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Microscopic modeling of the relaxation phenomenon using a macroscopic lane-changing model

机译:使用宏观车道变换模型对松弛现象进行微观建模

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摘要

A crucial challenge faced by current microscopic traffic flow models is capturing the relaxation phenomena commonly observed near congested on-ramps: vehicles are willing to accept very short spacings as they enter the freeway, but "relax" to more comfortable values shortly thereafter. This paper introduces a framework to solve this problem using a macroscopic theory of vehicle lane-changing inside microscopic models. In this theory, lane changes take place according to a stochastic process that has been validated in the field, and whose mean value is a function of lane-specific macroscopic quantities. As a consequence, the lane-changing logic becomes very simple compared to existing microscopic lane-changing models, and requires only one extra parameter. The resulting microscopic model is validated with empirical data.
机译:当前微观交通流模型面临的一个关键挑战是捕捉通常在拥挤的坡道附近观察到的松弛现象:车辆进入高速公路时愿意接受非常短的间距,但此后不久便“放松”到更舒适的位置。本文介绍了使用微观模型内部车辆换道的宏观理论来解决此问题的框架。在该理论中,车道变化是根据已在现场进行验证的随机过程发生的,其平均值是特定于车道的宏观量的函数。结果,与现有的微观车道改变模型相比,车道改变逻辑变得非常简单,并且仅需要一个额外的参数。所得的微观模型已通过经验数据验证。

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