Interaction-aware motion prediction for autonomous driving: A multiple model kalman filtering scheme

V Lefkopoulos, M Menner, A Domahidi… - IEEE Robotics and …, 2020 - ieeexplore.ieee.org
We consider the problem of predicting the motion of vehicles in the surrounding of an
autonomous car, for improved motion planning in lane-based driving scenarios without inter …

Multi-modal trajectory prediction of surrounding vehicles with maneuver based lstms

N Deo, MM Trivedi - 2018 IEEE intelligent vehicles symposium …, 2018 - ieeexplore.ieee.org
To safely and efficiently navigate through complex traffic scenarios, autonomous vehicles
need to have the ability to predict the future motion of surrounding vehicles. Multiple …

Interaction-aware kalman neural networks for trajectory prediction

C Ju, Z Wang, C Long, X Zhang… - 2020 IEEE Intelligent …, 2020 - ieeexplore.ieee.org
Forecasting the motion of surrounding obstacles (vehicles, bicycles, pedestrians and etc.)
benefits the on-road motion planning for intelligent and autonomous vehicles. Complex …

Multiple model unscented kalman filtering in dynamic bayesian networks for intention estimation and trajectory prediction

J Schulz, C Hubmann, J Löchner… - 2018 21st International …, 2018 - ieeexplore.ieee.org
Dynamic Bayesian networks (DBNs) are a popular method for driver intention estimation
and trajectory prediction. To account for hybrid state spaces and non-linear system …

Occupancy flow fields for motion forecasting in autonomous driving

R Mahjourian, J Kim, Y Chai, M Tan… - IEEE Robotics and …, 2022 - ieeexplore.ieee.org
We propose Occupancy Flow Fields, a new representation for motion forecasting of multiple
agents, an important task in autonomous driving. Our representation is a spatio-temporal …

A combined model-and learning-based framework for interaction-aware maneuver prediction

M Bahram, C Hubmann, A Lawitzky… - IEEE Transactions …, 2016 - ieeexplore.ieee.org
This paper presents a novel online-capable interaction-aware intention and maneuver
prediction framework for dynamic environments. The main contribution is the combination of …

Estimation of multivehicle dynamics by considering contextual information

G Agamennoni, JI Nieto… - IEEE Transactions on …, 2012 - ieeexplore.ieee.org
Human drivers are endowed with an inborn ability to put themselves in the position of other
drivers and reason about their behavior and intended actions. State-of-the-art driving …

Improving multi-agent trajectory prediction using traffic states on interactive driving scenarios

C Vishnu, V Abhinav, D Roy… - IEEE Robotics and …, 2023 - ieeexplore.ieee.org
Predicting trajectories of multiple agents in interactive driving scenarios such as
intersections, and roundabouts are challenging due to the high density of agents, varying …

Multi-modal interaction-aware motion prediction at unsignalized intersections

V Trentin, A Artuñedo, J Godoy… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Autonomous vehicle technologies have evolved quickly over the last few years, with safety
being one of the key requirements for their full deployment. However, ensuring their safety …

Trajectory prediction for heterogeneous traffic-agents using knowledge correction data-driven model

X Xu, W Liu, L Yu - Information Sciences, 2022 - Elsevier
There is a dilemma regarding the accuracy and reality of vehicle trajectory prediction.
Balancing and predicting the effective trajectory is a topic of debate in autonomous driving …