Action sequence predictions of vehicles in urban environments using map and social context
This work studies the problem of predicting the sequence of future actions for surrounding
vehicles in real-world driving scenarios. To this aim, we make three main contributions. The …
vehicles in real-world driving scenarios. To this aim, we make three main contributions. The …
Hierarchical adaptable and transferable networks (hatn) for driving behavior prediction
When autonomous vehicles still struggle to solve challenging situations during on-road
driving, humans have long mastered the essence of driving with efficient transferable and …
driving, humans have long mastered the essence of driving with efficient transferable and …
Predicting vehicles trajectories in urban scenarios with transformer networks and augmented information
A Quintanar, D Fernández-Llorca… - 2021 IEEE Intelligent …, 2021 - ieeexplore.ieee.org
Understanding the behavior of road users is of vital importance for the development of
trajectory prediction systems. In this context, the latest advances have focused on recurrent …
trajectory prediction systems. In this context, the latest advances have focused on recurrent …
Continual interactive behavior learning with traffic divergence measurement: A dynamic gradient scenario memory approach
Developing autonomous vehicles (AVs) helps improve the road safety and traffic efficiency
of intelligent transportation systems (ITS). Accurately predicting the trajectories of traffic …
of intelligent transportation systems (ITS). Accurately predicting the trajectories of traffic …
Interaction-based trajectory prediction over a hybrid traffic graph
Behavior prediction of traffic actors is an essential component of any real-world self-driving
system. Actors' long-term behaviors tend to be governed by their interactions with other …
system. Actors' long-term behaviors tend to be governed by their interactions with other …
A hybrid framework combining vehicle system knowledge with machine learning methods for improved highway trajectory prediction
MM Sánchez, E Silvas, D Pogosov… - … on Systems, Man, and …, 2020 - ieeexplore.ieee.org
Vehicle-to-vehicle communication is a solution to improve the quality of on-road traveling in
terms of throughput, safety, efficiency and comfort. However, road users that do not …
terms of throughput, safety, efficiency and comfort. However, road users that do not …
Trafficpredict: Trajectory prediction for heterogeneous traffic-agents
To safely and efficiently navigate in complex urban traffic, autonomous vehicles must make
responsible predictions in relation to surrounding traffic-agents (vehicles, bicycles …
responsible predictions in relation to surrounding traffic-agents (vehicles, bicycles …
Multimodal trajectory predictions for urban environments using geometric relationships between a vehicle and lanes
A Kawasaki, A Seki - 2020 IEEE International Conference on …, 2020 - ieeexplore.ieee.org
Implementation of safe and efficient autonomous driving systems requires accurate
prediction of the long-term trajectories of surrounding vehicles. High uncertainty in traffic …
prediction of the long-term trajectories of surrounding vehicles. High uncertainty in traffic …
[HTML][HTML] Using Dual Attention BiLSTM to Predict Vehicle Lane Changing Maneuvers on Highway Dataset
In this research, we address the problem of accurately predicting lane-change maneuvers
on highways. Lane-change maneuvers are a critical aspect of highway safety and traffic …
on highways. Lane-change maneuvers are a critical aspect of highway safety and traffic …
A Cognitive-Driven Trajectory Prediction Model for Autonomous Driving in Mixed Autonomy Environment
As autonomous driving technology progresses, the need for precise trajectory prediction
models becomes paramount. This paper introduces an innovative model that infuses …
models becomes paramount. This paper introduces an innovative model that infuses …