Predicting Vehicle Behaviors Over An Extended Horizon Using Behavior Interaction Network

03/03/2019
by   Wenchao Ding, et al.
0

Anticipating possible behaviors of traffic participants is an essential capability of autonomous vehicles. Many behavior detection and maneuver recognition methods only have a very limited prediction horizon that leaves inadequate time and space for planning. To avoid unsatisfactory reactive decisions, it is essential to count long-term future rewards in planning, which requires extending the prediction horizon. In this paper, we uncover that clues to vehicle behaviors over an extended horizon can be found in vehicle interaction, which makes it possible to anticipate the likelihood of a certain behavior, even in the absence of any clear maneuver pattern. We adopt a recurrent neural network (RNN) for observation encoding, and based on that, we propose a novel vehicle behavior interaction network (VBIN) to capture the vehicle interaction from the hidden states and connection feature of each interaction pair. The output of our method is a probabilistic likelihood of multiple behavior classes, which matches the multimodal and uncertain nature of the distant future. A systematic comparison of our method against two state-of-the-art methods and another two baseline methods on a publicly available real highway dataset is provided, showing that our method has superior accuracy and advanced capability for interaction modeling.

READ FULL TEXT
research
10/17/2019

Probabilistic Trajectory Prediction for Autonomous Vehicles with Attentive Recurrent Neural Process

Predicting surrounding vehicle behaviors are critical to autonomous vehi...
research
04/10/2018

Probabilistic Prediction of Vehicle Semantic Intention and Motion

Accurately predicting the possible behaviors of traffic participants is ...
research
04/12/2021

Building Mental Models through Preview of Autopilot Behaviors

Effective human-vehicle collaboration requires an appropriate un-derstan...
research
05/20/2019

Behavior Identification and Prediction for a Probabilistic Risk Framework

Operation in a real world traffic requires autonomous vehicles to be abl...
research
01/26/2023

Predicting Parameters for Modeling Traffic Participants

Accurately modeling the behavior of traffic participants is essential fo...
research
12/18/2018

Multi-Fidelity Recursive Behavior Prediction

Predicting the behavior of surrounding vehicles is a critical problem in...
research
07/11/2016

A Framework for Estimating Long Term Driver Behavior

The authors present a cyber-physical systems study on the estimation of ...

Please sign up or login with your details

Forgot password? Click here to reset