Collision Prediction in an Integrated Framework of Scenario-Based and Data-Driven Approaches by Sungwoo Lee, Bongsob Song, Jangho Shin

“…A collision prediction framework integrating scenario-based approach with data-driven approach is proposed to enhance the safety of autonomous driving vehicles as well as advanced driver assistance systems. …”
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Open-Pit Map: An HD Map Data Model for Open-Pit Mines by Xingliang Xu, Zhuo Wang, Pengli Huang, Suchuan Tian, Lin Bi

“…One of the core technologies for autonomous driving is high-definition map technology, while refined mine maps are also needed to support scenarios such as vehicle–shovel collaboration, loading and unloading, production scheduling, and traffic safety control. …”
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YOLOv5s-Fog: An Improved Model Based on YOLOv5s for Object Detection in Foggy Weather Scenarios by Xianglin Meng, Yi Liu, Lili Fan, Jingjing Fan

“…This method provides technical support for rapid and accurate target detection in adverse weather conditions, such as foggy weather, for autonomous driving vehicles.…”
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Risk Aware Planning and Probabilistic Prediction for Autonomous Systems under Uncertain Environments by Han, Weiqiao

“…Our model achieves state-of-the-art performance in autonomous driving trajectory prediction tasks.…”
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Mobilità a guida autonoma: tra tecnologia, nuovi trend e prospettive future by Valerio Carlucci

“… The article outlines an overview of the technologies used in autonomous mobility and the role of geomatics and geospatial technologies for a safe and efficient autonomous driving. Some of the latest technological innovations developed by autonomous car manufacturers are also illustrated. …”
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Communication Delay Outlier Detection and Compensation for Teleoperation Using Stochastic State Estimation by Eugene Kim, Myeonghwan Hwang, Taeyoon Lim, Chanyeong Jeong, Seungha Yoon, Hyunrok Cha

“…There have been numerous studies attempting to overcome the limitations of current autonomous driving technologies. However, there is no doubt that it is challenging to promise integrity of safety regarding urban driving scenarios and dynamic driving environments. …”
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A Lightweight High Definition Mapping Method Based on Multi-Source Data Fusion Perception by Haina Song, Binjie Hu, Qinyan Huang, Yi Zhang, Jiwei Song

“…In this paper, a lightweight, high-definition mapping method is proposed for autonomous driving to address the drawbacks of traditional mapping methods, such as high cost, low efficiency, and slow update frequency. …”
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Smart Vehicle Driving Behavior Analysis Based on 5G, IoT and Edge Computing Technologies by Jin Haoxuan, Zhang Hongkuan

“…With the development of science and technology, the realization of intelligent vehicle autonomous driving has become a popular research. In order to realize the optimal autonomous driving behavior, this paper proposes a vehicle-splittable task offloading algorithm for edge offloading in the IoT environment based on the study of edge computing technology and the integration of 5G communication. …”
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Research on Driving Obstacle Detection Technology in Foggy Weather Based on GCANet and Feature Fusion Training by Zhaohui Liu, Shiji Zhao, Xiao Wang

“…This is of great practical significance for improving the safe perception of driving obstacles under adverse weather conditions, ensuring the safety of autonomous driving.…”
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Research on the SSIDM Modeling Mechanism for Equivalent Driver’s Behavior by Rui Fang

“…This research can provide theoretical support for the construction of the point-to-point driving model and the development of L2+ autonomous driving functions. It can provide assistance for the landing and application of full-behavior and full-scene autonomous driving.…”
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Trajectory Prediction Method Based on Fusion of Graph Interaction and Scene Perception by FANG Yang, ZHAO Ting, LIU Qi-lie, HE Dong, SUN Kai-wei, CHEN Qian-bin

“…To accurately perceive the environment and predict the trajectory of the surrounding traffic participants for autonomous driving,we propose a real-time end-to-end trajectory prediction framework based on bird eye view(BEV) to learn both interaction and scene information simultaneously.The framework consists of two essential modules:graph interaction network and pyramid perception network.The former encodes the interaction patterns among traffic participants through a spatiotemporal graph convolutional network,and the latter adopts a spatiotemporal pyramid network to model the surrounding information and obtain the scene features.Next,interactive features and scene features are fused at a unified scale to perform classification and trajectory prediction tasks.Experiments and analysis on Nuscenes,a large open-source dataset,indicate that the proposed framework achieves a higher classification accuracy of 3.1% and 1.43% less predicted trajectory loss than MotionNet.Hence,our framework outperforms state-of-the-art algorithms in terms of generalization and robustness,and is more in line with perception requirements in actual autonomous driving scenes.…”
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Advanced Alarm Method Based on Driver’s State in Autonomous Vehicles by Ji-Hyeok Han, Da-Young Ju

“…In autonomous driving vehicles, the driver can engage in non-driving-related tasks and does not have to pay attention to the driving conditions or engage in manual driving. …”
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Unveiling strategies in recent automotive history. Using patent citations for ambidexterity evidence by Daniel Guffarth, Lukas Lang, Andreas Pyka

“…The omni-present electrification of the powertrain together with the technological convergence with connected-car and autonomous-driving technology are the key challenges. To process the pressure, new strategies are designed and implemented. …”
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Traffic flow digital twin generation for highway scenario based on radar-camera paired fusion by Yanbing Li, Weichuan Zhang

“…Abstract Autonomous driving is gradually moving from single-vehicle intelligence to internet of vehicles, where traffic participants can share the traffic flow information perceived by each other. …”
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Development of Path Generation and Algorithm for Autonomous Combine Harvester Using Dual GPS Antenna by Kyuho Lee, Hyohyuk Choi, Junghun Kim

“…Research on autonomous driving technology is actively underway to solve the facing problems in the agricultural field. …”
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A Multi-Task Road Feature Extraction Network with Grouped Convolution and Attention Mechanisms by Wenjie Zhu, Hongwei Li, Xianglong Cheng, Yirui Jiang

“…To cope with the challenges of autonomous driving in complex road environments, the need for collaborative multi-tasking has been proposed. …”
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A Comparative Analysis of Deep Reinforcement Learning-Enabled Freeway Decision-Making for Automated Vehicles by Teng Liu, Yuyou Yang, Wenxuan Xiao, Xiaolin Tang, Mingzhu Yin

“…In application, advanced autonomous driving technologies still face numerous challenges. …”
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Design of a Four-Wheel Steering Mobile Robot Platform and Adaptive Steering Control for Manual Operation by Beomsu Bae, Dong-Hyun Lee

“…The recent advancementsin autonomous driving technology have led to an increased utilization of mobile robots across various industries. …”
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A Secure Trajectory Planning Method for Connected Autonomous Vehicles at Mining Site by Han Li, Yiming Li, Peng Chen, Guizhen Yu, Yaping Liao

“…After receiving the loading task, the autonomous driving system will generate a feasible trajectory for the mining truck. …”
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Reinforcement-Learning-Based Decision and Control for Autonomous Vehicle at Two-Way Single-Lane Unsignalized Intersection by Yonggang Liu, Gang Liu, Yitao Wu, Wen He, Yuanjian Zhang, Zheng Chen

“…In the process of developing L3-and-above autonomous-driving techniques, it is necessary to solve problems in autonomous driving decisions and control at intersections. …”
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