Thesis supervisor: Tamás Tettamanti
Location of studies (in Hungarian): Dept. of Control for Transportation and Vehicle Systems Abbreviation of location of studies: KJIT
Description of the research topic:
Detailed description of the research:
a) Background:
Future mobility is about to change. On the one hand, significant technological improvements have been achieved in the field of driver assistance systems and vehicle automation. On the other hand, car ownership is changing from individual to collective ownership. Both factors will have an impact on congestion, parking spot occupation, energy source supply and urban traffic. A key question is, how to prepare infrastructure for the new forms of mobility. Major improvement in intelligent mobility management have to be made to keep track of the fast-changing environment. How will AVs influence the parking situation, can V2V communication or dynamic parking guidance reduce the time needed to find free parking spaces and is it advantageous to switch to the underground when all inner-city parking spaces are occupied? These are questions that will have to be addressed in the future.
b) Goal of research:
The goal of this proposal is to study the future mobility behavior with automated vehicles and shared mobility concepts. The aim is to build a model to simulate parking behavior under different circumstances such as technological improvements like V2V communication or dynamic car park management or interventions of authorities by e.g. dynamic pricing. Switching to the metro instead of the use of shared/automated carriages should also be considered.
c) Main tasks of research:
• Literature review
• Identify future mobility demand and possibilities for intelligent parking management
• Identify the confounding factors and how the approaches influence each other
• Build a general simulation environment
• Modification of this environment with potential management techniques under the conditions of various technological adaptations
• Extensive testing
• Dissertation writing
e) Minimum expected scientific results:
• Three papers in international SCI indexed journals with impact factor.
• Three articles in international conference papers.
f) Bibliography:
• Greenblatt, J. B., Shaheen, S. (2015). Automated vehicles, on-demand mobility, and environ-mental impacts. Current sustainable/renewable energy reports, 2(3), 74-81.
• de Almeida Correia, G. H., van Arem, B. (2016). Solving the User Optimum Privately OwnedAutomated Vehicles Assignment Problem (UO-POAVAP): A model to explore the impacts ofself-driving vehicles on urban mobility. Transportation Research Part B: Methodological, 87,64-88.
• Fagnant, D. J.,Kockelman, K. M. (2014). The travel and environmental implications ofshared autonomous vehicles, using agent-based model scenarios. Transportation Research PartC: Emerging Technologies, 40, 1-13.
• Kondor, D., Zhang, H., Tachet, R., Santi, P., Ratti, C. (2018). Estimating savings in park-ing demand using shared vehicles for home–work commuting. IEEE Transactions on IntelligentTransportation Systems, 20(8), 2903-2912.
• Ni, J., Zhang, K., Yu, Y., Lin, X., Shen, X. (2018). Privacy-preserving smart parking naviga-tion supporting efficient driving guidance retrieval. IEEE Transactions on Vehicular Technology,67(7), 6504-6517.
• Aliedani, A., Loke, S. W., Desai, A., Desai, P. (2016, September). Investigating vehicle-to-vehiclecommunication for cooperative car parking: The copark approach. In 2016 IEEE InternationalSmart Cities Conference (ISC2) (pp. 1-8). IEEE.
• Kotb, A. O., Shen, Y. C., Zhu, X., Huang, Y. (2016). iParker—A new smart car-parking systembased on dynamic resource allocation and pricing. IEEE transactions on intelligent transportationsystems, 17(9), 2637-2647.
Required language skills: English (min. medium level) Further requirements: proper knowledge of control theory and informatics (basic programming)
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