Deep Reinforcement Learning For Control by Bakar, Nurul Asyikin Abu

“…Autonomous cars must be capable to operate in various conditions and learn from unforeseen scenarios. …”
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Intelligent Road Management System for Autonomous, Non-Autonomous, and VIP Vehicles by Awad Bin Naeem, Biswaranjan Senapati, Md. Sakiul Islam Sudman, Kashif Bashir, Ayman E. M. Ahmed

“…Currently, autonomous vehicles, non-autonomous vehicles, and VIP (emergency) autonomous cars are using intelligent road management techniques to interact with one another and enhance the effectiveness of the traffic system. …”
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Machine learning based IoT system for secure traffic management and accident detection in smart cities by Saravana Balaji Balasubramanian, Prasanalakshmi Balaji, Asmaa Munshi, Wafa Almukadi, T. N. Prabhu, Venkatachalam K, Mohamed Abouhawwash

“…To identify, gather, and send data, autonomous cars, and intelligent gadgets are equipped with an IoT-based ITM system with a group of sensors. …”
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Heterogeneous Defect Prediction Based on Transfer Learning to Handle Extreme Imbalance by Kaiyuan Jiang, Yutong Zhang, Haibin Wu, Aili Wang, Yuji Iwahori

“…Software systems are now ubiquitous and are used every day for automation purposes in personal and enterprise applications; they are also essential to many safety-critical and mission-critical systems, e.g., air traffic control systems, autonomous cars, and Supervisory Control And Data Acquisition (SCADA) systems. …”
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Machine Learning for 5G/B5G Mobile and Wireless Communications: Potential, Limitations, and Future Directions by Manuel Eugenio Morocho-Cayamcela, Haeyoung Lee, Wansu Lim

“…Considering the ever-increasing complexity of the network, and the emergence of novel use cases such as autonomous cars, industrial automation, virtual reality, e-health, and several intelligent applications, machine learning (ML) is expected to be essential to assist in making the 5G vision conceivable. …”
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An Expanded Framework for Situation Control by James Llinas, Raj Malhotra

“…There is an extensive body of literature on the topic of estimating situational states, in applications ranging from cyber-defense to military operations to traffic situations and autonomous cars. In the military/defense/intelligence literature, situation assessment seems to be the sine qua non for any research on surveillance and reconnaissance, command and control, and intelligence analysis. …”
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A ROS-Based Open Tool for Intelligent Robotics Education by José M. Cañas, Eduardo Perdices, Lía García-Pérez, Jesús Fernández-Conde

“…It comprises a collection of exercises including recent service robot applications in real life, with different robots such as autonomous cars, drones or vacuum cleaners. It uses Robot Operating System (ROS) middleware, the de facto standard in robot programming, the 3D Gazebo simulator and the Python programming language. …”
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A Self-Organizing Spatial Clustering Approach to Support Large-Scale Network RTK Systems by Lili Shen, Jiming Guo, Lei Wang

“…Currently, precise positioning provides a spatial foundation for artificial intelligence (AI), and countless smart devices (autonomous cars, unmanned aerial-vehicles (UAVs), robotic equipment, etc.) require precise positioning services. …”
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Users’ trust in black-box machine learning algorithms by Heitor Hoffman Nakashima, Daielly Mantovani, Celso Machado Junior

“…The interviews reveal that the nature and complexity of the problem a black-box model addresses influences the users’ perceptions, trust being reduced in situations that represent a threat (e.g. autonomous cars). Concerns about the models’ ethics were also mentioned by the interviewees. …”
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Continuous Autonomous Ship Learning Framework for Human Policies on Simulation by Junoh Kim, Jisun Park, Kyungeun Cho

“…The reinforcement learning (RL) algorithm, which demonstrates high potential in autonomous cars, has been presented as an alternative to mathematical algorithms and has advanced in studies on autonomous ships. …”
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Quantitative rational verification by Steeples, T

“…As such, it is natural to ask questions like \enquote{does this fleet of autonomous cars have enough power to safely get from point A to point B?} …”

Hybrid Organic–Si C-MOSFET Image Sensor Designed with Blue-, Green-, and Red-Sensitive Organic Photodiodes on Si C-MOSFET-Based Photo Signal Sensor Circuit by Ui-Hyun Jeong, Joo-Hyeong Park, Ji-Ho Choi, Woo-Guk Lee, Jea-Gun Park

“…The resolution of Si complementary metal–oxide–semiconductor field-effect transistor (C-MOSFET) image sensors (CISs) has been intensively enhanced to follow the technological revolution of smartphones, AI devices, autonomous cars, robots, and drones, approaching the physical and material limits of a resolution increase in conventional Si CISs because of the low quantum efficiency (i.e., ~40%) and aperture ratio (i.e., ~60%). …”
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State-of-the-Art Mobile Intelligence: Enabling Robots to Move Like Humans by Estimating Mobility with Artificial Intelligence by Xue-Bo Jin, Ting-Li Su, Jian-Lei Kong, Yu-Ting Bai, Bei-Bei Miao, Dou Chao

“…It is the most important function when robotics is applied to domains such as autonomous cars, home service robots, and autonomous underwater vehicles. …”
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Artificial intelligence-driven vehicle fault diagnosis to revolutionize automotive maintenance: A review by Hossain, Md Naeem, Rahman, Md Mustafizur, D., Ramasamy

“…We then delve into some examples of the use of AI in fault diagnosis and maintenance for electric vehicles and autonomous cars. The review elucidates the transformation of VFD systems that consequently increase accuracy, economization, and prediction in most vehicular sub-systems due to AI applications. …”
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Imitation Learning through Image Augmentation Using Enhanced Swin Transformer Model in Remote Sensing by Yoojin Park, Yunsick Sung

“…Recent advancements in deep learning enable the direct mapping of input images in remote sensing to desired outputs, making it possible to learn through imitation learning and for unmanned systems to learn by collecting and analyzing those images. In the case of autonomous cars, raw high-dimensional data are collected using sensors, which are mapped to the values of steering and throttle through a deep learning network to train imitation learning. …”
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Learning-Based Coordination Model for On-the-Fly Self-Composing Services Using Semantic Matching by Houssem Ben Mahfoudh, Ashley Caselli, Giovanna Di Marzo Serugendo

“…Objects, such as sensors, drones or autonomous cars participate in pervasive applications of various domains ranging from smart cities, quality of life, transportation, energy, business or entertainment. …”
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Sustainable Vision-Based Navigation for Autonomous Electric Vehicle Charging by Srivastava Nandini, Singh Harminder, Ikram Mohsin, Setia Nipun, Sharma Prabhat, Prasad Raju V. Siva, Kampani Shivani

“…The study offers a comprehensive examination of the precision of calibration, the ability to identify objects, the navigation capabilities of autonomous cars, and the effectiveness of charging sessions. …”
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Computer Vision-Based Inspection System for Worker Training in Build and Construction Industry by M. Fikret Ercan, Ricky Ben Wang

“…Recently computer vision has been applied in various fields of engineering successfully ranging from manufacturing to autonomous cars. A key player in this development is the achievements of the latest object detection and classification architectures. …”
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Neural Approach to Coordinate Transformation for LiDAR–Camera Data Fusion in Coastal Observation by Ilona Garczyńska-Cyprysiak, Witold Kazimierski, Marta Włodarczyk-Sielicka

“…Fusion is used in autonomous cars and robots, despite many challenges related to spatiotemporal alignment or sensor calibration. …”
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Representing Unstructured Environments for Robotic Manipulation: Toward Generalization, Dexterity and Robustness by Gao, Wei

“…Our formulation is applied to the developed manipulation pipeline, and it can benefit many other cyber-physical systems, such as autonomous cars.…”
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