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A prediction model with wavelet neural network optimized by the chicken swarm optimization for on-ramps metering of the urban expressway
| 题名： | A prediction model with wavelet neural network optimized by the chicken swarm optimization for on-ramps metering of the urban expressway |
| 正文语种： | eng |
| 作者： | Yusheng Ci;Hailong Wu;Yichen Sun;Lina Wu |
| 作者单位： | School of Transportation Science and Engineering Harbin Institute of Technology;School of Transportation Science and Engineering Harbin Institute of Technology;School of Transportation Science and Engineering Harbin Institute of Technology||Shenzhen Urban Planning & Land Resource Research Center;School of Automobile and Traffic Engineering Heilongjiang Institute of Technology||College of Traffic Northeast Forestry University |
| 关键词： | ALINEA;CSO;on-ramp metering;urban expressway;WNN |
| 摘要： | Abstract Urban expressway, which plays a significant role in medium-and-long distance express travel, influences transport efficiency of an area in a city. The operation efficiency of an urban expressway system can be promoted by on-ramp metering (ORM). Based on ALINEA (asservissement linéaire d'entrée autoroutière) algorithm, this paper proposed an improved ALINEA method with a wavelet neural network (WNN) optimized by chicken swarm optimization (CSO). The algorithm integrates K-means algorithm to select key-point for dynamic multiple on-ramps coordinated control. The amended ALINEA method mainly aimed at solving the problems of the in-flow of the next control period and the mainline multi-lanes condition. Simulation results demonstrated that the coordinated control algorithm proposed can increase the traffic efficiency of the urban expressway. |
| 出版年： | 2022 |
| 期刊名称： | Journal of Intelligent Transportation Systems |
| 卷： | 26 |
| 期： | 1/6 |
| 页码： | 361-370 |
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