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

混合传统和自动车辆交通建模框架：改善运营、安全和环境影响

• 批准号: RGPIN-2020-06760
• 负责人: Alecsandru, Ciprian
• 金额: $ 1.89万
• 依托单位: Concordia University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=718460
• 关键词: Framework; Model; Mixed; Conventional; Automated

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.

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。