User-Centric Sensing and Distributed Control of Corridor Transportation Networks

以用户为中心的走廊交通网络感知和分布式控制

• 批准号: 1301496
• 负责人: Michael Zhang
• 金额: $ 35万
• 依托单位: University of California-Davis
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-07-01 至 2018-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1301496&HistoricalAwards=false
• 关键词: User; Centric; Sensing; Distributed; Control

This research studies the behavior and performance of a transportation corridor made of a freeway and arterial streets under a Connected Vehicles (CV) environment, where vehicles equipped with wireless communication and sensing devices collect, process, and share traffic information among themselves along with roadside sensors. First, methods of fusing/combining real-time traffic data from both vehicles and roadside sensors will be explored to automate the detection of incidents (e.g., accidents), to estimate the number of cars waiting in line and to populate the tables that contain the number of trips from origins to destinations. Second, the research studies how congestion, particularly traffic jams, emerge and spread, and how this information can help drivers cope with congestion. Finally, the research makes use of the results obtained from the first two tasks to explore algorithms that will enable the adaptive, coordinated control of freeway ramp meters and nearby arterial traffic lights, and the re-routing of traffic in response to traffic incidents.If successful, the results of this research will lead to a better understanding of traffic congestion in corridor networks and new ways to monitor and control vehicular traffic. These can enable applications with significant societal benefits such as reduced traffic congestion and fuel consumption. The results of this research will also be disseminated to public agencies (such as Departments of Transportation (DOTs)) and the general public through presentations and brochures, and other means. This research is at the intersection of vehicular traffic flow and computer networks, it is expected to contribute to the understanding of how corridor based transportation networks work, and provides interdisciplinary training to the students involved. Minority graduate and undergraduate students will be recruited to participate in this project through college-level minority programs such as CAMP (California Alliance for Minority Participation) at the University of California Davis.

本研究主要研究由高速公路和主干道组成的交通走廊在车联网环境下的行为和性能。车联网环境下，配备无线通信和传感设备的车辆与路边传感器一起沿着收集、处理和共享交通信息。首先，将探索融合/组合来自车辆和路边传感器的实时交通数据的方法，以自动检测事件（例如，事故），估计排队等候的汽车的数量，并填充包含从起点到目的地的行程数量的表。其次，研究拥堵，特别是交通拥堵，如何出现和蔓延，以及这些信息如何帮助司机科普拥堵。最后，本研究利用前两个任务的结果，探索算法，使高速公路匝道计和附近的主干道交通灯的自适应协调控制，以及交通改道，以响应交通事件。如果成功，这项研究的结果将有助于更好地了解走廊网络中的交通拥堵情况，并为监控车辆提供新的方法。交通这些可以使应用具有显著的社会效益，例如减少交通拥堵和燃料消耗。这项研究的结果还将通过介绍和小册子以及其他方式向公共机构（如交通部）和公众传播。这项研究处于车辆交通流和计算机网络的交叉点，预计将有助于了解基于走廊的交通网络如何工作，并为相关学生提供跨学科培训。少数民族研究生和本科生将被招募参加这个项目，通过大学一级的少数民族计划，如CAMP（加州少数民族参与联盟）在加州戴维斯大学。