témavezető: Esztergár-Kiss Domokos
helyszín (magyar oldal): Department of Transport Technology and Economics helyszín rövidítés: KUKG
A kutatási téma leírása:
a) Background:
The increasing volume of transport demand contributes to congestions on roads, which leads to delays and other negative impacts. Moreover transportation is one of the main contributors to emissions, therefore governmental institutions and commercial organizations are looking for solutions to mitigate these negative effects. Analyzing urban mobility patterns helps understanding travel habits of passengers and possibly decreases journey times, while maintaining transportation services. This should increase the quality of transportation services, thus transportation related processes could be optimized.
b) Aim of research:
The analysis of information and optimization of mobility patterns has been a research topic since a long time ago, but a significantly enhanced interest can be observed in the last decade. Therefore the aim of the proposed research is to develop an activity chain based model integrating technological and organizational aspects, providing fast, secure and optimal flow of passengers.
In the research a novel framework will be presented to support utilities maximization and regrets minimization models. The simulations will include stochastic elements in form of travel times, whereas the optimization model represents a deterministic service network design. Using choice models user decisions can be analyzed and predicted to provide best alternatives. Specifically some attributes will be modeled using conventional Utility Maximization approach (RUM), while others by Random Regret Minimization approach (RRM).
The results of the proposed research have the potential to be integrated into various Intelligent Transportation Systems applications by combining available traveler information services. To assist that process, strategic developments are realized in those areas, where they can provide most efficient functioning. The developments assist travelers in making more informed decisions regarding their travel plans and provide transportation service providers with an overall assessment of the system and its performance.
c) Main tasks of research:
• Assessment of the state-of-the-art research
• Activity based modeling theory
• Application of urban simulation software
• Research about advanced data collection technologies
• Research about advanced optimization methods
• Development of an activity chain optimization method using specific utility functions
• Simulation of the developed method with real data
• Testing and validation of the developed models and algorithms
d) HW/SW tools provided for research:
• PC
• MATLAB
• MATSIM
• VISSIM, VISUM
e) 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
f) Bibliography:
• Esztergár-Kiss D., Rózsa Z. (2015) Simulation results for a daily activity chain optimization method, MT-ITS 2015, 4th International Conference on Models and Technologies for Intelligent Transportation Systems, Budapest, Hungary, 03.06.2015-05.06.2015, pp. 259-264, ISBN 978-963-313-141-1
• Esztergár-Kiss D., Munkácsy A., Velázquez G. (2016) Definition and classification of parameters for daily activity chain optimization, Transportation Research Procedia, 3rd Conference on Sustainable Urban Mobility, 3rd CSUM 2016, 26 – 27 May 2016, Volos, Greece – accepted
• Timmermans, H. (2005) Progress in activity-based analysis, Elsevier Science Ltd, ISBN: 9780080445816
• 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.
előírt nyelvtudás: English (high level) felvehető hallgatók száma: 1
Jelentkezési határidő: 2018-04-24
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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