An automated driving systems data acquisition and analytics platform
In this paper, an automated driving system (ADS) data acquisition and analytics platform for
vehicle trajectory extraction, reconstruction, and evaluation based on connected automated …
vehicle trajectory extraction, reconstruction, and evaluation based on connected automated …
Deep transfer learning for intelligent vehicle perception: A survey
Deep learning-based intelligent vehicle perception has been developing prominently in
recent years to provide a reliable source for motion planning and decision making in …
recent years to provide a reliable source for motion planning and decision making in …
Benchmarking robustness of 3d object detection to common corruptions
Abstract 3D object detection is an important task in autonomous driving to perceive the
surroundings. Despite the excellent performance, the existing 3D detectors lack the …
surroundings. Despite the excellent performance, the existing 3D detectors lack the …
GNSS/IMU/LiDAR fusion for vehicle localization in urban driving environments within a consensus framework
The continuous, reliable, and accurate acquisition of position information is a fundamental
requirement for autonomous vehicles. It underpins perception, decision-making, and …
requirement for autonomous vehicles. It underpins perception, decision-making, and …
Contaminations on LiDAR sensor covers: Performance degradation including fault detection and modeling as potential applications
Lidar sensors play an essential role in the perception system of automated vehicles. Fault
Detection, Isolation, Identification, and Recovery (FDIIR) systems are essential for increasing …
Detection, Isolation, Identification, and Recovery (FDIIR) systems are essential for increasing …
3-D vehicle detection enhancement using tracking feedback in sparse point clouds environments
In recent years, vehicle detection in intelligent transportation systems using 3D LIDAR point
clouds based on deep neural networks has made substantial progress. However, when the …
clouds based on deep neural networks has made substantial progress. However, when the …
Choice of the miniature inertial optomechanical sensor geometric parameters with the help of their mechanical characteristics modelling
L Kumanchik, M Rezinkina, C Braxmaier - Micromachines, 2023 - mdpi.com
In this paper, the mechanical characteristics of a miniature optomechanical accelerometer,
similar to those proposed for a wide range of applications, have been investigated. With the …
similar to those proposed for a wide range of applications, have been investigated. With the …
A Hybrid Fault Diagnosis Method for Autonomous Driving Sensing Systems Based on Information Complexity
T Jin, C Zhang, Y Zhang, M Yang, W Ding - Electronics, 2024 - mdpi.com
In the context of autonomous driving, sensing systems play a crucial role, and their accuracy
and reliability can significantly impact the overall safety of autonomous vehicles. Despite …
and reliability can significantly impact the overall safety of autonomous vehicles. Despite …
Toward Foundation Models for Inclusive Object Detection: Geometry-and Category-Aware Feature Extraction Across Road User Categories
The safety of different categories of road users comprising motorized vehicles and
vulnerable road users (VRUs) such as pedestrians and cyclists is one of the priorities of …
vulnerable road users (VRUs) such as pedestrians and cyclists is one of the priorities of …
A Survey on the Use of Container Technologies in Autonomous Driving and the Case of BeIntelli
B Acar, MG Augusto, M Sterling… - IEEE Open Journal …, 2023 - ieeexplore.ieee.org
The application of containerization technology has seen a significant increase in popularity
in recent years, both in the business and scientific sectors. In particular, the ability to create …
in recent years, both in the business and scientific sectors. In particular, the ability to create …