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Cloud Computing for Agent-Based Urban Transportation Systems
Abstract
Agent-based traffic management systems can use the autonomy, mobility, and adaptability of mobile agents to deal with dynamic traffic environments. Cloud computing can help such systems cope with the large amounts of storage and computing resources required to effectively use of traffic strategy agents and mass transport data. This article reviews the history of the development of traffic control and management systems within the evolving computing paradigm and shows the state of traffic control and management systems based on mobile multiagent technology. An intelligent transportation cloud could provide services such as decision support, a standard development environment for traffic management strategy, and so on. Moreover, the cloud can generate, store, manage, test, optimize, and use mobile traffic strategy agents to maximize advantages of cloud computing and agent technology to effectively control and manage urban-traffic systems.
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Cites
Toward a Revolution in Transportation Operations: AI for Complex Systems
Wang, F.-Y. (2008) · IEEE Intelligent Systems · doi:10.1109/mis.2008.112 · Cited by 149
Cited by
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Ozatay, E., Onori, S., Wollaeger, J., Ozguner, U., Rizzoni, G., Filev, D., Michelini, J., & Di Cairano, S. (2014) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2014.2319812 · Cited by 294
Architecture and key technologies for Internet of Vehicles: A survey
Yang, F., Li, J., Lei, T., & Wang, S. (2017) · Journal of Communications and Information Networks · doi:10.1007/s41650-017-0018-6 · Cited by 129
Autonomous shared mobility-on-demand: Melbourne pilot simulation study
Dia, H., & Javanshour, F. (2017) · Transportation Research Procedia · doi:10.1016/j.trpro.2017.03.035 · Cited by 121
Intelligent Transport System: A Progressive Review
Zear, A., Kumar Singh, P., & Singh, Y. (2016) · Indian Journal of Science and Technology · doi:10.17485/ijst/2016/v9i32/100713 · Cited by 64
On Developing Smart Transportation Applications in Fog Computing Paradigm
Giang, N. K., Leung, V. C. M., & Lea, R. (2016) · Proceedings of the 6th ACM Symposium on Development and Analysis of Intelligent Vehicular Networks and Applications · doi:10.1145/2989275.2989286 · Cited by 59
Metadata
- Authors
- Li, Z., Chen, C., & Wang, K.
- Venue
- IEEE Intelligent Systems
- Published
- 2011-01
- Volume
- 26
- Issue
- 1
- Pages
- 73-79
- ISSN
- 1541-1672 (ISSN-L)
- OpenAlex
- W2133078284
- Cited by
- 177
- References
- 1
- FWCI
- 32.17
- Type
- journal article
- Language
- en
- Open access
- closed
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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
