A Framework to Model Mixed Conventional and Automated Vehicular Traffic: Ameliorating Operations, Safety and Environmental Impacts

该研究计划提出了将联网和自动驾驶车辆（即自动驾驶车辆）集成到传统交通流中的建模工具。所提出的模型控制了传统车辆和自动车辆在不间断流设施上的相互作用。目标是让交通分析人员使用这些模型来评估下一代交通系统的可持续性。研究计划分为三个阶段。第一阶段将把以前开发的混合交通流模型扩展为一个统一的方法，以捕获混合交通中的车辆交互。这种方法将适用于评估具有不同比例的自动和传统车辆的高速公路上的交通状况（即延误、安全、排放）。将开发特定的控制算法来模拟考虑不同驾驶机动的混合交通（例如，自由流和通行机动车道选择，进出高速公路坡道等）。所制订的方法必须纳入交通作业的评价方法。因此，现有的公路容量方法必须进行调整，以考虑自动驾驶车辆对混合交通流的影响。预计下一代运输系统将有助于运输发展的可持续性，因此需要确定准确的建模工具，以协助决策者促进适当的运输管理政策。研究计划的第二阶段将开发一种方法来评估自动驾驶汽车的三重好处（即，减少交通拥堵造成的延误的潜力，提高车辆冲突增加的地点的安全性，并通过减少车辆的温室气体排放来改善对环境的影响）。这将通过校准自动驾驶车辆控制算法的参数来完成，同时考虑混合交通流中自动驾驶车辆与传统车辆之间的各种比例。透过现有的智能交通控制器收集的数据，将补充其他项目的交通数据。在第三阶段，研究团队将通过评估混合交通流对预留车道设施（如公交车道、HOV车道等）的具体情况的影响来验证所开发的模型。在分析交通运营、安全和环境时，将考虑不同比例的自动驾驶车辆。因此，在逐步发展下一代交通基础设施与等待更长的时间直到大量自动驾驶汽车进入市场之间，我们将确定一种权衡。该项目考虑了当前的EDI指导方针，以招聘和培训新出现的自动驾驶汽车ITS领域的学生，因此解决了目前公共和私营部门专业知识短缺的问题。

This research program proposes modeling tools that integrate connected and autonomous vehicles (i.e., automated vehicles) into conventional traffic streams. The proposed models control the interactions between conventional and automated vehicles on uninterrupted flow facilities. The goal is for such models to be used by transportation analysts to assess the sustainability of the next generation transportation systems. The research program is divided into three stages. The first stage will extend previously developed mixed traffic flow models into a unified methodology to capture vehicle interactions in mixed traffic. This methodology will be suitable to assess traffic conditions (i.e., delay, safety, emissions) on highways with various proportions of automated and conventional vehicles. Specific control algorithms will be developed to model mixed traffic considering different driving maneuvers (e.g., free-flow and passing maneuvers lane selection, access and egress to/from highway ramps, etc.). The developed methodology has to be integrated into the evaluation methods of traffic operations. Thus, the existing highway capacity methodology has to be adjusted to account for the effects of automated vehicles into mixed traffic flows. Next generation transportation systems are expected to contribute to the sustainability of transportation development, hence the need to define accurate modeling tools that can assist decision makers in promoting appropriate transportation management policies. The second stage of the research program will develop a methodology to evaluate the three-fold benefits of automated vehicles (i.e., potential to reduce delay due to traffic congestion, to improve safety at locations with increased vehicular conflicts, and to ameliorate the environmental impact by reducing vehicle's GHG emissions). This will be done by calibrating the parameters of the control algorithms of automated vehicles, while considering various ratios between automated and conventional vehicles in mixed traffic flows. Traffic data available from other projects will be complemented by data collection through the available smart traffic controllers. In the third stage, the research team will validate the developed models by assessing the effects of mixed traffic flows on the specific case of reserved-lanes facilities (e.g., bus lanes, HOV lanes, etc.). Different ratios of automated vehicles will be considered for the analysis of traffic operations, safety and environment. Hence, a trade-off will be identified between gradual development of the next generation transportation infrastructures versus waiting a longer period until a critical mass of automated vehicles are penetrating the market. This program considers the current EDI guidelines for recruiting and training students in the newly emerging ITS area of automated vehicles, therefore addressing the current shortage of expertise in both the public and private sectors.