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 …
A review of vision-based traffic semantic understanding in ITSs
J Chen, Q Wang, HH Cheng, W Peng… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
A semantic understanding of road traffic can help people understand road traffic flow
situations and emergencies more accurately and provide a more accurate basis for anomaly …
situations and emergencies more accurately and provide a more accurate basis for anomaly …
Densetnt: End-to-end trajectory prediction from dense goal sets
Due to the stochasticity of human behaviors, predicting the future trajectories of road agents
is challenging for autonomous driving. Recently, goal-based multi-trajectory prediction …
is challenging for autonomous driving. Recently, goal-based multi-trajectory prediction …
Panoptic video scene graph generation
Towards building comprehensive real-world visual perception systems, we propose and
study a new problem called panoptic scene graph generation (PVSG). PVSG is related to …
study a new problem called panoptic scene graph generation (PVSG). PVSG is related to …
Stepwise goal-driven networks for trajectory prediction
We propose to predict the future trajectories of observed agents (eg, pedestrians or vehicles)
by estimating and using their goals at multiple time scales. We argue that the goal of a …
by estimating and using their goals at multiple time scales. We argue that the goal of a …
Overcoming limitations of mixture density networks: A sampling and fitting framework for multimodal future prediction
Future prediction is a fundamental principle of intelligence that helps plan actions and avoid
possible dangers. As the future is uncertain to a large extent, modeling the uncertainty and …
possible dangers. As the future is uncertain to a large extent, modeling the uncertainty and …
Bitrap: Bi-directional pedestrian trajectory prediction with multi-modal goal estimation
Pedestrian trajectory prediction is an essential task in robotic applications such as
autonomous driving and robot navigation. State-of-the-art trajectory predictors use a …
autonomous driving and robot navigation. State-of-the-art trajectory predictors use a …
Human-machine shared driving: Challenges and future directions
Distraction, misjudgement and driving mistakes can significantly affect a driver, resulting in
an increased risk of accidents. There are diverse factors that can cause mistakes in driving …
an increased risk of accidents. There are diverse factors that can cause mistakes in driving …
Unsupervised traffic accident detection in first-person videos
Recognizing abnormal events such as traffic violations and accidents in natural driving
scenes is essential for successful autonomous driving and advanced driver assistance …
scenes is essential for successful autonomous driving and advanced driver assistance …
Road: The road event awareness dataset for autonomous driving
G Singh, S Akrigg, M Di Maio, V Fontana… - IEEE transactions on …, 2022 - ieeexplore.ieee.org
Humans drive in a holistic fashion which entails, in particular, understanding dynamic road
events and their evolution. Injecting these capabilities in autonomous vehicles can thus take …
events and their evolution. Injecting these capabilities in autonomous vehicles can thus take …