Hurricane evacuation plays a critical role for effective disaster preparations. Giving accurate traffic prediction to evacuees enables a safe and smooth evacuation. Moreover, reliable traffic state prediction allows emergency managers to proactively respond to changes in traffic conditions. In this paper, we present a deep learning model to predict traffic speeds in freeways under extreme traffic demand, such as a hurricane evacuation. For prediction, we adopt a Long Short-Term Memory Neural Network (LSTM-NN) model. The approach is tested using real-world traffic data collected during hurricane Irma's evacuation for the interstate 75 (I-75), a major evacuation route in Florida. Using LSTM-NN, we perform several experiments for predicting speeds for 5 min, 10 min, and 15 min ahead of current time. The results are compared against other traditional prediction models such as KNN, ANN, ARIMA. We find that LSTM-NN performs better than these parametric and non-parametric models. The proposed method can be integrated with evacuation traffic management systems for a better evacuation operation.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Short-Term Traffic Speed Prediction for Freeways During Hurricane Evacuation: A Deep Learning Approach


    Contributors:


    Publication date :

    2018-11-01


    Size :

    805804 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




    Hurricane evacuation traffic model

    Nakagawa, Anisha / Winder, Ira | IEEE | 2016


    Hurricane Evacuation Traffic Operations

    A. J. Ballard / B. R. Ullman / N. D. Trout et al. | NTIS | 2008


    Short-Term Prediction for the Occurrence Probability of Traffic Incidents in Freeways

    Wang, H. / Wang, W. / China Communications and Transportation Association; Transportation & Development Institute (American Society of Civil Engineers) | British Library Conference Proceedings | 2009


    Traffic Operations for Hurricane Evacuation

    Ballard, Andrew J. | Online Contents | 2007