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CAREER: Traffic congestion on freeways: using probe vehicle data to understand bottlenecks and mitigate the resulting problems

CAREER: Traffic congestion on freeways: using probe vehicle data to understand bottlenecks and mitigate the resulting problems
职业:高速公路交通拥堵:使用探测车辆数据了解瓶颈并缓解由此产生的问题
批准号:
0133278
负责人:
Benjamin Coifman
金额:
$0.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2002
资助国家:
美国
项目状态:
已结题
起止时间:
2002-10-01 至 2008-09-30

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中文摘要
翻译
高速公路交通拥堵影响了美国大部分人和货物的流动。这种拥塞是由于网络上需求达到峰值或容量下降的少量点造成的。尽管这些瓶颈通常占用很短的道路距离,但由此产生的排队可能会延伸几英里。大多数高速公路排队的特点是从瓶颈向上游传播的慢波和停波。车速的变化增加了发生事故的可能性,频繁的加速增加了车辆的排放。虽然这些波的传播一旦形成就可以预测,但它们是如何产生的尚不清楚,关于它们是否会影响通行能力的争论仍在继续。到目前为止,这些问题已经通过点探测器进行了研究,这种探测器能够监测固定位置的交通。拟议的工作将为两辆探测车配备GPS接收器和距离传感器,以监测相邻的车辆。探测车将在整个瓶颈区域收集数据,并观察可能不会一直传播到点探测器的重要信号。这些探头将被用来确定哪些因素影响瓶颈通行能力,并确定信号和波形在高速公路排队中是如何形成的。这些努力应该会带来额外的好处,包括改善车辆跟车和交通流量模型。这项工作是跨学科的,借鉴了传感器技术的电气工程,以及交通流理论的土木工程。这项建议构成了一门新课程的基石,在两个学术部门之间交叉列出,并在课程中罕见的团队合作环境中授课。在这种综合的环境中,学生们将在每个季度结束前突破知识的界限。
英文摘要
Freeway traffic congestion impacts the movement of most people and goods in the United States. This congestion is due to a small number of points on the network where demand peaks or capacity drops. Although these bottlenecks typically occupy a short distance of roadway, the resulting queues can extend for several miles. Most freeway queues are characterized by slow and stop waves propagating upstream from a bottleneck. The changing speeds give rise to an increased probability of accidents and the frequent accelerations increase vehicle emissions. Although the propagation of these waves can be predicted once they form, it is not known how they originate and debate continues as to whether they impact capacity. To date, these issues have been studied with point detectors, which are capable of monitoring traffic at fixed locations.The proposed work will equip two probe vehicles with GPS receivers and distance sensors to monitor adjacent vehicles. The probe vehicles will collect data throughout bottleneck regions and observe important signals that may not propagate all the way to point detectors. These probes will be used to identify which factors influence bottleneck capacity, and identify how the signals and waves form in freeway queues. These efforts should lead to additional benefits including improved car following and traffic flow models. The work is interdisciplinary, drawing on electrical engineering for sensor technologies, and civil engineering for traffic flow theory. This proposal forms the cornerstone for a new course, cross-listed between the two academic departments and taught with a teamwork environment that is found rarely in coursework. In this integrated environment, the students will push the boundaries of knowledge by the end of each quarter.
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会议论文
The New Traffic Microscope- Measuring Microscopic Traffic Dynamics to Model and Control Freeway Traffic Congestion
  • 批准号:
    2023857
  • 项目类别:
    Standard Grant
  • 资助金额:
    $38.32万
  • 财政年份:
    2020
  • 负责人:
    Benjamin Coifman
  • 依托单位:
Changing Lanes - Using Advance Sensor Technology to Understand Driver Behavior
  • 批准号:
    1537423
  • 项目类别:
    Standard Grant
  • 资助金额:
    $37.37万
  • 财政年份:
    2015
  • 负责人:
    Benjamin Coifman
  • 依托单位:
NSF/USDOT Partnership for Exploratory Research - ICSST: Decentralized Surveillance, Control and Data Transmission for Transportation Applications
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