文章基本信息

标题：Unscented stochastic model predictive perimeter control of uncertain two-regions urban traffic
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作者：Ehsan Harati ; Stelios Timotheou ; Christos Panayiotou 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2020
卷号：53
期号：2
页码：14930-14935
DOI：10.1016/j.ifacol.2020.12.1978
语种：English
出版社：Elsevier
摘要：AbstractIn this article, Stochastic Model Predictive Control (SMPC) is employed for optimal perimeter control of traffic flow with uncertain Macroscopic Fundamental Diagram (MFD), traffic accumulation and traffic demand of two regions. Two regions urban traffic networks are described through the MFD. The MFD is a fundamental relation between average flow (production) and density (accumulation) in urban regions. Although the MFD is often assumed as a simple deterministic curve, possible heterogeneity in urban regions results in large scattering of the MFD pattern. Traffic accumulation is considered uncertain due to limited sources of measurements. Moreover, traffic demand is based on the stochastic nature of drivers. The stochastic uncertainty is modeled through appropriate probability distribution functions for MFD, traffic accumulation and demand. Simulation results show the superiority of the proposed method compared to deterministic MPC in the presence of model mismatch.
关键词：KeywordsMacroscopic fundamental diagramPredictive controlUncertaintyUnscented transformTraffic controlProbabilistic models