Obstacle Detection by Autonomous Vehicles: An Adaptive Neighborhood Search Radius Clustering Approach by Wuhua Jiang, Chuanzheng Song, Hai Wang, Ming Yu, Yajie Yan

“…Finally, an autonomous vehicle platform and the offline autonomous driving KITTI dataset were used to conduct multi-scene comparative experiments between the proposed method and a Euclidean clustering method. …”
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Deep Learning Techniques for Image Recognition and Object Detection by Sharada K., Alghamdi Wajdi, Karthika K., Alawadi Ahmed Hussein, Nozima Gulomova, Vijayan V.

“…Further advances in object identification and picture recognition are anticipated as deep learning develops, with applications in a variety of fields including autonomous driving, surveillance, and medical imaging.…”
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Simultaneous Object Detection and Distance Estimation for Indoor Autonomous Vehicles by Iker Azurmendi, Ekaitz Zulueta, Jose Manuel Lopez-Guede, Manuel González

“…On the one hand, we train the algorithm with the KITTI dataset, which is an autonomous driving vision dataset that provides labels for object detection and distance prediction. …”
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Blockchain for Vehicular Internet of Things: Recent Advances and Open Issues by Chunrong Peng, Celimuge Wu, Liming Gao, Jiefang Zhang, Kok-Lim Alvin Yau, Yusheng Ji

“…The vehicular Internet of Things (IoT) comprises enabling technologies for a large number of important applications including collaborative autonomous driving and advanced transportation systems. …”
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Internet of Intelligent Vehicles (IoIV): An Intelligent VANET Based Computing via Predictive Modeling by Muhammad Haris, Munam Ali Shah, Carsten Maple

“…With the significant research and advancements in technologies, arose new applications such as autonomous driving and augmented/virtual reality. These applications required massive computational resources for the execution of various tasks. …”
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Detection of Targets in Road Scene Images Enhanced Using Conditional GAN-Based Dehazing Model by Tsz-Yeung Chow, King-Hung Lee, Kwok-Leung Chan

“…For instance, in autonomous driving applications, targets such as cars and pedestrians are detected in the road scene video. …”
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Combining Low-Light Scene Enhancement for Fast and Accurate Lane Detection by Changshuo Ke, Zhijie Xu, Jianqin Zhang, Dongmei Zhang

“…Lane detection is a crucial task in the field of autonomous driving, as it enables vehicles to safely navigate on the road by interpreting the high-level semantics of traffic signs. …”
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Towards Strengthening the Resilience of IoV Networks—A Trust Management Perspective by Yingxun Wang, Hushairi Zen, Mohamad Faizrizwan Mohd Sabri, Xiang Wang, Lee Chin Kho

“…Over the past decade or so, considerable and rapid advancements in the state of the art within the promising paradigms of the Internet of Things (IoT) and Artificial Intelligence (AI) have accelerated the development of conventional Vehicular Ad Hoc Networks (VANETS) into the Internet of Vehicles (IoV), thereby bringing both connected and autonomous driving much closer to realization. IoV is a new concept in the Intelligent Traffic System (ITS) and an extended application of IoV in intelligent transportation. …”
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Personalized Driving Styles in Safety-Critical Scenarios for Autonomous Vehicles: An Approach Using Driver-in-the-Loop Simulations by Ioana-Diana Buzdugan, Silviu Butnariu, Ioana-Alexandra Roșu, Andrei-Cristian Pridie, Csaba Antonya

“…This could result in creating more individualized and secure autonomous driving systems that consider the preferences and behavior of the driver.…”
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Change detection in street environments based on mobile laser scanning: A fuzzy spatial reasoning approach by Joachim Gehrung, Marcus Hebel, Michael Arens, Uwe Stilla

“…Automated change detection based on urban mobile laser scanning data is the foundation for a whole range of applications such as building model updates, map generation for autonomous driving and natural disaster assessment. The challenge with mobile LiDAR data is that various sources of error, such as localization errors, lead to uncertainties and contradictions in the derived information. …”
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Spatial Aggregation Net: Point Cloud Semantic Segmentation Based on Multi-Directional Convolution by Guorong Cai, Zuning Jiang, Zongyue Wang, Shangfeng Huang, Kai Chen, Xuyang Ge, Yundong Wu

“…Semantic segmentation of 3D point clouds plays a vital role in autonomous driving, 3D maps, and smart cities, etc. Recent work such as PointSIFT shows that spatial structure information can improve the performance of semantic segmentation. …”
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A Simple and Efficient Time-Sensitive Networking Traffic Scheduling Method for Industrial Scenarios by Qing Li, Dong Li, Xi Jin, Qizhao Wang, Peng Zeng

“…It is suitable for time-sensitive applications and will be widely used in scenarios such as autonomous driving and industrial Internet. IEEE 802.1Qbv proposes a time-aware shaper mechanism, which enables switches to control the forwarding of traffic in port queues according to pre-defined Gate Control List (GCL). …”
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Active Mitigation Strategy of Structure-Borne Vibration with Complex Frequency Spectra from Asymmetric Plate-like Mounting Systems in Next Generation Mobilities by Yang Qiu, Dongwoo Hong, Byeongil Kim

“…Furthermore, sensor placement in future mobility is crucial because when the positions and orientations of sensors are altered by excessive vehicle vibration, it results in the malfunctioning of autonomous driving systems. Smart structure-based active mounting approaches have been developed to reduce engine-induced vibration. …”
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A Multi-Stage Adaptive Copy-Paste Data Augmentation Algorithm Based on Model Training Preferences by Xiaoyu Yu, Fuchao Li, Yan Liu, Aili Wang

“…By using MSACP to transplant the trained optimal weights to an embedded platform, and combining YOLOv3-tiny, the model’s accuracy in detecting traffic signs in autonomous driving scenarios was improved, verifying the effectiveness of the MSACP algorithm in practical applications.…”
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Development of a GPU-Accelerated NDT Localization Algorithm for GNSS-Denied Urban Areas by Keon Woo Jang, Woo Jae Jeong, Yeonsik Kang

“…There are numerous global navigation satellite system-denied regions in urban areas, where the localization of autonomous driving remains a challenge. To address this problem, a high-resolution light detection and ranging (LiDAR) sensor was recently developed. …”
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Enhanced YOLO Network for Improving the Efficiency of Traffic Sign Detection by Yang Cui, Dong Guo, Hao Yuan, Hengzhi Gu, Hongbo Tang

“…One important task for autonomous driving is the precise detection and recognition of road traffic signs. …”
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Transmit BeampattarnOptimization for Automotive MIMO Radar Coexistedwith Communication in V2V Networks by Zheng-Ming Jiang, Pei-Chang Zhang, Lei Huang, Xin He, Ji-Hong Zhang, Mohamed Rihan

“…Due to the flourishing development of vehicle-to-vehicle (V2V) communications and autonomous driving, interference between radar sensing and communication signals becomes a challenging issue. …”
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DSA: Deformable Segmentation Attention for Multi-Scale Fisheye Image Segmentation by Junzhe Jiang, Cheng Xu, Hongzhe Liu, Ying Fu, Muwei Jian

“…With a larger field of view (FOV) than ordinary images, fisheye images are becoming mainstream in the field of autonomous driving. However, the severe distortion problem of fisheye images also limits its application. …”
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VRR-Net: Learning Vehicle–Road Relationships for Vehicle Trajectory Prediction on Highways by Tingzhang Zhan, Qieshi Zhang, Guangxi Chen, Jun Cheng

“…Vehicle trajectory prediction is an important decision-making and planning basis for autonomous driving systems that enables them to drive safely and efficiently. …”
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Vehicle image datasets for image classification by Narong Boonsirisumpun, Emmanuel Okafor, Olarik Surinta

“…Vehicle image recognition is a critical research area with diverse traffic management, surveillance, and autonomous driving systems applications. Accurately classifying and identifying vehicles from images play a crucial role in these domains. …”
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