Towards Scalable Dynamic Traffic Assignment With Streaming Agents: A Decentralized Control Approach Using Genetic Programming
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gp-bibliography.bib Revision:1.7954
- @Article{Liao:2024:ETCI,
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author = "Xiao-Cheng Liao and Wei-Neng Chen and Ya-Hui Jia and
Wen-Jin Qiu",
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journal = "IEEE Transactions on Emerging Topics in Computational
Intelligence",
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title = "Towards Scalable Dynamic Traffic Assignment With
Streaming Agents: A Decentralized Control Approach
Using Genetic Programming",
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year = "2024",
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volume = "8",
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number = "1",
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pages = "942--955",
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abstract = "Traffic assignment is of great importance in real life
from foot traffic assignment of a building to vehicle
traffic assignment of a city. With the rapid increase
of the number of agents and the size of the traffic
network, the problem becomes more and more challenging
nowadays. To solve large-scale efficient dynamic
traffic assignment, this article proposes a
decentralized control approach to achieving this.
First, we transform the traffic assignment problem into
a routing rule generation problem by designing a
corresponding simulation-based optimisation framework
that can evaluate the performance of routing rules.
Then, we propose a genetic programming hyper-heuristic
algorithm to generate the optimal routing rule. During
execution, agents can collect environmental information
and plan their paths when moving according to the
generated rule. In this way, the proposed method can
handle the dynamically changing traffic flow
efficiently instead of pre-planing the whole path for
each agent. The proposed method is verified on both
synthetic networks and real-world networks in terms of
sensitivity, generality, and scalability. The
experimental results demonstrate that our method is
effective in urban-scale traffic networks and
outperforms the compared algorithms.",
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keywords = "genetic algorithms, genetic programming, Biological
cells, Heuristic algorithms, Transportation, Tail,
Symbols, Navigation, Adaptation models, routing,
traffic assignment",
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DOI = "doi:10.1109/TETCI.2023.3296671",
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ISSN = "2471-285X",
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month = feb,
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notes = "Also known as \cite{10197148}",
- }
Genetic Programming entries for
Xiao-Cheng Liao
Wei-Neng Chen
Ya-Hui Jia
Wen-Jin Qiu
Citations