to an NP-complete powertrain design and control problem. Specifically, we cast this optimization problem as an online competition, and received 2391 game plays by 124 anonymous players during the first week from the launch. We compare the performance of human players against that of the Efficient Global Optimization (EGO) algorithm. We show that while only a small portion of human players can outperform the algorithm in long term, players tend to formulate good heuristics early on, from where good solutions can be extracted and used to constrain the solution space. Incorporating this constraint into the search enhances the efficiency of the algorithm, even for problem settings different from the game. These findings indicate that human computation is promising in solving comprehensible and computationally hard optimal design and control problems.

    Original languageEnglish
    Title of host publication41st Design Automation Conference
    ISBN (Electronic)9780791857076
    DOIs
    StatePublished - 2015
    EventASME 2015 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2015 - Boston, United States
    Duration: 2 Aug 20155 Aug 2015

    Publication series

    NameProceedings of the ASME Design Engineering Technical Conference
    Volume2A-2015

    Conference

    ConferenceASME 2015 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE 2015
    Country/TerritoryUnited States
    CityBoston
    Period2/08/155/08/15

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