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Application of multi-agent systems in traffic and transportation
Abstract
Agent-oriented techniques offer a new approach to support the whole software development process. All the phases in the software development process are treated with a single uniform concept, namely that of agents, and a system modelled by a collection of agents is called a multi-agent system. AOTs as a new advance in information technology can help to respond to the growing interest in making traffic and transportation more efficient, resource-saving and ecological. The authors give an overview of a diverse range of applications where multi-agent systems promise to create a great impact in this domain. To demonstrate the ideas behind AOTs and their applicability in this domain, two applications currently under development at Daimler-Benz Research are described in some detail.
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Cited by
On agent-based software engineering
Jennings, N. R. (2000) · Artificial Intelligence · doi:10.1016/s0004-3702(99)00107-1 · Cited by 1,635
AI enabled applications towards intelligent transportation
Iyer, L. S. (2021) · Transportation Engineering · doi:10.1016/j.treng.2021.100083 · Cited by 315
Lyapunov-Based Reinforcement Learning for Decentralized Multi-agent Control
Zhang, Q., Dong, H., & Pan, W. (2020) · Lecture Notes in Computer Science · doi:10.1007/978-3-030-64096-5_5 · Cited by 18
Metadata
- Authors
- Burmeister, B., Haddadi, A., & Matylis, G.
- Venue
- IEE Proceedings - Software Engineering
- Published
- 1997
- Volume
- 144
- Issue
- 1
- Pages
- 51
- ISSN
- 1364-5080 (ISSN-L)
- OpenAlex
- W2166075343
- Cited by
- 183
- References
- 0
- FWCI
- 4.76
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Application of multi-agent systems in traffic and transportation. https://app.cochat.ai/papers/10.1049/ip-sen:19971023
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- Burmeister, B., Haddadi, A., & Matylis, G. (1997). Application of multi-agent systems in traffic and transportation. IEE Proceedings - Software Engineering. https://doi.org/10.1049/ip-sen%3A19971023
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
