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Engineering and Technology

Transportation Technologies

Transportation Technologies

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This edition covers different topics from the transportation technologies, including control and automation of transport, public transport prediction, techniques to reduce crashes and case studies from different countries. Section 1 focuses on control and automation of the transport, describing fuzzy rules to improve traffic light decisions in urban roads; evaluation of merge control strategies at interstate work zones under peak and off-peak traffic conditions; modulating traffic signal phases to realize real-time traffic control system; traffic regulation at critical intersections: a case study of Odole intersection, Akure, Nigeria. Section 2 focuses on techniques to reduce crashes, describing comprehensive study of single and multiple truck crashes using violation and crash data; predicting truck at-fault crashes using crash and traffic offence data; road traffic crash data: an overview on sources, problems, and collection methods; road crash prediction models: different statistical modeling approaches; high-risk rural road safety study and determining the crash-reduction factors for high-risk rural-road usage. Section 3 focuses on public transport prediction, describing prediction of civil aviation passenger transportation based on ARIMA model; present assessment of public traffic system based on GIS in Kitakyushu; development of a GIS based public transport composite social need index in Jeddah; evaluation of past investment in urban public transportation. Section 4 focuses on case studies from different countries, describing transport policy - the perspective of Swedish stakeholders; Spanish initiative for the automation in urban transport: AutoMOST; fuzzy analysis and evaluation of public transport service quality: a case study of Dar-es Salaam city, Tanzania; intermodal terminal localization using a linear programming approach: the case study of Togo and west African landlocked countries; study on objectives and strategies for energy conservation and emission reduction in transportation industry during the 13th five-year plan period in Beijing.

Dr. Zoran Gacovski has earned his PhD degree at Faculty of Electrical engineering, Skopje. His research interests include Intelligent systems and Software engineering, fuzzy systems, graphical models (Petri, Neural and Bayesian networks), and IT security. He has published over 50 journal and conference papers, and he has been reviewer of renowned Journals. Currently, he is a professor in Computer Engineering at European University, Skopje, Macedonia.