Weaving sections are components of highway networks that introduce a heightened likelihood for bottlenecks and collisions. Automated vehicle technology could address this as it holds considerable promise for transportation mobility and safety improvements. However, the implications of combining automated vehicles (AuVs) with traditional human-driven vehicles (HuVs) in weaving freeway sections have not been quantitatively measured. To address this gap, this paper objectively experimented with bidirectional (i.e., longitudinal and lateral) motion dynamics in a microscopic modeling framework to measure the mobility and safety implications for mixed traffic movement in a freeway weaving section. Our research begins by establishing a multilane microscopic model for studied vehicle types (i.e., AuV and HuV) from model predictive control with the provision to form a CACC platoon of AuV vehicles. The proposed modeling framework was tested first with HuV only on a two-lane weaving section and validated using standardized macroscopic parameters from the Highway Capacity Manual. This model was then applied to incrementally expand the AuV share for varying inflow rates of traffic. Simulation results showed that the maximum flow rate through the weaving section was attained at a 65% AuV share. At the same time, steadiness in the average speed of traffic was experienced with increasing AuV share. The results also revealed that a 95% AuV share could reduce potential conflicts by 94.28%. Finally, the results of simulated scenarios were consolidated and scaled to report expected mobility and safety outcomes from the prevailing traffic state and the optimal AuV share for the current inflow rate in weaving sections.

中文翻译：

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多车道显微建模以测量高速公路编织路段混合交通的流动性和安全后果

编织路段是高速公路网络的组成部分，会增加瓶颈和碰撞的可能性。自动驾驶汽车技术可以解决这个问题，因为它在交通出行和安全改进方面具有相当大的潜力。然而，尚未定量测量将自动车辆 (AuV) 与传统人类驾驶车辆 (HuV) 结合在高速公路路段中的影响。为了解决这一差距，本文在微观建模框架中客观地试验了双向（即纵向和横向）运动动力学，以测量高速公路编织路段混合交通运动的机动性和安全性影响。我们的研究首先为研究的车辆类型（即，AuV 和 HuV）来自模型预测控制，并提供形成 AuV 车辆的 CACC 排。提议的建模框架首先仅在双车道编织路段上使用 HuV 进行了测试，并使用《公路通行能力手册》中的标准化宏观参数进行了验证。然后应用该模型来逐步扩大 AuV 份额以适应不同的流量流入速度。模拟结果表明，通过编织部分的最大流速在 65% 的 AuV 份额下获得。同时，随着 AuV 份额的增加，交通平均速度趋于稳定。结果还显示，95% 的 AuV 份额可以减少 94.28% 的潜在冲突。最后，