Time-of-Flight Imaging in Fog Using Polarization Phasor Imaging by Yixin Zhang, Xia Wang, Yuwei Zhao, Yujie Fang

“…The problem limits ToF imaging to be applied in outdoor settings, such as autonomous driving. To improve the quality of the images captured by ToF cameras, we propose a polarization phasor imaging method for image recovery in foggy scenes. …”
Get full text

Optimal Duration of In-Vehicle Data Recorder Monitoring to Assess Bus Driver Behavior by Rachel Shichrur, Navah Z. Ratzon

“…Vision-based technology (VBT) from Mobileye Inc. is an emerging technology for monitoring driver behavior and enhancing safety in advanced driver assistance systems (ADASs) and autonomous driving. VBT detects hazardous driving events by assessing distances to vehicles. …”
Get full text

A Brief Review of Multipath TCP for Vehicular Networks by Luomeng Chao, Celimuge Wu, Tsutomu Yoshinaga, Wugedele Bao, Yusheng Ji

“…The vehicular Internet-of-Things systems, such as cooperative autonomous driving, require reliable high speed data transmission and robustness. …”
Get full text

Survey of Rigid Object Pose Estimation Algorithms Based on Deep Learning by GUO Nan, LI Jingyuan, REN Xi

“…Rigid object pose estimation aims to obtain 3D translation and 3D rotation information of the rigid object in the camera coordinate system,which plays an important role in rapidly developing fields such as autonomous driving,robotics and augmented reality.The representative papers on rigid object pose estimation based on deep learning from 2017 to 2021 are summarized and analyzed.The rigid object pose estimation methods are divided into coordinate-based,keypoints-based and template-based me-thods.The rigid object pose estimation task is divided into four sub-tasks:image preprocessing,spatial mapping or feature ma-tching,pose recovery,and pose optimization.The subtask realization of each method and its advantages and problems are introduced in detail.The challenges of rigid object pose estimation are analyzed,and the existing solutions and their advantages and disadvantages are summarized.Based on the rigid object pose estimation method,the articulated object and deformable object pose estimation are analyzed.The common datasets and performance evaluation indexes of rigid object pose estimation are introduced,and the performance of existing methods on common datasets is compared and analyzed.Finally,the future research directions of pose tracking and class rigid object pose estimation are prospected.…”
Get full text

A Risk-Based Decision-Making Process for Autonomous Trains Using POMDP: Case of the Anti-Collision Function by Mohammed Chelouati, Abderraouf Boussif, Julie Beugin, El-Miloudi El-Koursi

“…By consistently maintaining an acceptable risk level through ongoing risk estimation (in terms of occurrence probability and severity degree), the approach supports the decision-making capabilities of the autonomous driving system in autonomous trains, enabling safe and informed decisions despite the uncertainties in the train’s operational state and environmental conditions. …”
Get full text

Ego Vehicle Lane Detection and Key Point Determination Using Deep Convolutional Neural Networks and Inverse Projection Mapping by Bolimera Anudeepsekhar, Muthalagu Raja, Kalaichelvi V., Singh Abhilasha

“…Ego lane detection is one of the key techniques in Ego Lane Analysis System (ELAS) implemented in smart autonomous driving cars for lane detection in roads. This technique has been extensively studied in recent years because of its accurate and robust detection of shape and location of lanes. …”
Get full text

A novel dilated convolutional neural network model for road scene segmentation by Yachao Zhang, Yuxia Yuan

“…Road scene understanding is one of the important modules in the field of autonomous driving. It can provide more information about roads and play an important role in building high-precision maps and real-time planning. …”
Get full text

Vibration and Image Texture Data Fusion-Based Terrain Classification Using WKNN for Tracked Robots by Hui Wang, En Lu, Xin Zhao, Jialin Xue

“…Finally, the experimental results verify that the proposed method improves the terrain classification accuracy of the tracked robot and provides a basis for improving the stable autonomous driving of tracked vehicles.…”
Get full text

The Graph Neural Network Detector Based on Neighbor Feature Alignment Mechanism in LIDAR Point Clouds by Xinyi Liu, Baofeng Zhang, Na Liu

“…Three-dimensional (3D) object detection has a vital effect on the environmental awareness task of autonomous driving scenarios. At present, the accuracy of 3D object detection has significant improvement potential. …”
Get full text

Real Pseudo-Lidar Point Cloud Fusion for 3D Object Detection by Xiangsuo Fan, Dachuan Xiao, Dengsheng Cai, Wentao Ding

“…Three-dimensional object detection technology is an essential component of autonomous driving systems. Existing 3D object detection techniques heavily rely on expensive lidar sensors, leading to increased costs. …”
Get full text

Learning Policies for Automated Racing Using Vehicle Model Gradients by Nathan A. Spielberg, Maximilian Templer, John Subosits, J. Christian Gerdes

“…Safe autonomous driving approaches should be capable of quickly and efficiently learning as professional drivers do, while also using all of the available road-tire friction for safety. …”
Get full text

Traffic lights detection and tracking for HD map creation by Simone Mentasti, Yusuf Can Simsek, Matteo Matteucci

“…In particular, traffic light detection has been a well-known problem in the autonomous driving field. Still, the focus has always been on the light state, not the features (i.e., shape, orientation, pictogram). …”
Get full text

Segmentation Can Aid Detection: Segmentation-Guided Single Stage Detection for 3D Point Cloud by Xueqing Wang, Diankun Zhang, Haoyu Niu, Xiaojun Liu

“…Detecting accurate 3D bounding boxes from point cloud data plays an essential role in autonomous driving. However, improving performance requires more complex models, which come with high memory and computational cost. …”
Get full text

Secure Information Sharing Approach for Internet of Vehicles Based on DAG-Enabled Blockchain by Gangxin Du, Yangjie Cao, Jie Li, Yan Zhuang

“…Vehicles and roadside units (RSUs) can exchange perceptual information and driving experience to enable intelligent transportation applications such as autonomous driving and road condition analysis. However, ensuring secure and efficient information sharing among vehicles is challenging. …”
Get full text

Efficient V2V Communications by Clustering-Based Collaborative Caching by Hiroki Tokunaga, Suhua Tang

“…Vehicle-to-vehicle (V2V) communication plays an important role in enabling autonomous driving. However, when multiple vehicles request the same content, like road conditions, delivering it individually by V2V communication can significantly increase traffic volume, potentially causing congestion in the wireless channel. …”
Get full text

YOLOpeds: efficient real‐time single‐shot pedestrian detection for smart camera applications by Christos Kyrkou

“…Deep‐learning‐based pedestrian detectors can enhance the capabilities of smart camera systems in a wide spectrum of machine vision applications including video surveillance, autonomous driving, robots and drones, smart factory, and health monitoring. …”
Get full text

OTE-SLAM: An Object Tracking Enhanced Visual SLAM System for Dynamic Environments by Yimeng Chang, Jun Hu, Shiyou Xu

“…With the rapid development of autonomous driving and robotics applications in recent years, visual Simultaneous Localization and Mapping (SLAM) has become a hot research topic. …”
Get full text

Depth Estimation using DNN Architecture and Vision-Based Transformers by Kulkarni Uday, Devagiri Shreya B., Devaranavadagi Rohit B., Pamali Sneha, Negalli Nishanth R., Prabakaran V.

“…This is helpful in various applications like robotics, virtual reality, autonomous driving, medical imaging, and so on and so forth. …”
Get full text

Multi-Sensor Fault Detection, Identification, Isolation and Health Forecasting for Autonomous Vehicles by Saeid Safavi, Mohammad Amin Safavi, Hossein Hamid, Saber Fallah

“…The primary focus of autonomous driving research is to improve driving accuracy and reliability. …”
Get full text

STELLAR: A LARGE SATELLITE STEREO DATASET FOR DIGITAL SURFACE MODEL GENERATION by S. Patil, Q. Guo

“…Unlike stereo vision in autonomous driving and mobile imaging, a satellite stereo pair is not captured simultaneously. …”
Get full text