Stochastic Prediction of Lane Change Trajectories for Adaptive Cruise Control

  • Dominik Moser (Speaker)

Activity: Talk or presentationContributed talkscience-to-science

Description

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.
Period12 Jul 2017
Event titleThe 20th World Congress of the International Federation of Automatic Control
Event typeConference
LocationFranceShow on map

Fields of science

  • 207109 Pollutant emission
  • 202027 Mechatronics
  • 206001 Biomedical engineering
  • 202 Electrical Engineering, Electronics, Information Engineering
  • 202034 Control engineering
  • 206002 Electro-medical engineering
  • 203027 Internal combustion engines

JKU Focus areas

  • Mechatronics and Information Processing