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  • 标题:Adaptive-AR Model with Drivers’ Prediction for Traffic Simulation
  • 本地全文:下载
  • 作者:Xuequan Lu ; Mingliang Xu ; Wenzhi Chen
  • 期刊名称:International Journal of Computer Games Technology
  • 印刷版ISSN:1687-7047
  • 电子版ISSN:1687-7055
  • 出版年度:2013
  • 卷号:2013
  • DOI:10.1155/2013/904154
  • 出版社:Hindawi Publishing Corporation
  • 摘要:We present a novel model called A2R—“Adaptive-AR”—based on a well-known continuum-based model called AR Aw and Rascle (2000) for the simulation of vehicle traffic flows. However, in the standard continuum-based model, vehicles usually follow the flows passively, without taking into account drivers' behavior and effectiveness. In order to simulate real-life traffic flows, we extend the model with a few factors, which include the effectiveness of drivers' prediction, drivers' reaction time, and drivers' types. We demonstrate that our A2R model is effective and the results of the experiments agree well with experience in real world. It has been shown that such a model makes vehicle flows perform more realistically and is closer to the real-life traffic than AR (short for Aw and Rascle and introduced in Aw and Rascle (2000)) model while having a similar performance.
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