A Two-Layer Switching based Trajectory Prediction Method
Sprache des Titels:
Englisch
Original Buchtitel:
IEEE
Original Kurzfassung:
Abstract?Safety-critical situations in road traffic often result
from incorrect estimation of the future behavior of other road
users. Therefore, many Advanced Driver Assistance Systems
(ADAS) need prediction models to ensure safety. Physical
prediction models offer the advantage of general use and
work quite well for short prediction horizons, while for longer
periods of time, maneuver based models offer better performance
which, however, strongly depends on the data used
to train them. An additional challenge for prediction is the
fact that the surrounding traffic can change its path, i.e.
for safety not only one maneuver should be considered but
regular updates are required. Against this background, we
propose a method that uses three physics-based predictions ?
corresponding to different prediction assumptions and models
? combined with possible maneuver-based trajectories derived
from environmental knowledge. Continuous monitoring is used
to select the most likely of the three physics-based models. This
choice then influences the environment-based prediction and the
output of both models is fused afterwards. The output of the
resulting Multiple Model Trajectory Prediction (MMTP) has
been validated with measured data from two different scenarios
? a city junction and a highway ? with a good prediction
performance and without the need for special measurements
as commonly required for maneuver-based prediction.
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