… This is to say that intention prediction model learns or encodes probability distributions of
the … [83], recently, proposed a ”generic” intention prediction framework based on Semantic-…

… of probabilistic semantic occupancy layers over space and time, capturing locations of objects
of different classes (ie, vehicles, … by their interaction with our intended route (eg, oncoming …

… EKF for long-term predictions, as they learn a more nuanced motion model. For the …
Probabilistic prediction of vehicle semantic intention and motion,” in 2018 IEEE Intelligent Vehicles …

… Related Work Our work relates to several topics in probabilistic trajectory prediction. Unlike
… represent different driver intentions and behaviors. [27] explores the semantic features in the …

… predict the future semantics, geometry and motion of complex real-world urban scenes and
use this representation to control an autonomous vehicle. … For the purpose of this work, only …

… Our work relates to several topics in probabilistic trajectory prediction. Unlike deterministic …
different driver intentions and behaviors. [18] has shown that there exist semantics in the latent …

… combines intention prediction and trajectory prediction together… The prior trajectories model
with fitted probabilistic density is … vehicles, bioinspired robots, intelligent navigation, semantic …

… probabilistically predict the continuous motions partitioned by discrete driving styles and
intentions, … Fig.3 shows the semantic map and the RGB pixel map for multi-lane highway driving …

… -modal probabilistic prediction structure for autonomous vehicles … motion prediction of each
pair of interacting vehicles. Third, … , “Probabilistic prediction of vehicle semantic intention and …

… goal-state prediction problem which contains both intention (eg left/right turn) and motion …
, we aim at directly predicting vehicle’s behaviors related to its semantic goals. Specifically, we …