Joint driver intention classification and tracking of vehicles
Paper in proceedings, 2006

In this paper we present and validate a new modelling framework for joint driver intention classification and tracking of vehicles; a framework derived for automotive active safety systems. Such systems require reliable predictions of the traffic situation to act in time when a dangerous situation occur. Our proposal has two main benefits. First, it incorporates the intention of the driver into the vehicle motion model and thereby improves the prediction capability. The result is a multiple motion model where each model corresponds to a specific driver intent. Second, the connection between different driver plans and corresponding motion model enables a formal classification of the most likely driver intention. To validate our concept, we apply the motion model on real data using a particle filter implementation. Initial studies indicate promising performance.

Author

Joakim Gunnarsson

Chalmers, Signals and Systems, Signalbehandling och medicinsk teknik, Signal Processing

Lennart Svensson

Chalmers, Signals and Systems, Signalbehandling och medicinsk teknik, Signal Processing

Fredrik Bengtsson

Chalmers, Signals and Systems

Lars Danielsson

Chalmers, Signals and Systems, Signalbehandling och medicinsk teknik, Signal Processing

Proc. Nonlinear Statistical Signal Processing Workshop, NSSPW

Subject Categories

Signal Processing

More information

Latest update

11/5/2018