Scalable link cost learning for real-time route guidance systems

•Developed a learning-based framework for RGS using multi-armed bandit (MAB)•Modeled latent factors as link weights, integrating real-time large-scale GPS data.•Achieved an improvement in compliance rates from 64.22 % to 70.87 % in real-world RGS experiments.•Validated scalability through national-s...

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Vydané v:	Transportation research. Part C, Emerging technologies Ročník 178; s. 105244
Hlavní autori:	Kim, Pooreumoe, Yun, Hyunsoo, Kim, Jungmin, Kim, Dong-Kyu
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier Ltd 01.09.2025
Predmet:	Link cost learning Multi-armed bandit Online learning Reinforcement learning Route guidance system User compliance Route guidance system Link cost learning User compliance Online learning Multi-armed bandit Reinforcement learning
ISSN:	0968-090X
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