A New Framework of Intelligent Public Transportation System Based on the Internet of Things
Open accessAbstract
As a new paradigm of information technology, the Internet of Things (IoT) is attracting increasing attention from various industrial fields. It is foreseeable that the applications of IoT will be prevalent in the public transportation system and bring changes to the system in the near future. In this paper, we analyze the impact of IoT environment on the public transportation system, propose a new framework of the intelligent public transportation system based on IoT, and present the deployment of the elements, the communication network, and the three-tier architecture of the system in detail. We also present the information flow, technical scheme, optimization model, and algorithm of the main modules of dynamic optimization of the system. The innovative points of this paper lie in: (1) a new framework for public transport system based on IoT, which integrates the scheduling problems of subway, bus, and shared taxi, is proposed for better-coordinated transfer solutions; (2) transport flow prediction methods based on periodic patterns mining is proposed for road flow analysis and passenger flow analysis, and; (3) mathematical model and DSS-based evolutionary computation algorithm are proposed for solving the dynamic bus scheduling and controlling problems. The proposed intelligent transport system based on IoT can assist the decision makers to increase the utilization rate of the transport resources, improve the efficiency of scheduling, and reduce passengers' traveling time.
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Cites
Internet of Things (IoT): A vision, architectural elements, and future directions
Gubbi, J., Buyya, R., Marusic, S., & Palaniswami, M. (2013) · Future Generation Computer Systems · doi:10.1016/j.future.2013.01.010 · Cited by 12,293 · see citing works
Uniform crossover in genetic algorithms
Syswerda, G. (1989) · international conference on Genetic algorithms · Cited by 1,896 · see citing works
Double-horizon based heuristics for the dynamic pickup and delivery problem with time windows
Mitrović-Minić, S., Krishnamurti, R., & Laporte, G. (2003) · Transportation Research Part B Methodological · doi:10.1016/j.trb.2003.09.001 · Cited by 304 · see citing works
Daraio, C. C., Diana, M., Costa, F. D., Leporelli, C., Matteucci, G., & Nastasi, A. (2015) · European Journal of Operational Research · doi:10.1016/j.ejor.2015.05.059 · Cited by 163 · see citing works
Real-Time Control of Buses in a Transit Corridor Based on Vehicle Holding and Boarding Limits
Delgado, F., Muñoz, J. C., Giesen, R., & Cipriano, A. Z. (2009) · Transportation Research Record Journal of the Transportation Research Board · doi:10.3141/2090-07 · Cited by 162 · see citing works
Kyriazis, D., Varvarigou, T., Rossi, A., White, D., & Cooper, J. (2013) · 2013 IEEE 14th International Symposium on "A World of Wireless, Mobile and Multimedia Networks" (WoWMoM) · doi:10.1109/wowmom.2013.6583500 · Cited by 147 · see citing works
A model for holding strategy in public transit systems with real-time information
Zolfaghari, S., Azizi, N., & Jaber, M. Y. (2004) · International Journal of Transport Management · doi:10.1016/j.ijtm.2005.02.001 · Cited by 104 · see citing works
Integration of Smart Phone and IOT for development of smart public transportation system
Sutar, S. H., Koul, R., & Suryavanshi, R. (2016) · doi:10.1109/iota.2016.7562698 · Cited by 87 · see citing works
Advanced public transport and intelligent transport systems: new modelling challenges
Nuzzolo, A., & Comi, A. (2016) · Transportmetrica A Transport Science · doi:10.1080/23249935.2016.1166158 · Cited by 62 · see citing works
Intelligent Public Transportation Systems: A review of architectures and enabling technologies
Elkosantini, S., & Darmoul, S. (2013) · International Conference on Advanced Logistics and Transport (ICALT) · doi:10.1109/icadlt.2013.6568465 · Cited by 61 · see citing works
A Public Transport Bus as a Flexible Mobile Smart Environment Sensing Platform for IoT
Kang, L., Poslad, S., Wang, W., Li, X., Zhang, Y., & Wang, C. (2016) · International Conference on Intelligent Environments (IE) · doi:10.1109/ie.2016.10 · Cited by 38 · see citing works
A survey of cooperative ITS for next generation public transport systems
Seredynski, M., & Viti, F. (2016) · IEEE International Conference on Intelligent Transportation Systems (ITSC) · doi:10.1109/itsc.2016.7795714 · Cited by 31 · see citing works
A public transportation journey planner enabled by IoT data analytics
Puiu, D., Bischof, S., Serbanescu, B., et al. (2017) · doi:10.1109/icin.2017.7899440 · Cited by 24 · see citing works
Bastos, H. Z. L., & Albini, L. C. P. (2016) · IFAC-PapersOnLine · doi:10.1016/j.ifacol.2016.11.174 · Cited by 7 · see citing works
Zheng, F., Chen, S., Zhang, J., et al. (2015) · doi:10.1061/9780784479384.066 · Cited by 6 · see citing works
Design of an IoT-GIS emergency management system for public road transport networks
Du, P. Y., Chen, J., Sun, Z., et al. (2015) · doi:10.1145/2835596.2835611 · Cited by 5 · see citing works
Zhang, S. J., & Chen, S. Y. (2014) · Advanced materials research · doi:10.4028/www.scientific.net/amr.1049-1050.1753 · Cited by 3 · see citing works
Urban Public Transport in China: Benchmarking and Catching Up with Reference Countries
Wu, H., Jiang, Y., Peng, H., et al. (2010) · doi:10.1061/41127(382)282 · Cited by 2 · see citing works
Research for Advanced Public Transport Solutions Based on the IOT
Li, Y., Sun, G., Li, X., et al. (2010) · doi:10.1061/41139(387)73 · Cited by 1 · see citing works
Flagged first, then by citations
Research works printed but not linked: 2
- C. H. Alter, ''Evaluation of public transit services: The level-of-service concept,'' Transp. Res. Rec., no. 606, pp. 37-40, 1976.
- XING-GANG LUO received the M.Sc. degree in mechanical design, and the Ph.D. degree in system engineering and manufacturing from Northeastern University, China. He is the author of over 30 papers on peer-reviewed journals, including EJOR, IJPR, IJPE, C&IE, KBS, IEEE SMC, and IEEE EM. His current research interests include product planning, data mining, and service opera- tion management.
Cited by
Sorted by citations
Machine learning and data analytics for the IoT
Adi, E., Anwar, A., Baig, Z., & Zeadally, S. (2020) · Neural Computing and Applications · doi:10.1007/s00521-020-04874-y · Cited by 279 · see citing works
Design and Implementation of a Cloud-IoT-Based Home Energy Management System
Condon, F., Martínez, J. M., Eltamaly, A. M., Kim, Y.-C., & Ahmed, M. A. (2022) · Sensors · doi:10.3390/s23010176 · Cited by 68 · see citing works
- Authors
- Luo, X.-G., Zhang, H.-B., Zhang, Z.-L., Yu, Y., & Li, K.
- Affiliations
- Hangzhou Dianzi University (CN)
- Northeastern University (CN)
- Venue
- IEEE Access
- Published
- 2019
- Volume
- 7
- Pages
- 55290-55304
- ISSN
- 2169-3536 (ISSN-L)
- OpenAlex
- W2943055507
- Cited by
- 85
- References
- 19
- Citations by year
- 2026: 6 · 2025: 7 · 2024: 12 · 2023: 13 · 2022: 17 · 2021: 12 · 2020: 15 · 2019: 3
- FWCI
- 13.18
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- IEEE Access (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- National Natural Science Foundation of China (71831006, 71771070, 71801065, 71571037)
- Topics
- Social Sciences › Transportation › Transportation Planning and Optimization
- Physical Sciences › Engineering › Control and Systems Engineering › Traffic control and management
- Physical Sciences › Engineering › Civil and Structural Engineering › Urban Transport Systems Analysis
- Keywords
- Internet of Things, shared taxis, passenger demand forecasting, periodic pattern mining, three-tier architecture, decision support system, travel time reduction
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