Title
Stochastic Prediction of Lane Change Trajectories for Adaptive Cruise Control
Date Issued
01 July 2017
Access level
open access
Resource Type
conference paper
Author(s)
Universidad Johannes Kepler, Linz
Abstract
This paper presents a stochastic model for motion prediction of vehicles on the motorway. The predicted trajectories can be used for predictive control algorithms of Advanced Driver Assistance Systems such as Adaptive Cruise Control. The model uses as input actual measurements from the vehicles's radar and camera sensor. In order to deal with the prediction uncertainty, a graphical modeling approach is proposed that allows to incorporate the turning indicator signal of a traffic participant. The model is trained and evaluated with real measurements. The potential benefits of such a prediction model are demonstrated for the application of Adaptive Cruise Control where the incorporation of the predicted trajectories lead to a significant improvement of safety and fuel efficiency.
Start page
8907
End page
8912
Volume
50
Issue
1
OCDE Knowledge area
Ingeniería mecánica
Subjects
Scopus EID
2-s2.0-85031808706
Conference
IFAC-PapersOnLine
Sponsor(s)
Este trabajo ha sido financiado por la Agencia Austriaca de Promoción de la Investigación (FFGΣ junto con AVL List GmbH en el marco del proyecto Stochastische Fahrzeugregelung (número de proyecto 850725Σ).
Sources of information:
Directorio de Producción Científica
Scopus