Electric Multimodal Transport Systems for Enhancing Urban Accessibility and Connectivity (e-MATS), 699469 EUR to the European partners, 250000 EUR to Politehnica University of Timisoara (UPT), 4000000 RMB (equivalent 510509.63 EUR) to the Chinese partners, UPT financed by the Executive Agency for Higher Education, Research, Development and Innovation Funding (UEFISCDI), 2024-2026, project code: ERANET-ENUAC-e-MATS
The link to the project's website, which provides information and facts about the project at JPI Urban Europe:
The partners:
- Zhejiang University (ZJU), China, Prof. Sheng Jin - director of the project coordinator ZJU.
- Swedish National Road and Transport Research Institute (VTI), Sweden, Dr. David Daniels - director of VTI partner.
- Chalmers University of Technology (CTH), Sweden, Dr. Kun Gao - director of European co-coordinator and partner CTH.
- Chongqing University (CQU), China, Prof. Xiaosong Hu - director of CQU partner.
- The Hong Kong Polytechnic University Shenzhen Research Institute (PolyU-SZRI), China, Dr. Wen Yi - director of PolyU-SZRI partner.
- WSP Sverige AB (WSP), Sweden, Mr. Lars Drageryd - director of WSP partner.
- FellowBot AB (FellowBot), Sweden, Ms. Sida Jiang - director of FellowBot partner.
- Hangzhou Comprehensive Transportation Center (HZCTC), China, Mr. Haiwei Wu - director of HZCTC partner.
- Enjoyor Ltd Co. (Enjoyor), China, Mr. Xiaoyue Wen - director of Enjoyor partner.
The UPT team:
Abstract:
- This project targets to facilitate the development of multimodal transport systems with connected electric public transit and shared micro-mobility for sustainable, more efficient, and equitable mobility services with enhanced urban accessibility and resilience. We establish an interdisciplinary and complementary consortium consisting of leading research institutions, public authorities and industry partners from Romania, Sweden and China, to collectively advance next-generation multimodal transport systems via electrification, connectivity and sharing. With strong and complementary track records and resources, the consortium envisages holistically tackling critical and unsettled aspects in the current practice. We will develop holistic methodological and technical innovations through co-creation among key stakeholders at multiple levels, including infrastructure planning at the strategical level, system optimization, network design and management at the tactical level, and vehicle/platoon control and battery management at the operational level, with considerations of diverse users' needs and behavioral responses. The applicability and value of the project can be demonstrated in real-life applications through public authorities and industry partners. These ultimately contribute to promoting urban accessibility and connectivity, climate action in the transport sector, and the citizens' subjective well-being in the long term.
Objective:
- The main objective of this project is to facilitate the development of multimodal transport systems with connected electric public transit and shared micro-mobility for sustainable, more efficient, and equitable mobility services with enhanced urban accessibility and resilience. The achievement of this objective requires the achievement of the following particular objectives (1., 2., 3., and 4.) during the three years of the project:
1. At the strategical level, developing a holistic infrastructure planning framework and methods that reconciles the transit network, shared micro-mobility (SMM), charging facilities, and power grid with considerations of user behavior and equit.
2. At the tactical level, developing a tailored electric public transit network and deployment design framework and methods to minimize system expense and maximize efficiency and accessibility, considering the integration with SMM, battery management, charging facilities, effects on the power grid, and travelers' behavioral responses.
3. At the operational level, develop an adaptative operational control framework and methods leveraging information and communication technologies (ICT) and battery management to regulate the running strategies of electric buses in real-time to improve efficiency and resilience. The models can accommodate dynamic demand changes caused by incidents.
4. At the user level, evaluate the users' behavioral responses, resilience, and accessibility of multimodal transport systems, considering psychological factors and user heterogeneity. Meanwhile, strategies for shifting users to sustainable mobility and improving equity will be exploites.
Estimated results:
- A clear project management guidance, including risk management and the procedures for quality assurance.
- Derivation of behavior models for multimodal transit using the collected data about the drivers.
- Reports on dissemination and communication of the results obtained in the first stage of the project.
- An energy system model compatible with the multimodal transit model.
- An optimization model for the transit route structure considering charging facilities, demand distributions, operation timetable, and existing transit networks.
- Reports on dissemination and communication of the results obtained in the second stage of the project.
- An algorithm for adaptive speed control for optimization (minimization) of energy consumption, timetable deviation, and battery degradation.
- Reports on dissemination and communication of the results obtained in the third stage of the project.
Research reports of the UPT partner:
Overall results of the UPT partner (2024-2026):
- 5 papers published in Clarivate Analytics Web of Science (formerly ISI Web of Knowledge) journals with impact factors, cumulated impact factor according to 2023 Journal Citation Reports (JCR) released by Clarivate Analytics in 2024 = 26.1.
- 1 paper published in conference proceedings indexed in Clarivate Analytics Web of Science (formerly ISI Web of Knowledge or ISI Proceedings).
- 2 papers published in conference proceedings indexed in international databases (IEEE Xplore, INSPEC, Scopus, sciencedirect, Springer Link, DBLP).
- 2 book chapters published in Springer.
- One Highly Cited Paper according to Clarivate Analytics Web of Science (Romanian Journal of Information Science and Technology, 2024) as of July/August 2024.
- The results of the project have been promoted through five invited plenary lectures given by Prof. Radu-Emil Precup at international conferences and seminars.
Results of the UPT partner in 2024:
- 5 papers published in Clarivate Analytics Web of Science (formerly ISI Web of Knowledge) journals with impact factor, cumulated impact factor according to 2023 Journal Citation Reports (JCR) released by Clarivate Analytics in 2024 = 26.1, 1 paper published in conference proceedings indexed in Clarivate Analytics Web of Science (formerly ISI Web of Knowledge or ISI Proceedings), 2 papers published in conference proceedings indexed in international databases (IEEE Xplore, INSPEC, Scopus, sciencedirect, Springer Link, DBLP), 2 book chapters published in Springer.
- One Highly Cited Paper according to Clarivate Analytics Web of Science (Romanian Journal of Information Science and Technology, 2024) as of July/August 2024.
- The results of the project have been promoted through five invited plenary lectures given by Prof. Radu-Emil Precup at international conferences and seminars.
- I. A. Zamfirache, R.-E. Precup (corresponding author) and E. M. Petriu, Adaptive reinforcement learning-based control using proximal policy optimization and slime mould algorithm with experimental tower crane system validation, Applied Soft Computing (Elsevier), vol. 160, paper 111687, pp. 1-15, 2024, impact factor (IF) = 7.2, IF according to 2023 Journal Citation Reports (JCR) released by Clarivate Analytics in 2024 = 7.2, Q1 quartile, Article Influence Score (AIS) = 1.282 (www.sciencedirect.com).
- R.-E. Precup, R.-C. Roman, E.-L. Hedrea, E. M. Petriu, C.-A. Bojan-Dragoş and A.-I. Szedlak-Stînean, Metaheuristic-based tuning of proportional-derivative learning rules for proportional-integral fuzzy controllers in tower crane system payload position control, Facta Universitatis, Series: Mechanical Engineering (University of Nis), vol. 22, no. 4, pp. 1-16, DOI: 10.22190/FUME240914044P, 2024, impact factor (IF) = 10.1, IF according to 2023 Journal Citation Reports (JCR) released by Clarivate Analytics in 2024 = 10.1, Q1 quartile, Article Influence Score (AIS) = 0.850 (casopisi.junis.ni.ac.rs).
- R.-C. Roman, R.-E. Precup (corresponding author), E. M. Petriu and A.-I. Borlea, Hybrid Data-Driven Active Disturbance Rejection Sliding Mode Control with Tower Crane Systems Validation, Romanian Journal of Information Science and Technology (Romanian Academy, Section for Information Science and Technology), vol. 27, no. 1, pp. 50-64, 2024, impact factor (IF) = 3.7, IF according to 2023 Journal Citation Reports (JCR) released by Clarivate Analytics in 2024 = 3.7, Q1 quartile, Article Influence Score (AIS) = 0.462, Highly Cited Paper according to Clarivate Analytics Web of Science as of July/August 2024 (www.romjist.ro).
- S. Travin, O. B. Gromov, G. Duca and R.-E. Precup (corresponding author), Statistical Computational Model of Fission Products Composition of Irradiated Nuclear Fuel and Their Contribution to Gas-aerosol Emissions of Nuclear Power Plants, Romanian Journal of Information Science and Technology (Romanian Academy, Section for Information Science and Technology), vol. 27, no. 3-4, pp. 310-322, 2024, impact factor (IF) = 3.7, IF according to 2023 Journal Citation Reports (JCR) released by Clarivate Analytics in 2024 = 3.7, Q1 quartile, Article Influence Score (AIS) = 0.462 (www.romjist.ro).
- C. Pozna, R.-E. Precup and A. Ballagi, Using Tensor-Type Formalism in Causal Networks, Acta Polytechnica Hungarica, vol. 21, no. 10, pp. 75-91, 2024, impact factor (IF) = 1.4, IF according to 2023 Journal Citation Reports (JCR) released by Clarivate Analytics in 2024 = 1.4, Q2 quartile, Article Influence Score (AIS) = 0.151 (www.uni-obuda.hu/journal/).
- Cl. Pozna, R.-E. Precup and A. Ballagi, Hamiltonian-Based Control Approach with Pendulum Application, Proceedings of IEEE 18th International Symposium on Applied Computational Intelligence and Informatics SACI 2024, Siofok, Hungary, and Timisoara, Romania, pp. 593-598, 2024, indexed in Clarivate Analytics Web of Science (ieeexplore.ieee.org).
- R.-C. Roman, R.-E. Precup and E. M. Petriu, Active Disturbance Rejection Control for 3D Crane Systems, 11th International Conference on Information Technology and Quantitative Management (ITQM 2024), Procedia Computer Science (Elsevier), vol. 242, pp. 976-983, 2024, indexed in Scopus (www.sciencedirect.com).
- A.-I. Szedlak-Stînean, R.-E. Precup and N.-L. Iancu, Classical and Fuzzy Controllers for an Optimally Tuned Model of a Strip Winding System, Proceedings of 2024 International Semiconductor Conference CAS 2024, Sinaia, Romania, 2024, pp. 13-22, indexed in IEEE Xplore (ieeexplore.ieee.org).
- C.-R. Pozna, R.-E. Precup (corresponding author) and A. Ballagi, Tensor-Based Approach to Diagnostic Causal Network Modeling, in: Recent Advances in Intelligent Engineering, L. Kovacs, T. Haidegger and A. Szakal, Eds. Topics in Intelligent Engineering and Informatics, vol. 18, Springer, Cham, pp. 119-137, 2024, indexed in Springer Link (link.springer.com, link.springer.com).
- R.-C. Roman, E.-L. Hedrea, R.-E. Precup (corresponding author), C.-A. Bojan-Dragoş and A.-I. Szedlak-Stînean, Iterative Feedback Tuning Algorithms for Two Rotor Aerodynamic Systems, in: Decision Making and Decision Support in the Information Era, V. E. Balas, G. Dzemyda, S. Belciug and J. Kacprzyk, Eds., Studies in Systems, Decision and Control, vol. 534, Springer, Cham, pp. 337-364, 2024, indexed in Springer Link (link.springer.com, link.springer.com).