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Found 13 papers, 1 papers with code
Cooperative Probabilistic Trajectory Forecasting under Occlusion
Occlusion-aware planning often requires communicating the information of the occluded object to the ego agent for safe navigation.
The Impact of Different Backbone Architecture on Autonomous Vehicle Dataset
Object detection is a crucial component of autonomous driving, and many detection applications have been developed to address this task.
Pedestrian Trajectory Forecasting Using Deep Ensembles Under Sensing Uncertainty
For the current research, we consider an encoder-decoder based deep ensemble network for capturing both perception and predictive uncertainty simultaneously.
SalienDet: A Saliency-based Feature Enhancement Algorithm for Object Detection for Autonomous Driving
On the other hand, unknown objects, which have not been seen in training sample set, are one of the reasons that hinder autonomous vehicles from driving beyond the operational domain.
EEG-Fest: Few-shot based Attention Network for Driver's Vigilance Estimation with EEG Signals
A lack of driver's vigilance is the main cause of most vehicle crashes.
Uncertainty estimation of pedestrian future trajectory using Bayesian approximation
Past research on pedestrian trajectory forecasting mainly focused on deterministic predictions which provide only point estimates of future states.
A Quality Index Metric and Method for Online Self-Assessment of Autonomous Vehicles Sensory Perception
The results demonstrate that the proposed evaluation metric accurately assesses the detection quality of camera-based systems in autonomous driving environments.
Attention-based Neural Network for Driving Environment Complexity Perception
The output from the proposed algorithm is a surrounding environment complexity parameter.
EEG-Inception: An Accurate and Robust End-to-End Neural Network for EEG-based Motor Imagery Classification
The proposed CNN model, namely EEG-Inception, is built on the backbone of the Inception-Time network, which showed to be highly efficient and accurate for time-series classification.
A Survey and Tutorial of EEG-Based Brain Monitoring for Driver State Analysis
Then, the EEG signal preprocessing, feature extraction, and classification algorithms for driver state detection are reviewed.
A Computationally Efficient Multiclass Time-Frequency Common Spatial Pattern Analysis on EEG Motor Imagery
The experiment results show the proposed algorithm average computation time is 37. 22% less than the FBCSP (1st winner in the BCI Competition IV) and 4. 98% longer than the conventional CSP method.
Accurate Alignment Inspection System for Low-resolution Automotive and Mobility LiDAR
A misalignment of LiDAR as low as a few degrees could cause a significant error in obstacle detection and mapping that could cause safety and quality issues.
Automatic LiDAR Extrinsic Calibration System using Photodetector and Planar Board for Large-scale Applications
This paper presents a novel automatic calibration system to estimate the extrinsic parameters of LiDAR mounted on a mobile platform for sensor misalignment inspection in the large-scale production of highly automated vehicles.
