Naturalistic Driver Intention and Path Prediction using Recurrent Neural Networks

07/26/2018
by   Alex Zyner, et al.
4

Understanding the intentions of drivers at intersections is a critical component for autonomous vehicles. Urban intersections that do not have traffic signals are a common epicentre of highly variable vehicle movement and interactions. We present a method for predicting driver intent at urban intersections through multi-modal trajectory prediction with uncertainty. Our method is based on recurrent neural networks combined with a mixture density network output layer. To consolidate the multi-modal nature of the output probability distribution, we introduce a clustering algorithm that extracts the set of possible paths that exist in the prediction output, and ranks them according to likelihood. To verify the method's performance and generalizability, we present a real-world dataset that consists of over 23,000 vehicles traversing five different intersections, collected using a vehicle mounted Lidar based tracking system. An array of metrics is used to demonstrate the performance of the model against several baselines.

READ FULL TEXT

page 1

page 3

page 6

page 7

page 9

page 10

research
05/15/2018

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

To safely and efficiently navigate through complex traffic scenarios, au...
research
12/18/2018

Attention-based Recurrent Neural Network for Urban Vehicle Trajectory Prediction

As the number of various positioning sensors and location-based devices ...
research
06/23/2020

Probabilistic Crowd GAN: Multimodal Pedestrian Trajectory Prediction using a Graph Vehicle-Pedestrian Attention Network

Understanding and predicting the intention of pedestrians is essential t...
research
09/22/2017

Attention-based Mixture Density Recurrent Networks for History-based Recommendation

The goal of personalized history-based recommendation is to automaticall...
research
10/01/2019

Temporal Multimodal Fusion for Driver Behavior Prediction Tasks using Gated Recurrent Fusion Units

The Tactical Driver Behavior modeling problem requires understanding of ...
research
12/14/2018

Conversational Intent Understanding for Passengers in Autonomous Vehicles

Understanding passenger intents and extracting relevant slots are import...
research
03/07/2020

A Multi-Modal States based Vehicle Descriptor and Dilated Convolutional Social Pooling for Vehicle Trajectory Prediction

Precise trajectory prediction of surrounding vehicles is critical for de...

Please sign up or login with your details

Forgot password? Click here to reset