Traditional and electric bicycles are becoming a growing mean of transportation in urban areas. In this study we present an algorithm which predicts the amount of energy a cyclist will deliver for a given route. The main idea of the algorithm is to predict the speed profile the cyclist is going to follow thanks to a bicycle model and a cyclist model combined with infrastructure constraints (e.g. traffic lights). The proposed algorithm is validated on different experimental trips.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Model based cyclist energy prediction


    Contributors:


    Publication date :

    2017-10-01


    Size :

    312904 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    CONTEXT-BASED CYCLIST PATH PREDICTION USING RECURRENT NEURAL NETWORKS

    Pool, Ewoud A. I. / Kooij, Julian F. P. / Gavrila, Dariu M. | British Library Conference Proceedings | 2019


    Cyclist behaviour

    Shrimpton, D. E. / Bicycle Federation of Australia | British Library Conference Proceedings | 1992


    Context-based cyclist path prediction using Recurrent Neural Networks

    Pool, Ewoud A. I. / Kooij, Julian F. P. / Gavrila, Dariu M. | IEEE | 2019


    Using Road Topology to Improve Cyclist Path Prediction

    Pool, Ewoud Alexander Ignacz / Kooij, Julian Francisco Pieter / Gavrila, Dariu M. | British Library Conference Proceedings | 2017