There are numerous activities in the automotive industry in which a vehicle drives a pre-defined route multiple times such as portable emissions measurement systems testing or real-world electric vehicle range testing. The speed profile is not the same for each drive cycle due to uncontrollable real-world variables such as traffic, stoplights, stalled vehicles, or weather conditions. It can be difficult to compare each run accurately. To this end, this paper presents a method to compare and quantify the repeatability of real-world on-road vehicle driving schedules using dynamic time warping (DTW). DTW is a well-developed computational algorithm which compares two different time-series signals describing the same underlying phenomenon but occurring at different time scales. DTW is applied to real-world, on-road drive cycles, and metrics are developed to quantify similarities between these drive cycles. This methodology is vehicle-agnostic and can be applied to conventional light-duty, hybrid, fully electric or heavy-duty on-road vehicles.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Quantifying Repeatability of Real-World On-Road Driving Using Dynamic Time Warping


    Additional title:

    Sae Technical Papers


    Contributors:

    Conference:

    WCX SAE World Congress Experience ; 2022



    Publication date :

    2022-03-29




    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




    Quantifying Repeatability of Real-World On-Road Driving Using Dynamic Time Warping

    Lobato, Peter / Rayno, Mars / Daily, Jeremy et al. | British Library Conference Proceedings | 2022


    Off road autonomous vehicle modeling and repeatability using real world telemetry via simulation

    Spencer, Matthew P. / Bos, Jeremy P. | British Library Conference Proceedings | 2022


    TIME-WARPING FOR AUTONOMOUS DRIVING SIMULATION

    LUI RICHARD / WITWICKI STEFAN | European Patent Office | 2021

    Free access

    Time-warping for autonomous driving simulation

    LUI RICHARD / WITWICKI STEFAN | European Patent Office | 2020

    Free access

    Speech Recognition using Dynamic Time Warping

    Amin, Talal Bin / Mahmood, Iftekhar | IEEE | 2008