A Scalable and Coordinated Energy Management for Electric Vehicles Based on Multiagent Reinforcement Learning Method by Ruien Bian, Xiuchen Jiang, Guoying Zhao, Yadong Liu, Zhou Dai

“…The electric vehicle (EV) has been popular in recent years, which also brings huge challenges to the distribution network due to its energy instability. …”
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STF-LPPVA: Local Privacy-Preserving Method for Vehicle Assignment Based on Spatial–Temporal Fusion by Lei Tang, Zhengxin Cao, Xin Zhou, Junzhe Zhang, Junchi Ma

“…Based on the similarity of the vectors, the cloud platform can allocate vehicles using the Kuhn–Monkreth (KM) algorithm. In addition, we analyze the theoretical feasibility of the STF-LPPVA strategy using entropy change and get good performance with a dataset from DiDi in Chengdu, China. …”
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Reinforcement learning for autonomous underwater vehicles (AUVs): navigating challenges in dynamic and energy-constrained environments by Mohab M. Eweda, Karim ElNaggar

“…This paper examines significant progress in reinforcement learning algorithms, emphasizing their application in the training of autonomous underwater vehicles in both simulated and real-world environments. …”
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Fatigue Damage Assessment of a Metro Vehicle Bogie Frame Based on Measured Field Load by Yangmin Wu, Zunsong Ren

“…As the operating conditions of metro vehicles become more complex, the fatigue damage of metro bogie frames under actual operating conditions becomes increasingly difficult to evaluate realistically. …”
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Transportation Severity Analysis of Factors Contributing to Two-Vehicle Road Crashes Based on Interpretability Theory by Chen Zhang, Linjia Li, Aihui Pei, Li Tao, Junli Yuan, Feng Xiao, Yuxi Zheng

“…Two-vehicle crashes dominate among all types of urban traffic accidents. …”
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MEP-YOLOv5s: Small-Target Detection Model for Unmanned Aerial Vehicle-Captured Images by Shengbang Zhou, Song Zhang, Chuanqi Li, Shutian Liu, Dong Chen

“…Due to complex backgrounds, significant scale variations of targets, and dense distributions of small objects in Unmanned Aerial Vehicle (UAV) aerial images, traditional object detection algorithms face challenges in adapting to such scenarios. …”
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Optimized Detection Algorithm for Vertical Irregularities in Vertical Curve Segments by Rong Xie, Chunjun Chen

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Robust UAV Target Tracking Algorithm Based on Saliency Detection by Hanqing Wu, Weihua Wang, Gao Chen, Xin Li

“…Next, this article uses saliency detection to supervise the aspect ratio of the target, and trains a scale filter in the continuous domain to improve the tracker’s adaptability to scale variations. …”
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Garbage classification detection system based on the YOLOv8 algorithm by Yan Zhou, Lixiong Lin, Tong Wang

“…Subsequently, the YOLOv8 algorithm is studied, applied to garbage detection and classification, and used for practical verification in unmanned vehicles. …”
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Research on Cooperative Velocity Planning Technology for Urban Rail Train Virtual Coupling by HUANG Qiang, LI Cheng, YUAN Xiwen, CHEN Lin, LUO Jiaxiang

“…Based on the key requirements for urban rail trains, namely punctuality, comfort and sufficient time for platform operations, this study proposed a cooperative speed planning algorithm for virtual coupling, featuring information centralized decision-making, following an investigation into train traction and braking characteristics, vehicle kinematics and dynamics models. …”
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Joint Caching and Computation in UAV-Assisted Vehicle Networks via Multi-Agent Deep Reinforcement Learning by Yuhua Wu, Yuchao Huang, Ziyou Wang, Changming Xu

“…We precisely model the problem as a Decentralized Partially Observable Markov Decision Process (Dec-POMDP) and adopt the Multi-Agent Proximal Policy Optimization (MAPPO) algorithm, which follows the Centralized Training Decentralized Execution (CTDE) paradigm. …”
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Research and Application of an Online Train ConditionMonitoring Method Based on Streaming Data by FENG Furen

“…At the same time, an intelligent maintenance equipment which applied to the train multi-function vehicle bus MVB network is designed to carry and verify the algorithm. …”
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Multi-Agent Deep Reinforcement Learning Cooperative Control Model for Autonomous Vehicle Merging into Platoon in Highway by Jiajia Chen, Bingqing Zhu, Mengyu Zhang, Xiang Ling, Xiaobo Ruan, Yifan Deng, Ning Guo

“…The developed MA-DRL architecture enables coordinated learning among multiple autonomous agents to address the multi-objective coordination challenge through synchronized control of platoon longitudinal acceleration, AV steering and acceleration. To enhance training efficiency, we develop a dual-layer multi-agent maximum Q-value proximal policy optimization (MAMQPPO) method, which extends the multi-agent PPO algorithm (a policy gradient method ensuring stable policy updates) by incorporating maximum Q-value action selection for platoon gap control and discrete command generation. …”
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MM-VSM: Multi-Modal Vehicle Semantic Mesh and Trajectory Reconstruction for Image-Based Cooperative Perception by Márton Cserni, András Rövid, Zsolt Szalay

“…The effectiveness of the algorithm is proven through a real-world smart valet parking application, which is evaluated in our university parking area with real vehicles. …”
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Detection of Rice Leaf Folder in Paddy Fields Based on Unmanned Aerial Vehicle-Based Hyperspectral Images by Shanshan Feng, Shun Jiang, Xuying Huang, Lei Zhang, Yangying Gan, Laigang Wang, Canfang Zhou

“…The training and testing accuracies reached 87.46% and 86%, respectively. …”
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Path Planning Based on Combination of Sampling and Learning-From-Demonstration for Static Obstacle Avoidance of Autonomous Vehicles by Youngmin Yoon, Ara Jo

“…This paper presents a sampling-based path planning algorithm for autonomous vehicles with the existence of static obstacles. …”
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Precision Weed Control Using Unmanned Aerial Vehicles and Robots: Assessing Feasibility, Bottlenecks, and Recommendations for Scaling by Shanmugam Vijayakumar, Palanisamy Shanmugapriya, Pasoubady Saravanane, Thanakkan Ramesh, Varunseelan Murugaiyan, Selvaraj Ilakkiya

“…In response, precision weed control (PWC) technologies, such as robots and unmanned aerial vehicles (UAVs), have emerged as innovative solutions. …”
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A deep neural network approach for optimizing charging behavior for electric vehicle ride-hailing fleet by Kaizhe Chen, Jin Liu, Wenjing Lyu, Tianyuan Wang, Jinxi Wen

“…Therefore, this research develops a Neural Network (NN) trained with the Adaptive Moment Estimation (Adam) algorithm, based on 2.14 million charging events. …”
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A deep learning model for fault detection in distribution networks with high penetration of electric vehicle chargers by Seyed Amir Hosseini, Behrooz Taheri, Seyed Hossein Hesamedin Sadeghi, Adel Nasiri

“…Integration of a significant number of domestic electrical vehicle (EV) charging stations into the power distribution infrastructure can give rise to several protection problems. …”
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Stochastic Potential Game-Based Target Tracking and Encirclement Approach for Multiple Unmanned Aerial Vehicles System by Kejie Yang, Ming Zhu, Xiao Guo, Yifei Zhang, Yuting Zhou

“…Utilizing fully distributed intelligent control algorithms has enabled the gradual adoption of the multiple unmanned aerial vehicles system for executing Target Tracking and Encirclement missions in industrial and civil applications. …”
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