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14th Conference on Traffic and Granular Flow (TGF)

作者： Zhan, Zhonghao Song, Weiguo Zhang, Jun Huang, Chuanli Univ Sci & Technol China State Key Lab Fire Sci Hefei Peoples R China

ISBN: (纸本)9789819979783;9789819979769;9789819979752

This paper proposes a nuclear accident emergency evacuation model based on nuclide concentration field and traffic flow network model. Gaussian puff model, which describes the instantaneous concentration of nuclide, is widely used to predict the diffusion of radionuclides in nuclear accidents. We adopt a modified Gaussian puff model to preserve the time characteristics of nuclide diffusion, which considers the effects of dry deposition (gravity deposition), wet deposition (rain wash), and nuclide decay on the concentration distribution. An a-star algorithm based on nuclide concentration and traffic pressure cost is proposed to formulate the optimal path planning under nuclear accident. With the expansion of the nuclide concentration field, more and more paths cannot be safely passed through, and evacuation vehicles will also cause congestion on the path. The evacuation model we proposed will regularly update the optimal route according to road traffic conditions and nuclide spatial distribution, so as to obtain an optimized evacuation strategy. This study takes a real road network around the nuclear power plant as the application scenario of evacuation simulation. The computation time of the evacuation model is short, so it can respond quickly in the event of a nuclear emergency. The results show that the evacuation strategy formulated by the model can ensure good evacuation efficiency and avoid areas with high nuclide concentrations during the evacuation process, thereby reducing the radiation exposure of personnel.

关键词： Nuclear accident Emergency evacuation Path-planning a-star algorithm Route optimization

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Optimal Design of Topological Structure for Mountainous Wind Farm Collection System 8

Optimal Design of Topological Structure for Mountainous Wind...

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8th International Conference on Power and Renewable Energy, ICPRE 2023

作者： Chen, Guoyu Gao, Heng Li, Ming Dalian University of Technology State Key Laboratory of Structural Analysis for Industrial Equipment Dalian China

ISBN: (纸本)9798350328813

In wind farm projects, the investment cost of the collection system is high, and optimizing the topological structure of the collection system can save a significant amount of cost. This paper addresses the optimization problem of the collection system in mountainous wind farms and proposes a feasible optimization method, including methods for acquiring geographical information data and establishing topographic maps, subdomain partitioning considering terrain and cable load flow impact, three-dimensional shortest path search method, and cost-optimal collection cable connection method. Case studies demonstrate that for mountainous wind farm projects with significant terrain influences, this method exhibits good optimization performance. © 2023 IEEE.

关键词： a-star algorithm clustering algorithm collection system minimum cost tree algorithm mountainous wind farm optimized design

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Slope Stability Assessment For Block-In-Matrix Composite-Materials By The Tortuous Surface Method

Slope Stability Assessment For Block-In-Matrix Composite-Mat...

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作者： Exneyder Andres Montoya Araque Universidad Nacional de Colombia

学位级别：硕士

This thesis deals with the general problem of slope stability analysis in bimsoils/bimrocks and tortuous failure surfaces in slopes. The problem was handled by means of developing an application software named pyBIMstab that is capable of randomly generating bimsoil/bimrock structures inside a slope; defining automatically the surfaces that pass around the blocks by applying a pathfinding algorithm named A*; and evaluating the factor of safety of those tortuous surfaces with limit equilibrium methods. The application software pyBIMstab was used to perform thousands of analysis for different conditions and conclusion were obtained from that work. Finally, a methodology is proposed to properly perform analysis in slopes made of bimsoils/bimrocks in a stochastic way to deal with the uncertainties related to the wide range of factors of safety that can occur even with bimsoils/bimrocks having the same block proportions.

关键词： Slope stability a-star algorithm Tortuous failure surface General limit method

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A Study of the Improved A* algorithm Incorporating Road Factors for Path Planning in Off-Road Emergency Rescue Scenarios

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SENSORS 2024年第17期24卷 5643页

作者： Zhao, Dequan Ni, Li Zhou, Kefa Lv, Zhihong Qu, Guangjun Gao, Yue Yuan, Weiting Wu, Qiulan Zhang, Feng Zhang, Qing Shandong Agr Univ Sch Informat Sci & Engn Tai An 271018 Peoples R China Chinese Acad Sci Inst Aerosp Informat Innovat Beijing 100094 Peoples R China Chinese Acad Sci Technol & Engn Ctr Space Utilizat Beijing 100045 Peoples R China Jiangsu Ocean Univ Sch Marine Technol & Geomatics Lianyungang 222005 Peoples R China Beijing Univ Chem Technol Sch Mech & Elect Engn Beijing 100020 Peoples R China

To address the problem of ignoring unpaved roads when planning off-road emergency rescue paths, an improved A* algorithm that incorporates road factors is developed to create an off-road emergency rescue path planning model in this study. To reduce the number of search nodes and improve the efficiency of path searches, the current node is classified according to the angle between the line connecting the node and the target point and the due east direction. Additionally, the search direction is determined in real time through an optimization method to improve the path search efficiency. To identify the path with the shortest travel time suitable for emergency rescue in wilderness scenarios, a heuristic function based on the fusion of road factors and a path planning model for off-road emergency rescue is developed, and the characteristics of existing roads are weighted in the process of path searching to bias the selection process toward unpaved roads with high accessibility. The experiments show that the improved A* algorithm significantly reduces the travel time of off-road vehicles and that path selection is enhanced compared to that with the traditional A* algorithm;moreover, the improved A* algorithm reduces the number of nodes by 16.784% and improves the search efficiency by 27.18% compared with the traditional 16-direction search method. The simulation results indicate that the improved algorithm reduces the travel time of off-road vehicles by 21.298% and improves the search efficiency by 93.901% compared to the traditional A* algorithm, thus greatly enhancing off-road path planning.

关键词： path planning a-star algorithm off-road vehicles efficiency emergency rescue

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Methodologies for automated design of subsea layout alternatives for oil production systems

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APPLIED OCEAN RESEARCH 2023年第1期139卷

作者： Stape, Philip Rapozo, Murilo Fiorenzano Baioco, Juliana Souza Lima, Beatriz Souza Leite Pires Jacob, Breno Pinheiro Rocha, Djalene Maria Univ Fed Rio De Janeiro LAMCSO Lab Comp Methods & Offshore Syst PEC COPPE UFRJ Postgrad Inst Civil Engn Dept Ave Pedro Calmon S-NCidade Univ BR-21941596 Rio De Janeiro RJ Brazil CENPES Res & Dev Ctr Petrobras Petr Brasileiro SA Ave Horacio Macedo 950Cidade Univ BR-21941915 Rio De Janeiro RJ Brazil

This work presents methodologies to automate the synthesis of subsea layouts for oil production systems. The objective is to achieve a higher number of design alternatives, in less time, with increased efficiency and sig-nificant reduction in associated costs. The result is a computational tool that automatically explores different platform locations;for each location, considering several engineering criteria, it generates and evaluates alter-natives for the spatial arrangement not only of the multiple flowline routes, but also of the riser connection order on the riser porch at the platform balcony. The quality of each solution is evaluated through metrics that include total flowline length. Several methods associated to the modeling and solution of the problem are presented, including: the algorithm that selects the order in which the risers will be connected;the routing algorithm that defines the trajectory of the flowlines;and the global search method for positioning the platform. Case studies are presented to demonstrate their performance, applied to representative offshore scenarios. The results indicate substantial improvement in response time, generating several efficient solutions in few minutes, as opposed to weeks that are usually required in the traditional design procedure. This way, the tool can reduce the design time to evaluate a higher number of alternative layouts, providing accurate results, and minimizing costs.

关键词： Subsea layout Flowline routing Riser porch connection a-star algorithm

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Designing an Autonomous Vehicle Using Sensor Fusion Based on Path Planning and Deep Learning algorithms

SAIEE AFRICA RESEARCH JOURNAL

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SAIEE AFRICA RESEARCH JOURNAL 2024年第3期115卷 86-98页

作者： Suprapto, Bhakti Y. Dwijayanti, Suci Hafiz, Dimsyiar M. A. Ardandy, Farhan A. Jonathan, Javen Univ Sriwijaya Elect Engn Dept Palembang 30662 Indonesia

Autonomous electric vehicles use camera sensors for vision-based steering control and detecting both roads and objects. In this study, road and object detection are combined, utilizing the YOLOv8x-seg model trained for 200 epochs, achieving the lowest segmentation loss at 0.53182. Simulation tests demonstrate accurate road and object detection, effective object distance measurement, and real-time road identification for steering control, successfully keeping the vehicle on track with an average object distance measurement error of 2.245 m. Route planning for autonomous vehicles is crucial, and the a-star algorithm is employed to find the optimal route. In real-time tests, when an obstacle is placed between nodes 6 and 7, the a-star algorithm can reroute from the original path (5, 6, 7, 27, and 28) to a new path (5, 6, 9, 27, and 28). This study demonstrates the vital role of sensor fusion in autonomous vehicles by integrating various sensors. This study focuses on sensor fusion for object-road detection and path planning using the A* algorithm. Real-time tests in two different scenarios demonstrate the successful integration of sensor fusion, enabling the vehicle to follow planned routes. However, some route nodes remain unreachable, requiring occasional driver intervention. These results demonstrate the feasibility of sensor fusion with diverse tasks in third-level autonomous vehicles.

关键词： a-star algorithm object detection path planning road detection sensor fusion YOLOv8

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GPS probe map matching algorithm based on spatial data model

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Journal of Southeast University(English Edition) 2010年第3期26卷 461-465页

作者：王卫过秀成侯佳东南大学交通学院南京210096

To improve the performance of the traditional map matching algorithms in freeway traffic state monitoring systems using the low logging frequency GPS （global positioning system） probe data, a map matching algorithm based on the Oracle spatial data model is proposed. The algorithm uses the Oracle road network data model to analyze the spatial relationships between massive GPS positioning points and freeway networks, builds an N-shortest path algorithm to find reasonable candidate routes between GPS positioning points efficiently, and uses the fuzzy logic inference system to determine the final matched traveling route. According to the implementation with field data from Los Angeles, the computation speed of the algorithm is about 135 GPS positioning points per second and the accuracy is 98.9%. The results demonstrate the effectiveness and accuracy of the proposed algorithm for mapping massive GPS positioning data onto freeway networks with complex geometric characteristics.

关键词： GPS probe map matching a-star algorithm fuzzy logic Oracle spatial data model

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A comprehensive ship weather routing system using CMEMS products and A* algorithm

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OCEAN ENGINEERING 2022年 255卷

作者： Grifoll, Manel Boren, Clara Castells-Sanabra, Marcella Univ Politecn Cataluna Civil & Environm Engn Dept UPC BarcelonaTech Barcelona 08028 Spain Univ Politecn Catalunya UPC BarcelonaTech Naut Sci & Engn Dept Barcelona 08003 Spain

We describe the implementation of a comprehensive software for Ship Weather Routing referred to as SIMROUTE. The A* pathfinding algorithm is used to optimize the sailing route as a function of the wave action. The aim of the software is to provide a comprehensive, open and easy tool including pre- and post-processing for ship weather routing simulations. The software is constructed considering the Copernicus Marine Environment Monitoring Service (CMEMS) wave predictions systems which are available for free use. The code provides the optimized route and the minimum distance route together with additional modules to compute ship emission and safety on navigation monitoring. SIMROUTE has been tested in several cases using different CMEMS products over short and long distances. The comprehensive structure of the code enables it to be easily modified to include additional ship wave resistance models and the effect of the water currents and winds on navigation. SIMROUTE is also used for academic purposes, providing skills for ship routing optimization in the framework of standards of training, certification and watchkeeping (STCW) for competence-based maritime education and training. Due to the simplicity of its use, SIMROUTE is a good candidate for benchmarking strategies and inter-comparison exercises with advanced methods for ship weather routing. This contribution highlights the technical aspects, code organization and structure behind SIMROUTE, demonstrating its capabilities through examples of route optimization.

关键词： Weather ship routing a-star algorithm CMEMS Ship emissions SIMROUTE

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Development of a Virtual Pet Simulator for Pain and Stress Distraction for Pediatric Patients using Intelligent Techniques

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INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS 2021年第2期12卷 539-549页

作者： Solis-Vargas, Angie Contreras-Alcazar, Iam Sulla-Torres, Jose Univ Nacl San Agustin Arequipa Escuela Profes Ingn Sistemas Arequipa Peru

Pediatric medical procedures are often stressful and painful for children, so they can resist and make the work of doctors and nurses a little more complicated. This research aims to develop a virtual pet simulator to distract pediatric patients from pain and stress using smart techniques. The methodology used is SUM. The primary data for the development of the simulator were gravity, the player's position, the speed, and the mass for the calculation of the predictive physics in the toy to interact with the pet. As part of the intelligent techniques, the a-star algorithm was used for the pet to follow the user and the flocking algorithm to have a natural behavior of a group of animals and thus have a higher immersion level. Trials were conducted with pediatric patients where those who made use of the virtual pet simulator during the medical procedure felt less pain and stress than those who did not try the simulator. Therefore, it is highly recommended to use alternatives such as the one developed to reduce pain and stress in pediatric patients.

关键词： Virtual pet pediatric patients pain stress smart techniques a-star algorithm flocking algorithm

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A Heuristic Motion Planning algorithm for a Mobile Robot With Nonholonomic Constraints

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JOURNAL OF ROBOTICS 2024年第1期2024卷

作者： Tran, Duc Thien Pham, Duc Huy Nguyen, Quang Chien Ho Chi Minh City Univ Technol & Educ Automatic Control Dept Ho Chi Minh Vietnam

This paper proposes a heuristic motion planning algorithm to enhance optimal path determination and tracking for a differential drive mobile robot within a global environment. The proposed method uses the A-star search algorithm to discover the optimal path between the start and goal vertices. This algorithm employs precise distance values and heuristic distance values to compute and expand the vertex for identifying a suitable path. When the path is generated, the movement of the robot is regulated by an attractive potential field (APF) and a repulsive potential field (RPF). The APF assists the robot in following its designed path, while the RPF is employed to avoid obstacles. Subsequently, the APF plays a role in helping the robot return to its trajectory. In case of obstacles obstruct the path, the a-star algorithm identifies a new alternative route starting from the current position to the goal, and the robot navigates along this path. During a series of scenario evaluation, the algorithm demonstrates the ability to present optimal solutions in complex environments. To validate the effectiveness of the system, the simulation is executed with the Webots R2021a software. Then, experimental verification for the designed robot demonstrates the system's high accuracy in tracking and obstacle avoidance on a specific map.

关键词： a-star algorithm mobile robot motion planning PID controller potential field

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