Pedestrian Trajectory Prediction with Convolutional Neural Networks

by   Simone Zamboni, et al.
KTH Royal Institute of Technology

Predicting the future trajectories of pedestrians is a challenging problem that has a range of application, from crowd surveillance to autonomous driving. In literature, methods to approach pedestrian trajectory prediction have evolved, transitioning from physics-based models to data-driven models based on recurrent neural networks. In this work, we propose a new approach to pedestrian trajectory prediction, with the introduction of a novel 2D convolutional model. This new model outperforms recurrent models, and it achieves state-of-the-art results on the ETH and TrajNet datasets. We also present an effective system to represent pedestrian positions and powerful data augmentation techniques, such as the addition of Gaussian noise and the use of random rotations, which can be applied to any model. As an additional exploratory analysis, we present experimental results on the inclusion of occupancy methods to model social information, which empirically show that these methods are ineffective in capturing social interaction.


page 13

page 14


HGCN-GJS: Hierarchical Graph Convolutional Network with Groupwise Joint Sampling for Trajectory Prediction

Accurate pedestrian trajectory prediction is of great importance for dow...

Probability Trajectory: One New Movement Description for Trajectory Prediction

Trajectory prediction is a fundamental and challenging task for numerous...

An End-to-End Learning Approach for Trajectory Prediction in Pedestrian Zones

This paper aims to explore the problem of trajectory prediction in heter...

Conditioned Human Trajectory Prediction using Iterative Attention Blocks

Human motion prediction is key to understand social environments, with d...

ForceFormer: Exploring Social Force and Transformer for Pedestrian Trajectory Prediction

Predicting trajectories of pedestrians based on goal information in high...

Evaluating Pedestrian Trajectory Prediction Methods for the Application in Autonomous Driving

In this paper, the state of the art in the field of pedestrian trajector...

Convolutional Neural Networkfor Trajectory Prediction

Predicting trajectories of pedestrians is quintessential for autonomous ...

Please sign up or login with your details

Forgot password? Click here to reset