Travel time is one of the key concerns among travelers before starting a trip and also an important indicator of traffic conditions. However, travel time acquisition is time delayed and the pattern of travel time is usually irregular. In this paper, we explore a deep learning model, the LSTM neural network model, for travel time prediction. By employing the travel time data provided by Highways England, we construct 66 series prediction LSTM neural networks for the 66 links in the data set. Through model training and validation, we obtain the optimal structure within the setting range for each link. Then we predict multi-step ahead travel times for each link on the test set. Evaluation results show that the 1-step ahead travel time prediction error is relatively small, the median of mean relative error for the 66 links in the experiments is 7.0% on the test set. Deep learning models considering sequence relation are promising in traffic series data prediction.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Travel time prediction with LSTM neural network


    Contributors:
    Yanjie Duan, (author) / Yisheng Lv, (author) / Fei-Yue Wang, (author)


    Publication date :

    2016-11-01


    Size :

    193703 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Traffic Density Based Travel-Time Prediction With GCN-LSTM

    Katayama, Hiroki / Yasuda, Shohei / Fuse, Takashi | IEEE | 2022


    Passenger Traffic Volume Prediction with LSTM Neural Network

    Wang, Xu / Yang, Linjian / An, Yisheng et al. | British Library Conference Proceedings | 2019


    Travel Demand Prediction using Deep Multi-Scale Convolutional LSTM Network

    Chu, Kai Fung / Lam, Albert Y.S. / Li, Victor O.K. | IEEE | 2018


    Aircraft Trajectory Prediction Using Social LSTM Neural Network

    Xu, Zhengfeng / Zeng, Weili / Chen, Lijing et al. | TIBKAT | 2021


    Short-term traffic flow prediction with LSTM recurrent neural network

    Kang, Danqing / Lv, Yisheng / Chen, Yuan-yuan | IEEE | 2017