Thesis supervisor: Domokos Esztergár-Kiss
Location of studies (in Hungarian): Transport Technology and Economics Abbreviation of location of studies: KUKG
Description of the research topic:
Providing high quality transportation requires continuous research and elaboration of studies, because it is connected to daily desires of people. Mobility improvements change the transportation system in terms of technology, services, environmental and social aspect. Transportation is becoming smarter, more efficient and more environmentally friendly and innovation in technology leads to the possibility to analyze pattern in different aspects of life, especially travel behavior in transportation. Transportation research has seen a gradual shift from trip-based, via tour-based to activity-based models, in an effort to capture the true complexity of travel behavior, therefore the analysis of activity based models is highly required.
Another paradigm is the introduction of car-sharing system, which leads to reduction of vehicle ownership, mitigation of traffic density on roads and as a result better environmental circumstances. Also self driving autonomous vehicles systems will play a crucial element in changing travel behaviour and optimizing time and distances needed for conducting a trip.
Moreover the integration of these two systems with other transportation modes requires studying user behaviour and optimization possibilities of multimodal travel chains. This optimization will be presented by integrating these systems into available activity based models. The optimization is based on surveys and data collected from existing travel planners and statistical techniques.
Available activity optimization chain framework could be upgraded and developed to consider both system car-sharing and autonomous systems. Therefore this research will study, seek, search and develop an activity based travel chain model with utility function for different modes, and a proper algorithm considering different attributes of traveler perspectives and attributes.
The effects of autonomous systems on network requires studying the behavior of passenger demand, therefore a simulation model could be developed to simulate the shift of people from traditional modes to car-sharing and autonomous systems in order to deduce the consequences in terms of distances, time congestions, comfort, fuel consumption, optimization parameters and others.
Main tasks of research:
• Developing/upgrading an activity based multimodal travel chain optimization model involving new transportation modes and technologies (autonomous and car-sharing)
•Studying the distribution of car-sharing demand and their implications on the behavior of existing multimodal travel chain
• Studying the effectiveness use of autonomous vehicles and their influence on travel behavior mode choice
• Creating an algorithm that combines existing transportation modes and specifications of car-sharing and autonomous systems.
Minimum expected scientific results:
• 1 paper in international journal with Impact Factor
• 2 papers in international journal indexed in Scopus
• 4 conference papers in international conferences
Bibliography:
Esztergár-Kiss D., Rózsa Z., Tettamanti T. (2018) Extensions of the activity chain optimization method, Journal of Urban Technology, Taylor and Francis, Vol 25, Issue 2, pp 125-142., ISSN 1063-0732, DOI 10.1080/10630732.2017.1407998
Arentze T.A (2013) Adaptive Personalized Travel Information Systems: A Bayesian Method to Learn Users' Personal Preferences in Multimodal Transport Networks, IEEE Transactions on Intelligent Transportation Systems, Vol.14, Issue 4 , pp. 1957-1966.
Nijland L., Arentze T., Timmermans H. (2012) Incorporating planned activities and events in a dynamic multi-day activity agenda generator, Transportation, Vol.39, Issue 4, pp. 791-806.
Charypar D., Nagel K. (2005) Generating complete all-day activity plans with genetic algorithms, Transportation, Vol. 32, Issue 4, pp. 369-397.
Miller E.J., Roorda M.J. (2003) Prototype Model of Household Activity-Travel Scheduling, Transportation Research Record: Journal of the Transportation Research Board, Issue 1831, pp. 114-121.
Sharmeen F., Arentze T., Timmermans H. (2013) Incorporating Time Dynamics in Activity-travel Behaviour Analysis: A Path Analysis of Changes in Activity and Travel Time Allocation in Response to Life Cycle Events, Transportation Research Record: Journal of Transportation Research Board, Vol. 2382, Issue 1, pp. 54-62.
Certicky M., Drchal J., Cuchy M., Jakob M. (2015) Fully Agent-based Simulation Model of Multimodal Mobility in European Cities, 4th International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS), Budapest, Hungary, 03.06.2015-05.06.2015., ISBN: 978-963-313-142-8
Prelipcean A. C., Gidofalvi G., Susilo Y.O. (2015) Comparative framework for activity-travel diary collection systems, Models and Technologies for Intelligent Transportation Systems (MT-ITS), 2015 International Conference on, Budapest, 2015, pp. 251-258.
Sierpiński G., Staniek M., Celiński I. (2016) Travel behavior profiling using a trip planner, Transportatrion Research Procedia, Vol. 14, pp. 1743-1752.
Dib O., Manier M.A., Moalic L., Caminada A. (2017) Combining VNS with Genetic Algorithm to solve the one-to-one routing issue in road networks, Computers & Operations Research, Vol. 78, pp. 420-430.
Required language skills: English (high level) Recommended language skills (in Hungarian): English (high level) Further requirements: proper knowledge of transportation systems, modeling theory, mathematical methods, informatics and basic programming
Number of students who can be accepted: 1
Deadline for application: 2019-03-21
2024. IV. 17. ODT ülés Az ODT következő ülésére 2024. június 14-én, pénteken 10.00 órakor kerül sor a Semmelweis Egyetem Szenátusi termében (Bp. Üllői út 26. I. emelet).
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