Lane Change Prediction Using Gaussian Classification, Support Vector Classification and Neural Network Classifiers

Authors

  • Olivér Rákos
    Affiliation

    Department of Control for Transportation and Vehicle Systems, Faculty of Transportation Engineering and Vehicle Engineering, Budapest University of Technology and Economics, H-1111 Budapest, Stoczek street 2., Hungary

  • Szilárd Aradi
    Affiliation

    Department of Control for Transportation and Vehicle Systems, Faculty of Transportation Engineering and Vehicle Engineering, Budapest University of Technology and Economics, H-1111 Budapest, Stoczek street 2., Hungary

  • Tamás Bécsi
    Affiliation

    Department of Control for Transportation and Vehicle Systems, Faculty of Transportation Engineering and Vehicle Engineering, Budapest University of Technology and Economics, H-1111 Budapest, Stoczek street 2., Hungary

https://doi.org/10.3311/PPtr.15849

Abstract

It is essential for a driver assistant system’s motion planning to take the vehicles moving in the surroundings into account. One of the most crucial driver intentions which should be predicted is lane changing. It has been investigated whether it is possible to reliably classify lane-changing maneuvers in a highway situation using learning algorithms such as Gaussian-classifier, SVM, and LSTM neural networks. Real vehicle trajectories are extracted from the NGSIM US-101 and I-80 datasets. The input for the classifiers is derived from the trajectory by selecting a subset of the features: lateral and longitudinal position coordinates, longitudinal acceleration, and velocity. In such an environment, the vehicle movement is limited, so it has been tested that how sufficient if only the mean and the variance of the derivative of lateral coordinate was taken as input for the classification had been tested. Different strategies for labeling the input sequences were tested.

Keywords:

behavior prediction, maneuver detection, SVM, LSTM, NGSIM

Published Online

2020-06-30

How to Cite

Rákos, O., Aradi, S., Bécsi, T. (2020) “Lane Change Prediction Using Gaussian Classification, Support Vector Classification and Neural Network Classifiers”, Periodica Polytechnica Transportation Engineering, 48(4), pp. 327–333. https://doi.org/10.3311/PPtr.15849

Issue

Section

Articles