Sampling-Based MPC with Learning-Based Trajectory Predictions for Interaction-Aware Motion Planning: Autonomous navigation in urban canals

With the world’s population recently surpassing the 8 billion mark, population growth poses significant challenges on the planet. This growth is particularly evident in urban areas, and as a consequence, cities must find innovative ways to accommodate the increasing pressure on the current road infrastructure. In Amsterdam, a city with an...

Interaction-aware Pedestrian Trajectory Prediction using Monocular Video in Automated Driving

Pedestrian trajectory prediction is essential for developing safe autonomous driving systems. Such trajectories depend on various contextual cues, among which surrounding objects. <br/><br/>This work proposes the first pedestrian trajectory prediction method in the 2D on-board domain that models interactions between the pedestrian and...

HiPSS-LSTM: A Hierarchical Probabilistic LSTM model for motion forecasting

When driving a car, people can usually predict the intention of other road users with high confidence. They can spot small variations in a recent trajectory, take into account road infrastructure, traffic rules and other factors, which influence a future trajectory. As a result, they can interact with other drivers smoothly and safely. Even...