A Stackelberg Game-Based Caching Incentive Scheme for Roadside Units in VANETs by Yang Wang, Yuankun Lin, Lingyu Chen, Jianghong Shi

“…To support different applications about traffic safety, traffic efficiency, autonomous driving and entertainment, it is important to investigate how to effectively deliver content in VANETs. …”
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An Internet of Vehicles (IoV) Access Gateway Design Considering the Efficiency of the In-Vehicle Ethernet Backbone by Dae-Young Kim, Minwoo Jung, Seokhoon Kim

“…These days, in-vehicle devices that require high bandwidth is increased for autonomous driving services. Thus, the spread of data for vehicles is exploding. …”
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Shifting Perceptions and Emotional Responses to Autonomous Vehicles Using Simulated Experiences by Jose L. Tapia, David Sánchez-Borda, Carmen Iniesta, Francisco Badea, Jon Andoni Duñabeitia

“…Acceptance was measured in terms of AV knowledge, perception of autonomous driving, and safety, with emphasis on lexical-emotional analysis after simulation. …”
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Dynamic Multi-LiDAR Based Multiple Object Detection and Tracking by Muhammad Sualeh, Gon-Woo Kim

“…Environmental perception plays an essential role in autonomous driving tasks and demands robustness in cluttered dynamic environments such as complex urban scenarios. …”
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Estimating Leaf Water Content through Low-Cost LiDAR by Akira Hama, Yutaro Matsumoto, Nobuhiro Matsuoka

“…In recent years, rapid development has been achieved in technologies and sensors related to autonomous driving and assistive technologies. In this study, low-cost light detection and ranging (LiDAR) was used to estimate leaf water content (LWC) by measuring LiDAR reflectance instead of morphological measurement (e.g., plant size), which is the conventional method. …”
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Lane and Road Marker Semantic Video Segmentation Using Mask Cropping and Optical Flow Estimation by Guansheng Xing, Ziming Zhu

“…Lane and road marker segmentation is crucial in autonomous driving, and many related methods have been proposed in this field. …”
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Dynamic robust analysis of IoV link delay in cellular Telematics and smart edge networking base on deep reinforcement learning by Aijun Kou, Xiaojun Li, Zhiwen Zou

“…Applications for the Internet of Vehicles (IoV) are progressing from more fundamental ones like those for traffic efficiency, road safety, and information services to more sophisticated ones like autonomous driving and intelligent mobility that have a variety of connectivity requirements. …”
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Predictive Analysis of Vehicular Lane Changes: An Integrated LSTM Approach by Hongjie Liu, Keshu Wu, Sicheng Fu, Haotian Shi, Hongzhe Xu

“…In the rapidly advancing domain of vehicular traffic management and autonomous driving, accurate lane change predictions are paramount for ensuring safety and optimizing traffic flow. …”
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DRCNet: Road Extraction From Remote Sensing Images Using DenseNet With Recurrent Criss-Cross Attention and Convolutional Block Attention Module by Debin Wei, Pinru Li, Hongji Xie, Yongqiang Xu

“…Extracting road networks from remote sensing images holds critical implications for various applications including autonomous driving, path planning, and road navigation. …”
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Road Scene Instance Segmentation Based on Improved SOLOv2 by Qing Yang, Jiansheng Peng, Dunhua Chen, Hongyu Zhang

“…Road instance segmentation is vital for autonomous driving, yet the current algorithms struggle in complex city environments, with issues like poor small object segmentation, low-quality mask edge contours, slow processing, and limited model adaptability. …”
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Dynamic activation and enhanced image contour features for object detection by Jun Wu, Jiahui Zhu, Xin Tong, Tianliang Zhu, Tianyi Li, Chunzhi Wang

“…Object detection technology is a popular research direction which is widely used in areas such as autonomous driving and medical diagnosis. At this stage mobile devices often have limited storage resources to deploy large object detection networks and need to meet real-time requirements. …”
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Physics and semantic informed multi-sensor calibration via optimization theory and self-supervised learning by Shmuel Y. Hayoun, Meir Halachmi, Doron Serebro, Kfir Twizer, Elinor Medezinski, Liron Korkidi, Moshik Cohen, Itai Orr

“…We present a holistic approach to performing joint calibration of a camera–lidar–radar trio in a representative autonomous driving application. Leveraging prior knowledge and physical properties of these sensing modalities together with semantic information, we propose two targetless calibration methods within a cost minimization framework: the first via direct online optimization, and the second through self-supervised learning (SSL).…”
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Autonomously Steering Vehicles along Unmarked Roads Using Low-Cost Sensing and Computational Systems by Giuseppe DeRose, Austin Ramsey, Justin Dombecki, Nicholas Paul, Chan-Jin Chung

“…The vast majority of autonomous driving systems are limited to applications on roads with clear lane markings and are implemented using commercial-grade sensing systems coupled with specialized graphic accelerator hardware. …”
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A Real-Time Channel Prediction Model Based on Neural Networks for Dedicated Short-Range Communications by Tianhong Zhang, Sheng Liu, Weidong Xiang, Limei Xu, Kaiyu Qin, Xiao Yan

“…Such a model can be easily extended to the applications of autonomous driving, the Internet of Things (IoT), 5th generation cellular network technology (5G) and many others.…”
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Reducing Message Collisions in Sensing-Based Semi-Persistent Scheduling (SPS) by Using Reselection Lookaheads in Cellular V2X by Yongseok Jeon, Seungho Kuk, Hyogon Kim

“…Still, the current standard mechanism produces a high number of packet collisions, which may hinder the high-reliability communications required in future C-V2X applications such as autonomous driving. In this paper, we show that by drastically reducing the uncertainties in the choice of the resource to use for SPS, we can significantly reduce the message collisions in the C-V2X sidelink Mode 4. …”
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Efficient Multi-Lane Detection Based on Large-Kernel Convolution and Location by Shoubiao Li, Xin Wu, Zhifei Wu

“…Lane detection is the critical sensing technology for autonomous driving systems and advanced driving assistance systems. …”
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Simulation and Post-Processing for Advanced Driver Assistance System (ADAS) by Matteo Dollorenzo, Vincenzo Dodde, Nicola Ivan Giannoccaro, Davide Palermo

“…Considering the continuous development in the automotive sector and autonomous driving technology, it is necessary to conduct continuous research to identify the main points that can allow continuous improvement of system autonomy. …”
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Dynamic Trajectory Planning and Optimization for Automated Driving on Ice and Snow Covered Road by Jialu Pan, Jianqiang Wang, Shengsheng Xing

“…The rapid development of 5G and Artificial Intelligence (AI) has promoted the widespread application of autonomous driving in various scenarios. Currently, autonomous vehicles (AVs) can autonomously perform operations such as turning, lane changing, and acceleration in accordance with road traffic rules. …”
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Enhancing Object Detection in Self-Driving Cars Using a Hybrid Approach by Sajjad Ahmad Khan, Hyun Jun Lee, Huhnkuk Lim

“…The findings of this research have practical implications for the integration of AI technologies in autonomous driving systems.…”
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Towards Enhancing Traffic Sign Recognition through Sliding Windows by Muhammad Atif, Tommaso Zoppi, Mohamad Gharib, Andrea Bondavalli

“…Automatic Traffic Sign Detection and Recognition (TSDR) provides drivers with critical information on traffic signs, and it constitutes an enabling condition for autonomous driving. Misclassifying even a single sign may constitute a severe hazard, which negatively impacts the environment, infrastructures, and human lives. …”
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