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 …
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 …
Scene transformer: A unified architecture for predicting multiple agent trajectories
Predicting the motion of multiple agents is necessary for planning in dynamic environments.
This task is challenging for autonomous driving since agents (eg vehicles and pedestrians) …
This task is challenging for autonomous driving since agents (eg vehicles and pedestrians) …
A dynamic multi-scale voxel flow network for video prediction
The performance of video prediction has been greatly boosted by advanced deep neural
networks. However, most of the current methods suffer from large model sizes and require …
networks. However, most of the current methods suffer from large model sizes and require …
A survey on safety-critical driving scenario generation—A methodological perspective
Autonomous driving systems have witnessed significant development during the past years
thanks to the advance in machine learning-enabled sensing and decision-making …
thanks to the advance in machine learning-enabled sensing and decision-making …
On adversarial robustness of trajectory prediction for autonomous vehicles
Trajectory prediction is a critical component for autonomous vehicles (AVs) to perform safe
planning and navigation. However, few studies have analyzed the adversarial robustness of …
planning and navigation. However, few studies have analyzed the adversarial robustness of …
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 …
A review of tracking and trajectory prediction methods for autonomous driving
F Leon, M Gavrilescu - Mathematics, 2021 - mdpi.com
This paper provides a literature review of some of the most important concepts, techniques,
and methodologies used within autonomous car systems. Specifically, we focus on two …
and methodologies used within autonomous car systems. Specifically, we focus on two …
Video prediction recalling long-term motion context via memory alignment learning
Our work addresses long-term motion context issues for predicting future frames. To predict
the future precisely, it is required to capture which long-term motion context (eg, walking or …
the future precisely, it is required to capture which long-term motion context (eg, walking or …