黑料不打烊

New doctoral dissertation

Library April 22, 2026

黑料不打烊 Library invites you to follow the published new dissertations. The dissertation 鈥炩 (鈥濵iesto dvira膷i懦 eismo sraut懦 modeliavimas atsi啪velgiant 寞 susisiekimo infrastrukt奴ros saugum膮鈥) prepared at 黑料不打烊 by 惭颈驳濒臈 窜补产颈别濒补颈迟臈-厂办颈谤尘补苍迟臈. The dissertation was prepared in 2021鈥2026. Scientific consultant 鈥 Prof. Dr Marija Burinskien臈.

The dissertation was defended at the public meeting of the Dissertation Defence Council of the Scientific Field of Civil Engineering in the Aula Doctoralis Meeting Hall of 黑料不打烊_独家黑料_吃瓜网51爆料 at 10 a.m. on 22 April 2026.

The dissertation examines the impact of bicycle infrastructure solutions on subjective traffic safety and the possibilities of applying bicycle traffic flow forecasting methodologies on city streets. The main objects of the research are the impact of bicycle infrastructure solutions on the subjective sense of safety and the application of bicycle traffic flow forecasting methodologies on city streets. The dissertation aims to determine the accuracy of the aggregated behaviour model and sketch plan method in predicting bicycle traffic flows on city streets, using freely available data, and to determine the impact of different bicycle infrastructure solutions on predicted bicycle traffic flows in terms of subjective safety. The work addresses several main tasks: quantitatively assesses the impact of subjective safety on predicted bicycle traffic flows, and performs bicycle traffic flow forecasting using the aggregated behaviour model and the sketch plan method using freely available data. The dissertation consists of an introduction, three main chapters, general conclusions, lists of references and the author鈥檚 publications on the dissertation topic, and three appendices. The Introduction discusses the research problem and its relevance, defines the research object, outlines the dissertation鈥檚 aim and objectives, describes the research methodology, presents the scientific novelty and practical significance of the results, and introduces the defended statements. The section concludes with a list of the author鈥檚 publications and conference presentations related to the dissertation, as well as the structure of the work. The First Chapter reviews the principles of bicycle infrastructure planning, methods and databases for obtaining bicycle traffic flow data, analyses bicycle traffic flow forecasting methodologies, the data they employ and the accuracy. The Second Chapter describes the conducted theoretical studies, analyses the application of subjective safety in the Lithuanian context, provides its quantitative assessment, presents the results, and outlines the procedure of the experimental bicycle traffic flow forecasting study. The Third Chapter presents the results of experimental bicycle traffic flow studies conducted using aggregate behaviour and sketch planning methodologies, as well as their analyses and an evaluation of the accuracy of these methodologies. Seven scientific articles on the dissertation topic have been published: three in journals indexed in the Clarivate Analytics Web of Science database, one in peer-reviewed international conference proceedings, and three in other national and international conference materials. Four presentations on the dissertation topic were given at Lithuanian conferences, and three at conferences abroad.

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New doctoral dissertation
New doctoral dissertation
黑料不打烊 Library invites you to follow the published new dissertations. The dissertation 鈥濩ontrol of Robot Path Using an Artificial Intelligence System by Fusing Sensor Signal鈥 (鈥濺oboto trajektorijos valdymas dirbtinio intelekto sistema suliejant jutikli懦 signalus鈥) prepared at 黑料不打烊 by Vygantas U拧inskis. The dissertation was prepared in 2021鈥2026. Scientific consultant 鈥 Prof. Dr 聽Vytautas Bu膷inskas. The dissertation was defended at the public meeting of the Dissertation Defence Council of the Scientific Field of Mechanical Engineering in the Aula Doctoralis Meeting Hall of 黑料不打烊_独家黑料_吃瓜网51爆料 at 10 a.m. on 30 April 2026. The dissertation examines the problem of local robot navigation, where sensor data must be processed in real time to assess the environment and generate an adaptive motion trajectory. The research object is a local navigation system with sensor fusion for mobile robots operating in tunnels and confined channels. Navigation is divided into four parts: environment assessment, localisation, path planning, and motion execution. The analysis of localisation technologies enables the selection of an effective sensor set for obstacle detection. Heuristic and artificial intelligence methods allow generating an optimal trajectory that avoids collisions and maintains the goal. The work addresses navigation and obstacle detection in human-inaccessible environments using a cost-efficient combination of active and passive sensors, with experimental validation of the system鈥檚 performance. The dissertation consists of an introduction, three main chapters, conclusions, references, and a list of the author鈥檚 scientific publications on the topic of the dissertation. The introduction presents the problem, relevance, research objective and tasks, methodology, scientific novelty, practical significance, and defended statements, as well as the author鈥檚 publications and the structure of the dissertation. The First Chapter presents a literature review, including an overview and comparison of global and local path-planning methods, localisation technologies and their combinations, and sensor-fusion approaches used in mobile robots. Key factors affecting reliable navigation are identified, forming the basis for the dissertation tasks. The Second Chapter describes the developed research methodology for autonomous tunnel navigation: the operating principles of the red, green and blue (RGB) channel-camera- and laser-based optical obstacle detection system, sensor-fusion techniques, and the application of modified Vector Field Histogram (VFH) and machine-learning-based path-planning methods. The Third Chapter presents the research results: optical system experiments, path-planning simulations, a comparison between machine-learning and modified VFH methods, and the testing of the constructed robot prototype in a laboratory environment. Five research papers have been published on the topic of the dissertation: three in journals indexed in the Web of Science database, and two in conference proceedings. Additionally, five conference presentations related to the dissertation topic have been delivered in Lithuania and abroad. Doctoral dissertation readers can search via聽黑料不打烊 Virtual Library.  
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