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Zhixi Hu, Yi Zhu, Xiaoying Chen and Yu Zhao
Autonomous driving is a safety-critical system, and the occupancy of its environmental resources affects the safety of autonomous driving. In view of the lack of safety verification of environmental resource occupation rules in autonomous driving, this p...
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Bohdan Petryshyn, Serhii Postupaiev, Soufiane Ben Bari and Armantas Ostreika
The development of autonomous driving models through reinforcement learning has gained significant traction. However, developing obstacle avoidance systems remains a challenge. Specifically, optimising path completion times while navigating obstacles is ...
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Haojun Wen, Xiaodong Ma, Chenjian Qin, Hao Chen and Huanyu Kang
The high clearance spray is a type of large and efficient agricultural machinery used for plant protection, and path tracking control is the key to ensure the efficient and safe operation of spray. Sliding mode control and other methods are commonly used...
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Youngkwang Kim, Woochan Kim, Jungwoo Yoon, Sangkug Chung and Daegeun Kim
This paper presents a practical contamination detection system for camera lenses using image analysis with deep learning. The proposed system can detect contamination in camera digital images through contamination learning utilizing deep learning, and it...
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Arpad Takacs and Tamas Haidegger
The significance of V2X (Vehicle-to-Everything) technology in the context of highly automated and autonomous vehicles can hardly be overestimated. While V2X is not considered a standalone technology for achieving high automation, it is recognized as a sa...
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Benny Wijaya, Mengmeng Yang, Tuopu Wen, Kun Jiang, Yunlong Wang, Zheng Fu, Xuewei Tang, Dennis Octovan Sigomo, Jinyu Miao and Diange Yang
This research paper employed a multi-session framework to present an innovative approach to map monitoring within the domain of high-definition (HD) maps. The proposed methodology uses a machine learning algorithm to derive a confidence level for the det...
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Yuan Guo, Jian Zhou, Xicheng Li, Youchen Tang and Zhicheng Lv
High-definition (HD) maps serve as crucial infrastructure for autonomous driving technology, facilitating vehicles in positioning, environmental perception, and motion planning without being affected by weather changes or sensor-visibility limitations. M...
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Chan-Hoo Kim, Ji-Hyun Choi and Sung-Young Park
Contaminated autonomous-driving sensors frequently malfunction, resulting in accidents; these sensors need regular cleaning. The autonomous-driving sensor-cleaning nozzle currently used is the windshield-washer nozzle; few studies have focused on the sen...
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JongBae Kim
This technology can prevent accidents involving large vehicles, such as trucks or buses, by selecting an optimal driving lane for safe autonomous driving. This paper proposes a method for detecting forward-driving vehicles within road images obtained fro...
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Yanfeng Li, Hsin Guan, Xin Jia and Chunguang Duan
A scenario vehicle in autonomous driving simulations is a dynamic entity that is expected to perform trustworthy bidirectional interaction tasks with the autonomous vehicle under test. Modeling interactive behavior can not only facilitate better predicti...
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Yasser Bin Salamah
In the past few years, there has been a growing interest among researchers in developing control systems for autonomous vehicles, specifically for tractor-trailer systems. This newfound interest is driven by the potential benefits of enhancing safety, re...
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Yu Cao, Kan Ni, Xiongwen Jiang, Taiga Kuroiwa, Haohao Zhang, Takahiro Kawaguchi, Seiji Hashimoto and Wei Jiang
The potential of autonomous driving technology to revolutionize the transportation industry has attracted significant attention. Path following, a fundamental task in autonomous driving, involves accurately and safely guiding a vehicle along a specified ...
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Fatima Zahra Guerrouj, Sergio Rodríguez Flórez, Mohamed Abouzahir, Abdelhafid El Ouardi and Mustapha Ramzi
Convolutional Neural Networks (CNNs) have been incredibly effective for object detection tasks. YOLOv4 is a state-of-the-art object detection algorithm designed for embedded systems. It is based on YOLOv3 and has improved accuracy, speed, and robustness....
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Priyank Kalgaonkar and Mohamed El-Sharkawy
Object detection, a more advanced application of computer vision than image classification, utilizes deep neural networks to predict objects in an input image and determine their locations through bounding boxes. The field of artificial intelligence has ...
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Yusef Savid, Reza Mahmoudi, Rytis Maskeliunas and Robertas Dama?evicius
Advancements in artificial intelligence are leading researchers to find use cases that were not as straightforward to solve in the past. The use case of simulated autonomous driving has been known as a notoriously difficult task to automate, but advancem...
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Inês A. Ribeiro, Tiago Ribeiro, Gil Lopes and A. Fernando Ribeiro
This paper presents a solution for an autonomously driven vehicle (a robotic car) based on artificial intelligence using a supervised learning method. A scaled-down robotic car containing only one camera as a sensor was developed to participate in the Ro...
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Masoud Mohammadi, Poria Fajri, Reza Sabzehgar and Farshad Harirchi
Finding the optimal speed profile of an autonomous electric vehicle (AEV) for a given route (eco-driving) can lead to a reduction in energy consumption. This energy reduction is even more noticeable when the regenerative braking (RB) capability of AEVs i...
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EunByul Ko, KwangHo Han and Chul-Hee Lee
Many issues have recently arisen as a result of the aging population and dwindling labor force. To solve these problems, including reduced convenience and productivity, research on the mobility of agricultural machinery and logistics involving autonomous...
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Rui Jiang, Hongyun Xu, Gelian Gong, Yong Kuang and Zhikang Liu
Vehicle-trajectory prediction is essential for intelligent traffic systems (ITS), as it can help autonomous vehicles to plan a safe and efficient path. However, it is still a challenging task because existing studies have mainly focused on the spatial in...
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Martin Holen, Kristian Muri Knausgård and Morten Goodwin
Autonomous driving is a research field that has received attention in recent years, with increasing applications of reinforcement learning (RL) algorithms. It is impractical to train an autonomous vehicle thoroughly in the physical space, i.e., the so-ca...
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