Article
Automation & Control Systems
Keqi Shu, Huilong Yu, Xingxin Chen, Shen Li, Long Chen, Qi Wang, Li Li, Dongpu Cao
Summary: This article proposes a hierarchical decision-making and planning method based on critical turning points to address the challenges of decision making at uncertain intersections of different shapes. By generating behavior-oriented paths and using a partially observable Markov decision process solver, the method can make efficient and safe planning decisions in real time.
IEEE-ASME TRANSACTIONS ON MECHATRONICS
(2022)
Article
Engineering, Civil
Muhammad Rehan Siddiqi, Alireza Saharkhiz, Reza N. Jazar, Hormoz Marzbani
Summary: Motion sickness in self-driving cars is investigated in this study, where thresholds and transition curves are established to minimize the probability of motion sickness. The study also compares trajectory tracking algorithms within the Autodriver system and provides recommendations for further research to address remaining motion sickness thresholds.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Automation & Control Systems
Jiankun Wang, Max Q-H Meng
Summary: This article proposes a two-level planner to address the autonomous luggage trolley collection problem at the airport. The higher level planner tackles a decision-making problem, while the lower level planner introduces a novel real-time path planning algorithm.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2022)
Article
Automation & Control Systems
Weida Wang, Tianqi Qie, Chao Yang, Wenjie Liu, Changle Xiang, Kun Huang
Summary: This article proposes a prediction method based on a fuzzy inference system and a long short-term memory neural network to accurately predict the lane-changing behavior of surrounding vehicles, as well as an intelligent decision-making strategy for path planning of autonomous vehicles to enhance driving safety.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2022)
Article
Computer Science, Artificial Intelligence
Akhil Vinayak, Muhammad Aizzat Zakaria, K. Baarath, Mohamad Heerwan Peeie, Muhammad Izhar Ishak
Summary: Path planning in autonomous vehicle navigation faces challenges when plotting paths in roundabouts. While Bezier curves are widely used for circular path planning, locating their control points remains a major obstacle. Due to the varying shapes and sizes of roundabouts, there is no universal strategy for control point placement.
JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS
(2023)
Review
Engineering, Electrical & Electronic
Faizan Sana, Nasser L. Azad, Kaamran Raahemifar
Summary: The development of autonomous vehicles (AVs) is crucial for reliable and safe transportation. However, achieving level 5 autonomy requires efficient navigation in complex scenarios. This review paper discusses different navigation methodologies, including traditional planning methods and emerging solutions. It identifies key challenges such as benchmarking, ensuring interpretability, incorporating safety and road user interactions, and unrealistic simplifications. The paper also presents suggestions to tackle these challenges.
Review
Engineering, Mechanical
Shen Li, Keqi Shu, Chaoyi Chen, Dongpu Cao
Summary: This paper provides an overview of recent studies on planning and decision-making technologies at intersections, including algorithm-based approaches, prediction-based approaches, optimization-based approaches, and machine learning-based approaches, as well as future trends and potential research problems to be addressed.
CHINESE JOURNAL OF MECHANICAL ENGINEERING
(2021)
Article
Computer Science, Information Systems
Zhiqi Feng, Wenjie Song, Mengyin Fu, Yi Yang, Meiling Wang
Summary: Safe and efficient decision-making and path planning in autonomous driving on highways involves separating decision-making and path planning modules. This approach is executed in different coordinate systems for better performance in dynamic high-speed interaction scenarios.
IEEE SYSTEMS JOURNAL
(2022)
Article
Computer Science, Information Systems
Ilias Panagiotopoulos, George Dimitrakopoulos
Summary: Intelligent connected vehicles (ICVs) are a transformative technology that has attracted significant research effort and holds great promise in enhancing road safety, transport efficiency, driving comfort, and eco-friendly mobility. Due to the increasing connectivity of the driving environment, the driving style of an ICV can dynamically vary based on individual traits and the vehicle's surroundings. This study aims to present a novel in-vehicle autonomous decision-making functionality that enables ICVs to utilize the most suitable driving style by considering personal characteristics, preferences, and changes in the driving environment.
Article
Environmental Sciences
Heba Kurdi, Shaden Almuhalhel, Hebah Elgibreen, Hajar Qahmash, Bayan Albatati, Lubna Al-Salem, Ghada Almoaiqel
Summary: With the rise of autonomous vehicles and artificial intelligence, path planning has become a key research focus area. A new algorithm called Tide Path Planning (TPP) inspired by natural tide phenomenon was introduced in this paper, showing superior performance compared to other existing path planning algorithms.
Article
Engineering, Electrical & Electronic
Yisong Wang, Chunyan Wang, Wanzhong Zhao, Can Xu
Summary: This paper proposes a decision-making and planning method for autonomous vehicles based on motivation and risk assessment, which can flexibly adjust path and speed, and make effective driving behavior decisions in real-time environments.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2021)
Article
Chemistry, Multidisciplinary
Mingrui Shu, Xiuyu Zheng, Fengguo Li, Kaiyong Wang, Qiang Li
Summary: This paper proposes a time-optimal path planning method for autonomous underwater vehicles (AUVs) based on a Markov decision process (MDP) algorithm, and demonstrates its importance and advantages in the marine environment through simulation experiments.
APPLIED SCIENCES-BASEL
(2022)
Article
Automation & Control Systems
Omveer Sharma, N. C. Sahoo, N. B. Puhan
Summary: Autonomous vehicles are gaining attention in academic and industrial research due to their advantages such as safety improvement and reduced traffic congestion. Intelligent motion and behavior planning play crucial roles in decision making process, considering factors like safety, comfort, and traffic rules. Various techniques have been developed over the past few decades, but there is still a need for rigorous evaluation and improvement of existing approaches.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2021)
Article
Engineering, Civil
Zhiqiang Jian, Shitao Chen, Songyi Zhang, Yu Chen, Nanning Zheng
Summary: This article analyzes the issues with current path planning frameworks in autonomous driving systems and proposes a global path planning framework based on multiple models. The framework divides the planning process into layers and adaptsively adjusts the process according to changes in traffic scenes, ensuring safety and flexibility in driving.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Engineering, Civil
Junior Anderson Rodrigues da Silva, Iago Pacheco Gomes, Denis Fernando Wolf, Valdir Grassi
Summary: This paper proposes a road network model based on clothoids for Autonomous Vehicles to autonomously navigate in traffic roads. Through piecewise linear continuous-curvature paths, the model takes into account the vehicle's compliance with traffic rules in urban scenarios, while also considering passengers' comfort parameters.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Engineering, Multidisciplinary
Pedro Maria Alcover, Pedro J. Navarro, Carlos Fernandez-Isla, Juan Angel Pastor
Review
Chemistry, Analytical
Francisca Rosique, Pedro J. Navarro, Carlos Fernandez, Antonio Padilla
Article
Cell Biology
Marta Terry, Fernando Perez-Sanz, Pedro J. Navarro, Julia Weiss, Marcos Egea-Cortines
Article
Mathematics, Applied
Pedro Maria Alcover Garau
COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION
(2020)
Article
Plant Sciences
Maria Victoria Diaz-Galiana, Magdalena Torres, Jose David Sanchez-Pagan, Pedro J. Navarro, Julia Weiss, Marcos Egea-Cortines
Summary: The study found that increasing red and blue light has a positive impact on strawberry production and quality, improving flowering rate and fruit quality. Supplementary lighting within a 13-hour light cycle can achieve fruit production and enhance quality.
SOUTH AFRICAN JOURNAL OF BOTANY
(2021)
Article
Environmental Sciences
Pedro J. Navarro, Leanne Miller, Alberto Gila-Navarro, Maria Victoria Diaz-Galian, Diego J. Aguila, Marcos Egea-Cortines
Summary: A new deep learning architecture named 3DeepM was developed for multispectral image classification, achieving superior performance in accuracy, number of classes, number of parameters, and training time. Additionally, a flexible and reconfigurable computer vision system was introduced to support the validation of the 3DeepM architecture for acquiring multispectral images.
Article
Biochemistry & Molecular Biology
Fernando Perez-Sanz, Victoria Ruiz-Hernandez, Marta Terry, Sara Arce-Gallego, Julia Weiss, Pedro J. Navarro, Marcos Egea-Cortines
Summary: Metabolomes consist of constitutive and non-constitutive metabolites produced due to physiological, genetic, or environmental effects. The tool gcProfileMakeR is developed for automatic data analysis in large datasets to define differences in metabolites.
Article
Computer Science, Information Systems
Francisca Rosique, Fernando Losilla, Pedro J. Navarro
Summary: Measurement of joint range of motion is an essential part in functional evaluation of patients. ROMCam, an alternative system for measuring joint range of motion based on estimating human pose in 2D, is proven to be a low-cost and accessible tool for telerehabilitation treatments.
IEEE LATIN AMERICA TRANSACTIONS
(2021)
Article
Computer Science, Information Systems
Pedro J. Navarro, Leanne Miller, Francisca Rosique, Carlos Fernandez-Isla, Alberto Gila-Navarro
Summary: The study introduced six end-to-end architectures based on deep neural networks for generating driving actions directly on vehicle control elements, with the mixed data architecture showing the best performance. Through detailed design and optimization processes, it was proven possible to design lightweight, high-performance architectures suitable for implementation in autonomous driving.
Article
Chemistry, Multidisciplinary
Francisca Rosique, Fernando Losilla, Pedro J. Navarro
Summary: This paper presents an augmented reality mirror application called ExerCam, which utilizes vision-based human pose detection. ExerCam operates with a simple RGB camera and does not require special controllers or sensors, making it accessible and cost-effective. The application includes a web-based system for managing patients, tasks, and games, allowing therapists to remotely monitor patients. Results suggest that ExerCam is a viable telerehabilitation tool, with positive outcomes in range of motion assessment and patient performance improvement during therapy sessions.
APPLIED SCIENCES-BASEL
(2021)
Article
Mathematics, Applied
Isidro Villo-Perez, Pedro -Maria Alcover-Garau, Maria Campo-Valera, Rafael Toledo-Moreo
Summary: In this paper, a novel and simple Yee Finite-Difference Time-Domain (FDTD) scheme is presented for the numerical solution of nonlinear second-order thermoviscous Navier-Stokes and Continuity equations. By rewriting the equations in a new form, the Yee's mesh can be used for discretization, leading to higher computational performance.
COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION
(2023)
Article
Chemistry, Analytical
Francisca Rosique, Pedro J. Navarro, Leanne Miller, Eduardo Salas
Summary: The popularity of autonomous vehicle development has led to the publication of numerous datasets, with synthetic datasets gaining particular interest. However, existing datasets lack human interaction data, which is crucial for real implementation and evaluation of vehicles at higher levels of autonomy. In this article, the UPCT dataset is introduced, which includes high-quality multimodal data obtained from state-of-the-art sensors and equipment onboard an autonomous vehicle.
Article
Mathematics, Applied
Pedro-Maria Alcover-Garau
Summary: Discrete quadratic dynamical systems are used to define models of reality. The behavior of their complex orbits can be understood by studying the Mandelbrot Set. Symmetrical points on the map of periods, generated by encoding the orbits of points in the Mandelbrot Set, play a significant role in determining the values of other points. Understanding the properties of these points is crucial for comprehending the behavior of quadratic and discrete dynamical systems. The article highlights the emergence of scalar symmetry property and its impact on the hypersensitivity of the map of periods to small changes in parameters.
DISCRETE AND CONTINUOUS DYNAMICAL SYSTEMS-SERIES B
(2023)
Article
Biology
Pedro J. Navarro, Leanne Miller, Maria Victoria Diaz-Galian, Alberto Gila-Navarro, Diego J. Aguila, Marcos Egea-Cortines
Summary: This study developed the first public dataset of grape ground truth multispectral images. The dataset includes measurements of weight, anthocyanins, and Brix index associated with each multispectral image. This dataset should be useful for developing deep learning algorithms for classification, dimensionality reduction, regression, and prediction analysis.
Proceedings Paper
Computer Science, Hardware & Architecture
Leanne Miller, Antonio Ros Garcia, Pedro J. Navarro Lorente, Carlos Fernandez Andres, Raul Borraz Moron
INFORMATION SYSTEMS ARCHITECTURE AND TECHNOLOGY, ISAT 2019, PT II
(2020)
