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Traffic Density Estimation under Lane Indisciplined Conditions using Strips along the Road Width

机译:使用沿道路宽度的条带,在车道不规则条件下的交通密度估计

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In this paper, a model based estimation scheme has been proposed to estimate density incorporating the heterogeneity and lane indiscipline observed in Indian traffic. In order to incorporate lane indiscipline, the road stretch under study was considered as multiple parallel strips. Time occupancy and composition based weighted vehicle length were used to incorporate heterogeneity. Then, using these, a single state non-continuum macroscopic model was developed with density as the state variable and time occupancy as the output variable. The Kalman filtering technique was used for dynamic estimation of density. The estimator was corroborated using data generated from a microscopic traffic simulation software, VISSIM. Results obtained showed that the proposed approach could provide accurate density estimates and reproduced traffic characteristics better than without considering lane indiscipline.
机译:在本文中,提出了一种基于模型的估计方案,以结合印度交通中观察到的异质性和车道不规则来估计密度。为了纳入车道纪律,研究中的道路延伸被认为是多个平行带。使用时间占用和基于组成的加权车辆长度来合并异质性。然后,使用它们,开发了一个以密度为状态变量和时间占用为输出变量的单状态非连续体宏观模型。卡尔曼滤波技术用于密度的动态估计。使用从微观交通模拟软件VISSIM生成的数据来验证估算器。获得的结果表明,与不考虑车道纪律相比,所提出的方法可以提供准确的密度估计和重现的交通特征。

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