Intelligent Transportation System

Major: Transport Technology (by type)
Code of subject: 8.275.00.M.024
Credits: 3.00
Department: Transport Technologies
Lecturer: Associate Professor Mykola Zhuk.
Semester: 4 семестр
Mode of study: денна
Learning outcomes: 1. To simulate multimodal transport networks; 2. To make forecasting of state variables and behavior of transport networks users; 3. To simulate multimodal transport networks in real time; 4. To support users in the multimodal network; 5. To design and manage multimodal intelligent transport systems operatively; 6. Improve the parameters of the demand and supply model.
Required prior and related subjects: • Intelligent transport and urban logistics; • Modeling of traffic flows; • Information provision of traffic participants; • Fundamentals of transport research and forecasting.
Summary of the subject: ITS planning. Services for ITS users. Network models and their use in transport engineering. Forecast of network status variables. New technologies of ITS. Systems for monitoring, collecting and sending information about vehicles. Elements of the vehicle-infrastructure, user-control center. Real-time transport network forecasting. Specification, calibration and testing of ITS models. Examples of application of ITS models.
Assessment methods and criteria: • writing reports from practical work, oral examination (40%); • final control (55% control measure, test); • oral form (5 %).
Recommended books: 1. Cascetta, E. (2009). Transportation Systems Analysis: Models and Applications. Springer. 2. Ortuzar S, J. D. D. and Willumsen, L. G. (2001). Modelling transport. Chichester New York, J. Wiley. 3. Sussman, J. S. Perspectives on Intelligent Transportation Systems (ITS) [Текст] / Joseph S. Sussman. – Springer, 2005. – 229 p. 4. Ceder, A. (2015) Public Transit Planning and Operation: Modeling, Practice and Behavior, Second Edition - CRC Press Book. 5. Mogre, R. Intelligent Transportation Systems: A Private Organizations Perspective [Текст] / Riccardo Mogre. LAP Lambert Acad. Publ., 2010. – 156 p. 6. Hyndman, R. B. and Athanasopoulos, G. (2018) Forecasting: principles and practice. 7. Support tools R - R Project for Statistical Computing MS Office (Excel, Word, PowerPoint).