Learning to Navigate Intersections with Unsupervised Driver Trait Inference

09/14/2021
by   Shuijing Liu, et al.
0

Navigation through uncontrolled intersections is one of the key challenges for autonomous vehicles. Identifying the subtle differences in hidden traits of other drivers can bring significant benefits when navigating in such environments. We propose an unsupervised method for inferring driver traits such as driving styles from observed vehicle trajectories. We use a variational autoencoder with recurrent neural networks to learn a latent representation of traits without any ground truth trait labels. Then, we use this trait representation to learn a policy for an autonomous vehicle to navigate through a T-intersection with deep reinforcement learning. Our pipeline enables the autonomous vehicle to adjust its actions when dealing with drivers of different traits to ensure safety and efficiency. Our method demonstrates promising performance and outperforms state-of-the-art baselines in the T-intersection scenario.

READ FULL TEXT
POST COMMENT

Comments

There are no comments yet.

Authors

page 1

page 6

03/02/2018

Identifying Driver Behaviors using Trajectory Features for Vehicle Navigation

We present a novel approach to automatically identify driver behaviors f...
11/11/2021

Driver-Specific Risk Recognition in Interactive Driving Scenarios using Graph Representation

This paper presents a driver-specific risk recognition framework for aut...
09/05/2021

Multi-Agent Variational Occlusion Inference Using People as Sensors

Autonomous vehicles must reason about spatial occlusions in urban enviro...
02/11/2021

Driving Style Representation in Convolutional Recurrent Neural Network Model of Driver Identification

Identifying driving styles is the task of analyzing the behavior of driv...
02/25/2018

An Intelligent Intersection

Intersections are hazardous places. Threats arise from interactions amon...
04/19/2017

Simultaneous Policy Learning and Latent State Inference for Imitating Driver Behavior

In this work, we propose a method for learning driver models that accoun...
01/05/2017

Autoencoder Regularized Network For Driving Style Representation Learning

In this paper, we study learning generalized driving style representatio...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.