Social interactions for autonomous driving: A review and perspectives
No human drives a car in a vacuum; she/he must negotiate with other road users to achieve
their goals in social traffic scenes. A rational human driver can interact with other road users …
their goals in social traffic scenes. A rational human driver can interact with other road users …
Deep learning-based vehicle behavior prediction for autonomous driving applications: A review
S Mozaffari, OY Al-Jarrah, M Dianati… - IEEE Transactions …, 2020 - ieeexplore.ieee.org
Behaviour prediction function of an autonomous vehicle predicts the future states of the
nearby vehicles based on the current and past observations of the surrounding environment …
nearby vehicles based on the current and past observations of the surrounding environment …
A survey on trajectory-prediction methods for autonomous driving
In order to drive safely in a dynamic environment, autonomous vehicles should be able to
predict the future states of traffic participants nearby, especially surrounding vehicles, similar …
predict the future states of traffic participants nearby, especially surrounding vehicles, similar …
Agentformer: Agent-aware transformers for socio-temporal multi-agent forecasting
Predicting accurate future trajectories of multiple agents is essential for autonomous systems
but is challenging due to the complex interaction between agents and the uncertainty in …
but is challenging due to the complex interaction between agents and the uncertainty in …
Trace and pace: Controllable pedestrian animation via guided trajectory diffusion
We introduce a method for generating realistic pedestrian trajectories and full-body
animations that can be controlled to meet user-defined goals. We draw on recent advances …
animations that can be controlled to meet user-defined goals. We draw on recent advances …
Trajectron++: Dynamically-feasible trajectory forecasting with heterogeneous data
Abstract Reasoning about human motion is an important prerequisite to safe and socially-
aware robotic navigation. As a result, multi-agent behavior prediction has become a core …
aware robotic navigation. As a result, multi-agent behavior prediction has become a core …
Decoupling human and camera motion from videos in the wild
We propose a method to reconstruct global human trajectories from videos in the wild. Our
optimization method decouples the camera and human motion, which allows us to place …
optimization method decouples the camera and human motion, which allows us to place …
Transformer networks for trajectory forecasting
Most recent successes on forecasting the people motion are based on LSTM models and all
most recent progress has been achieved by modelling the social interaction among people …
most recent progress has been achieved by modelling the social interaction among people …
Interaction dataset: An international, adversarial and cooperative motion dataset in interactive driving scenarios with semantic maps
Behavior-related research areas such as motion prediction/planning, representation/
imitation learning, behavior modeling/generation, and algorithm testing, require support from …
imitation learning, behavior modeling/generation, and algorithm testing, require support from …
Human trajectory forecasting in crowds: A deep learning perspective
Since the past few decades, human trajectory forecasting has been a field of active research
owing to its numerous real-world applications: evacuation situation analysis, deployment of …
owing to its numerous real-world applications: evacuation situation analysis, deployment of …