Explainable artificial intelligence for autonomous driving: A comprehensive overview and field guide for future research directions
Autonomous driving has achieved significant milestones in research and development over
the last two decades. There is increasing interest in the field as the deployment of …
the last two decades. There is increasing interest in the field as the deployment of …
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 …
nuscenes: A multimodal dataset for autonomous driving
Robust detection and tracking of objects is crucial for the deployment of autonomous vehicle
technology. Image based benchmark datasets have driven development in computer vision …
technology. Image based benchmark datasets have driven development in computer vision …
Explanations in autonomous driving: A survey
The automotive industry has witnessed an increasing level of development in the past
decades; from manufacturing manually operated vehicles to manufacturing vehicles with a …
decades; from manufacturing manually operated vehicles to manufacturing vehicles with a …
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 …
Recent advancements in end-to-end autonomous driving using deep learning: A survey
End-to-End driving is a promising paradigm as it circumvents the drawbacks associated with
modular systems, such as their overwhelming complexity and propensity for error …
modular systems, such as their overwhelming complexity and propensity for error …
Memory-and-anticipation transformer for online action understanding
Most existing forecasting systems are memory-based methods, which attempt to mimic
human forecasting ability by employing various memory mechanisms and have progressed …
human forecasting ability by employing various memory mechanisms and have progressed …
A survey of collaborative machine learning using 5G vehicular communications
SV Balkus, H Wang, BD Cornet… - … Surveys & Tutorials, 2022 - ieeexplore.ieee.org
By enabling autonomous vehicles (AVs) to share data while driving, 5G vehicular
communications allow AVs to collaborate on solving common autonomous driving tasks …
communications allow AVs to collaborate on solving common autonomous driving tasks …
Gaitgci: Generative counterfactual intervention for gait recognition
Gait is one of the most promising biometrics that aims to identify pedestrians from their
walking patterns. However, prevailing methods are susceptible to confounders, resulting in …
walking patterns. However, prevailing methods are susceptible to confounders, resulting in …
A survey of end-to-end driving: Architectures and training methods
Autonomous driving is of great interest to industry and academia alike. The use of machine
learning approaches for autonomous driving has long been studied, but mostly in the …
learning approaches for autonomous driving has long been studied, but mostly in the …