Action Sequence Predictions of Vehicles in Urban Environments using Map and Social Context
Jan-Nico Zaech,Dengxin Dai,Alexander Liniger,Luc Van Gool,Jan-Nico Zaech,Dengxin Dai,Alexander Liniger,Luc Van Gool
This work studies the problem of predicting the sequence of future actions for surrounding vehicles in real-world driving scenarios. To this aim, we make three main contributions. The first contribution is an automatic method to convert the trajectories recorded in real-world driving scenarios to action sequences with the help of HD maps. The method enables automatic dataset creation for this task...
