User-Centric Sensing and Distributed Control of Corridor Transportation Networks

本研究研究了在车联网（CV）环境下由高速公路和主干道组成的交通走廊的行为和性能，其中配备无线通信和传感设备的车辆与路边传感器一起收集、处理和共享交通信息。首先，将探索融合/结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数量，并填充包含从起点到目的地的行程数量的表格。其次，研究拥堵，特别是交通堵塞是如何产生和传播的，以及这些信息如何帮助司机应对拥堵。最后，本研究利用前两项任务的结果，探索能够自适应协调控制高速公路匝道米和附近主干道交通灯的算法，并根据交通事故重新安排交通。如果成功，本研究的结果将有助于更好地理解走廊网络中的交通拥堵，并为监测和控制车辆交通提供新的方法。这可以使应用具有显著的社会效益，如减少交通拥堵和燃料消耗。这项研究的结果也将通过简报和小册子以及其他方式散发给公共机构（例如运输部）和一般公众。本研究是在车辆交通流和计算机网络的交叉点，期望它有助于理解基于走廊的交通网络是如何工作的，并为相关的学生提供跨学科的培训。少数族裔研究生和本科生将通过加州大学戴维斯分校的CAMP（加州少数族裔参与联盟）等大学级别的少数族裔项目被招募参与该项目。

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.