DeepAI AI Chat
Log In Sign Up

Convolutional Social Pooling for Vehicle Trajectory Prediction

by   Nachiket Deo, et al.
University of California, San Diego

Forecasting the motion of surrounding vehicles is a critical ability for an autonomous vehicle deployed in complex traffic. Motion of all vehicles in a scene is governed by the traffic context, i.e., the motion and relative spatial configuration of neighboring vehicles. In this paper we propose an LSTM encoder-decoder model that uses convolutional social pooling as an improvement to social pooling layers for robustly learning interdependencies in vehicle motion. Additionally, our model outputs a multi-modal predictive distribution over future trajectories based on maneuver classes. We evaluate our model using the publicly available NGSIM US-101 and I-80 datasets. Our results show improvement over the state of the art in terms of RMS values of prediction error and negative log-likelihoods of true future trajectories under the model's predictive distribution. We also present a qualitative analysis of the model's predicted distributions for various traffic scenarios.


page 1

page 8


Multi-Modal Trajectory Prediction of Surrounding Vehicles with Maneuver based LSTMs

To safely and efficiently navigate through complex traffic scenarios, au...

How would surround vehicles move? A Unified Framework for Maneuver Classification and Motion Prediction

Reliable prediction of surround vehicle motion is a critical requirement...

Multi-Head Attention-based Probabilistic Vehicle Trajectory Prediction

This paper presents online-capable deep learning model for probabilistic...

Maneuver-based Anchor Trajectory Hypotheses at Roundabouts

Predicting future behavior of the surrounding vehicles is crucial for se...

An efficient Deep Spatio-Temporal Context Aware decision Network (DST-CAN) for Predictive Manoeuvre Planning

To ensure the safety and efficiency of its maneuvers, an Autonomous Vehi...

Maneuver-Aware Pooling for Vehicle Trajectory Prediction

Autonomous vehicles should be able to predict the future states of its e...