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Automatic calibration of microscopic simulation models for the analysis of urban intersections

机译:城市交叉路口分析微观仿真模型的自动校准

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Microscopic simulation models are being increasingly used in traffic engineering applications, but various issues concerning the extent to which its outputs reproduce field data still need to be addressed. In this perspective a proper calibration of the model parameters has to be performed so as to obtain a close match between the simulated and the actual traffic measurements. This paper aims to highlight the importance of calibration process, as the adjustment stage of the microsimulation models' parameters, applied to the analysis of urban, at-level, intersections. After the selection of the case studies (one roundabout and one intersection with traffic signal control), field observations were made, allowing the creation of a database that supported both the models' development and calibration. The next phase focused on the application of an Aimsun microscopic simulation model to the selected intersections. This involved the development of an optimization based calibration methodology, coupled with a sensitivity analysis. The optimization framework was implemented in Matlab using the pre-defined genetic algorithm in the optimization extension. With the models properly calibrated and validated, the performance indicators were obtained and conclusions about their approximation to reality were drawn. The recommended calibration methodology easily allows the replication of the observed conditions, revealing however poor adaptation to other intersections and a general lack of representativeness. The results obtained by the genetic algorithm are very sensitive to small changes in the initial set of parameters. The calibration methodology allows the replication of the observed conditions, revealing however poor adaptation to other intersections and a general lack of representativeness.
机译:微观仿真模型正在越来越多地用于交通工程应用,但有关其输出再现现场数据的程度仍然需要解决各种问题。在该透视图中,必须执行模型参数的适当校准,以便在模拟和实际流量测量之间获得近距离匹配。本文旨在突出校准过程的重要性,作为微观模拟模型参数的调整阶段,适用于城市,级别交叉口的分析。在选择案例研究(一个环形交叉路口和交通信号控制的一个交叉点)之后,进行了现场观察,允许创建支持模型的开发和校准的数据库。下一阶段专注于将AIMSUN微观模拟模型应用于所选交叉点。这涉及开发基于优化的校准方法,与灵敏度分析相结合。优化框架在Matlab中在优化扩展中使用预定义的遗传算法在Matlab中实现。通过正确校准和验证的模型,获得了性能指标并绘制了对现实的近似的结论。推荐的校准方法容易允许复制观察条件,揭示对其他交叉路口的适应性差和一般缺乏代表性。通过遗传算法获得的结果对初始参数集的小变化非常敏感。校准方法允许复制观察到的条件,揭示对其他交叉路口的适应性差和普遍缺乏代表性。

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