Surrounding vehicles' lane change maneuver prediction and detection for intelligent vehicles: A comprehensive review
R Song, B Li - IEEE Transactions on Intelligent Transportation …, 2021 - ieeexplore.ieee.org
Identifying and evaluating the potential risks in the surrounding environment is critical for
intelligent vehicles' safety and user experience. This paper provides a comprehensive …
intelligent vehicles' safety and user experience. This paper provides a comprehensive …
Convolutional social pooling for vehicle trajectory prediction
N Deo, MM Trivedi - Proceedings of the IEEE conference on …, 2018 - openaccess.thecvf.com
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 …
deployed in complex traffic. Motion of all vehicles in a scene is governed by the traffic …
An LSTM network for highway trajectory prediction
F Altché, A de La Fortelle - 2017 IEEE 20th international …, 2017 - ieeexplore.ieee.org
In order to drive safely and efficiently on public roads, autonomous vehicles will have to
understand the intentions of surrounding vehicles, and adapt their own behavior …
understand the intentions of surrounding vehicles, and adapt their own behavior …
Graph-based spatial-temporal convolutional network for vehicle trajectory prediction in autonomous driving
Forecasting the trajectories of neighbor vehicles is a crucial step for decision making and
motion planning of autonomous vehicles. This paper proposes a graph-based spatial …
motion planning of autonomous vehicles. This paper proposes a graph-based spatial …
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 …
need to have the ability to predict the future motion of surrounding vehicles. Multiple …
Grip: Graph-based interaction-aware trajectory prediction
Nowadays, autonomous driving cars have become commercially available. However, the
safety of a self-driving car is still a challenging problem that has not been well studied …
safety of a self-driving car is still a challenging problem that has not been well studied …
How would surround vehicles move? a unified framework for maneuver classification and motion prediction
Reliable prediction of surround vehicle motion is a critical requirement for path planning for
autonomous vehicles. In this paper, we propose a unified framework for surround vehicle …
autonomous vehicles. In this paper, we propose a unified framework for surround vehicle …
Tpnet: Trajectory proposal network for motion prediction
Making accurate motion prediction of the surrounding traffic agents such as pedestrians,
vehicles, and cyclists is crucial for autonomous driving. Recent data-driven motion prediction …
vehicles, and cyclists is crucial for autonomous driving. Recent data-driven motion prediction …
Modeling vehicle interactions via modified LSTM models for trajectory prediction
The long short-term memory (LSTM) model is one of the most commonly used vehicle
trajectory predicting models. In this paper, we study two problems of the existing LSTM …
trajectory predicting models. In this paper, we study two problems of the existing LSTM …
Use of social interaction and intention to improve motion prediction within automated vehicle framework: A review
Human errors contribute to 94%(±2.2%) of road crashes resulting in fatal/non-fatal
causalities, vehicle damages and a predicament in the pathway to safer road systems …
causalities, vehicle damages and a predicament in the pathway to safer road systems …