Travel time prediction with LSTM neural network

Yanjie Duan · Yisheng Lv · Fei–Yue Wang

370 citations0/0 files storedIEEE International Conference on Intelligent Transportation Systems (ITSC)

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Traffic Prediction and Management Techniques Transportation Planning and Optimization Hydrological Forecasting Using AI

Abstract

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.

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References

2004Travel-Time Prediction With Support Vector Regression 2015A gradient boosting method to improve travel time prediction 2005Accurate freeway travel time prediction with state-space neural networks under missing data 2001An object-oriented neural network approach to short-term traffic forecasting 1998DynaMIT: a simulation-based system for traffic prediction 2006Application of the ARIMA Models to Urban Roadway Travel Time Prediction - A Case Study 2015Trend Modeling for Traffic Time Series Analysis: An Integrated Study 2003Improving a Travel-Time Estimation Algorithm by Using Dual Loop Detectors

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2020Temporal Multi-Graph Convolutional Network for Traffic Flow Prediction 2018Multi-output bus travel time prediction with convolutional LSTM neural network 2018Learning to Estimate the Travel Time

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