no code implementations • 22 Jun 2022 • Aravinda Ramakrishnan Srinivasan, Yi-Shin Lin, Morris Antonello, Anthony Knittel, Mohamed Hasan, Majd Hawasly, John Redford, Subramanian Ramamoorthy, Matteo Leonetti, Jac Billington, Richard Romano, Gustav Markkula
Even though the models' RMSE value differed, all the models captured the kinematic-dependent merging behavior but struggled at varying degrees to capture the more nuanced courtesy lane change and highway lane change behavior.
Behavior of each of the surrounding vehicles is governed by the motion of its neighbor vehicles.
Accordingly, our model employs a set of maneuver-specific anchor trajectories that cover the space of possible outcomes at the roundabout.
There is quickly growing literature on machine-learned models that predict human driving trajectories in road traffic.
From this, we devised a qualitative representation of the task space to abstract the decision making, irrespective of the number of obstacles.