Free-standing social conversations constitute a yet underexplored setting for human
behavior forecasting. While the task of predicting pedestrian trajectories has received much …

Driving experience and anticipatory driving are essential skills for humans to operate
vehicles in complex environments. In the context of autonomous vehicles, the software must …

对周围车辆轨迹的精确预测可以辅助自动驾驶车辆做出合理的即时决策. 虽然相比传统轨迹预测
算法, 深度学习方法已取得较好效果, 但是自动驾驶车辆在异构高动态复杂变化环境下实现多模 …

Planning the trajectory of the controlled ego vehicle is a key challenge in automated driving.
As for human drivers, predicting the motions of surrounding vehicles is important to plan the …

Motion prediction is a key factor towards the full deployment of autonomous vehicles. It is
fundamental in order to assure safety while navigating through highly interactive complex …

Resolving predicted conflicts is vital for safe and efficient autonomous vehicles (AV). In
practice, vehicular motion prediction faces inherent uncertainty due to heterogeneous …

Generating realistic simulations is critical for autonomous system applications such as self-
driving and humanrobot interactions. However, driving simulators nowadays still have …

Autonomous driving vehicles can effectively improve traffic conditions and promote the
development of intelligent transportation systems. An autonomous vehicle can be divided …

Motion forecasting plays a crucial role in autonomous driving, with the aim of predicting the
future reasonable motions of traffic agents. Most existing methods mainly model the …

This letter presents View-of-Delft Prediction, a new dataset for trajectory prediction, to
address the lack of on-board trajectory datasets in urban mixed-traffic environments. View-of …