考虑微观车辆相互作用的无管理交叉口解析建模
Analytically Modeling Unmanaged Intersections with Microscopic Vehicle Interactions
摘要：
随着自动驾驶汽车的出现，了解其对交通系统的影响非常重要。然而，传统的交通模拟是耗时的。在本文中，我们介绍了一个分析交通模型，无人管理的交叉口占微观车辆的相互作用。宏观性质，即，交叉口延误被建模为一个事件驱动的随机动态过程，其动力学编码的微观车辆行为。宏观性质的分布可以通过直接分析或事件驱动模拟来获得。它们比传统的（时间驱动的）交通模拟更有效，与传统的宏观流模型相比，它们可以捕捉更多的微观细节。我们说明了这种方法的效率在两个不同的政策下，在双车道交叉口的延误分析。所提出的模型允许1）不同策略之间的高效和有效比较，2）策略优化，3）流量预测，以及4）系统优化（例如，基础设施和协议）。
英文摘要：
With the emergence of autonomous vehicles, it is important to understand their impact on the transportation system. However, conventional traffic simulations are time-consuming. In this paper, we introduce an analytical traffic model for unmanaged intersections accounting for microscopic vehicle interactions. The macroscopic property, i.e., delay at the intersection, is modeled as an event-driven stochastic dynamic process, whose dynamics encode the microscopic vehicle behaviors. The distribution of macroscopic properties can be obtained through either direct analysis or event-driven simulation. They are more efficient than conventional (time-driven) traffic simulation, and capture more microscopic details compared to conventional macroscopic flow models. We illustrate the efficiency of this method by delay analyses under two different policies at a two-lane intersection. The proposed model allows for 1) efficient and effective comparison among different policies, 2) policy optimization, 3) traffic prediction, and 4) system optimization (e.g., infrastructure and protocol).
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
