Research on LSTM-PPO Obstacle Avoidance Algorithm and Training Environment for Unmanned Surface Vehicles by Wangbin Luo, Xiang Wang, Fang Han, Zhiguo Zhou, Junyu Cai, Lin Zeng, Hong Chen, Jiawei Chen, Xuehua Zhou

“…The current unmanned surface vehicle (USV) intelligent obstacle avoidance algorithm based on deep reinforcement learning usually adopts the mass point model to train in an ideal environment. …”
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Timetable Design of Metro Train Based on RegenerativeBraking Energy Utilization by HE Deqiang, WANG Heliang, TAN Wenju, MIAO Jian

“…By introducing the immune algorithm, the headway,dwell time and running time were adjusted, and the train operation strategies was optimized. …”
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Joint Optimization Method for Preventive Maintenance and Train Scheduling of Subway Vehicles Based on a Spatiotemporal Network Graph by Chuanzhen Liu, Zhongwei Xu, Meng Mei, Wenqing Li

“…First, based on spatiotemporal network theory, the transition process between train operation scheduling and preventive maintenance states is analyzed, and a spatiotemporal state network graph is constructed to represent the temporal and spatial transitions of subway vehicles throughout the planning period. …”
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Swarm Confrontation Algorithm for UGV Swarm with Quantity Advantage by a Novel MSRM-MAPOCA Training Method by Huanli Gao, Chongming Zhao, Xinghe Yu, Shuangfei Ren, He Cai

“…The objective of this article is to design a swarm confrontation algorithm for the team with quantity advantage based on the multi-agent reinforcement learning training method. …”
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Research on the Prediction Model of Wheel Set Failure Rate for Urban Rail Trains Based on IPSO-BP Algorithm by HE Deqiang, SUN Yi, MENG Jiwei, LIU Jianren

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Overhaul Scheduling Approach for Metro Vehicles Based on Genetic Algorithms by WANG Bingjing, LI Bingxin

“…In this scheduling approach, an evaluation function is applied to transform the train overhaul scheduling into the tasks to optimize the resource allocation for the overhaul process, and the resource allocation to the overhaul process is optimized leveraging the inherent parallelism and global optimization ability of the genetic algorithm, and the optimal chromosome is deemed as the final result of the overhaul scheduling. …”
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A Vehicle Reidentification Algorithm Based on Double-Channel Symmetrical CNN by Lijun Yang, Tangsen Huang

“…In order to solve the above problems, a double-channel symmetric CNN vehicle recognition algorithm is proposed by improving the network structure. …”
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Multi-Target Vehicle Tracking Algorithm Based on Improved DeepSORT by Dudu Guo, Zhuzhou Li, Hongbo Shuai, Fei Zhou

“…First, we optimize the appearance feature extraction process by training a lightweight appearance extraction network (OSNet) on a vehicle re-identification dataset. …”
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A Data-Driven Front Tracking Algorithm for Autonomous Undersea Vehicles by Jieyang LU, Yongpeng WEN, Qian GUO, Xinke ZHU, Junsheng JIAO

“…To meet the requirement for adaptive observation of autonomous undersea vehicles(AUVs), a data-driven ocean front tracking algorithm was designed. …”
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Detection of Obstacle Intrusion in Front of Train Based on Vehicle-borne LiDAR by ZENG Xiang, JIANG Guotao, PAN Wenbo, LENG Binghan, CHEN Guibin

“…Obstacle intrusion threatens the running safety of automatically-operated train seriously. This paper proposes a method to detect obstacle intrusion in front of the trains based on vehicle-borne LiDAR. …”
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Energy management strategy for hybrid electric vehicle based on improved PPO algorithm by Chao MA, Tong SUN, Lei CAO, Kun YANG, Wenjing HU

“…In order to improve the economy of power-split hybrid electric vehicle (HEV),a longitudinal dynamics model of the entire HEV vehicle was established,and an energy management strategy (EMS) based on strategy entropy optimization with an improved proximal policy optimization (PPO) algorithm was proposed. …”
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YOLO-PEL: The Efficient and Lightweight Vehicle Detection Method Based on YOLO Algorithm by Zhi Wang, Kaiyu Zhang, Fei Wu, Hongxiang Lv

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Duty Cycle Algorithm for 3D Cable Routing in Rail Transit Vehicles by DU Qinghua, ZHOU Yongzhi

“…［Objective］ With the widespread application of rail transit vehicles such as high-speed and intercity trains, the increasing functional demands for these products have led to greater complexity in cable design. …”
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Research on the Virtual Coupling Technology for Urban Rail Transit Trains by YANG Weifeng, LEI Chengjian, HAN Chen, LI Qihe, XIE Xing

“…It also analyzes key technologies for implementing virtual coupling in urban rail transit trains, including high-performance vehicle-to-vehicle communication, safety protection based on relative braking, collision avoidance based on autonomous perception, train localization based on multi-sensor fusion , and collaborative control. …”
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Unmanned Aerial Vehicles (UAV) Networking Algorithms: Communication, Control, and AI-Based Approaches by Mien L. Trinh, Dung T. Nguyen, Long Q. Dinh, Mui D. Nguyen, De Rosal Ignatius Moses Setiadi, Minh T. Nguyen

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Reconfigurable intelligent surface assist wireless channel estimation algorithm in Internet of vehicles environment by Rong ZENG, Xiao HANG

“…Aiming at the problem that multi-user channel estimation assisted by reconfigurable intelligent surface (RIS) in the uplink Internet of vehicles environment, a location assisted compressive sensing channel estimation algorithm was proposed.Based on the location information of the communication equipment, a single RIS-assisted single-user communication model was built, and the optimal phase shift matrix was derived according to the logical relationship between the beam angle of departure (AOD) and the angle of arrival (AOA).The perception matrix was constructed and channel estimation was performed, and finally it was extended to multi-user scenarios and solved iteratively.The optimal RIS phase shift matrix was solved based on the position information obtained by the Internet of vehicles technology, which reduced the additional training overhead of the channel and further reduces the complexity of the channel estimation.Simulation results show that the proposed algorithm based on location information has high channel estimation performance.…”
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Reconfigurable intelligent surface assist wireless channel estimation algorithm in Internet of vehicles environment by Rong ZENG, Xiao HANG

“…Aiming at the problem that multi-user channel estimation assisted by reconfigurable intelligent surface (RIS) in the uplink Internet of vehicles environment, a location assisted compressive sensing channel estimation algorithm was proposed.Based on the location information of the communication equipment, a single RIS-assisted single-user communication model was built, and the optimal phase shift matrix was derived according to the logical relationship between the beam angle of departure (AOD) and the angle of arrival (AOA).The perception matrix was constructed and channel estimation was performed, and finally it was extended to multi-user scenarios and solved iteratively.The optimal RIS phase shift matrix was solved based on the position information obtained by the Internet of vehicles technology, which reduced the additional training overhead of the channel and further reduces the complexity of the channel estimation.Simulation results show that the proposed algorithm based on location information has high channel estimation performance.…”
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Predictive PID Control for Automated Guided Vehicles Using Genetic Algorithm and Machine Learning by Kinza Nazir, Yong-Woon Kim, Yung-Cheol Byun

“…The integration of automated guided vehicles (AGVs) in industrial automation demands precise and adaptive control systems for efficient path tracking. …”
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Smart prediction-planning algorithm for connected and autonomous vehicle based on social value orientation by Donglei Rong, Yuefeng Wu, Wenjun Du, Chengcheng Yang, Sheng Jin, Min Xu, Fujian Wang

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Vehicle Trajectory Prediction Algorithm Based on Hybrid Prediction Model with Multiple Influencing Factors by Tao Wang, Yiming Fu, Xing Cheng, Lin Li, Zhenxue He, Yuchi Xiao

“…Ultimately, the prediction module is engaged to yield the predicted movement positions of the vehicles, expressed in coordinate form. The proposed algorithm was trained and validated using the publicly accessible datasets I-80 and US-101. …”
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