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
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
中文摘要
高速公路交通拥堵影响了美国大多数人和货物的流动。这种拥塞是由于网络上需求达到峰值或容量下降的少数点造成的。虽然这些瓶颈通常只占用一小段道路,但排队的队伍却可以绵延数英里。大多数高速公路队列的特点是从瓶颈向上游传播的慢波和停止波。不断变化的车速增加了事故发生的可能性,频繁的加速增加了车辆的排放。虽然这些波一旦形成就可以预测其传播,但尚不清楚它们是如何产生的,关于它们是否影响容量的争论仍在继续。迄今为止,这些问题已经用点探测器进行了研究,点探测器能够监测固定地点的交通。拟议的工作将为两辆探测车辆配备GPS接收器和距离传感器,以监视相邻车辆。探测车辆将在整个瓶颈区域收集数据,并观察可能无法一路传播到点探测器的重要信号。这些探针将用于确定影响瓶颈容量的因素,并确定高速公路队列中的信号和波是如何形成的。这些努力应该会带来额外的好处,包括改善汽车跟随和交通流量模型。这项工作是跨学科的,利用电子工程的传感器技术和土木工程的交通流理论。这个建议形成了一个新课程的基石,在两个学术部门之间交叉列出,并在一个团队合作的环境中教授,这在课程中很少发现。在这种整合的环境中,学生将在每个季度结束时突破知识的界限。
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
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批准号:2023857
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项目类别:Standard Grant
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资助金额:$38.32万
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财政年份:2020
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负责人:Benjamin Coifman
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依托单位:
Changing Lanes - Using Advance Sensor Technology to Understand Driver Behavior
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批准号:1537423
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项目类别:Standard Grant
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资助金额:$37.37万
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财政年份:2015
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负责人:Benjamin Coifman
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依托单位:
NSF/USDOT Partnership for Exploratory Research - ICSST: Decentralized Surveillance, Control and Data Transmission for Transportation Applications
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批准号:0127944
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项目类别:Standard Grant
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资助金额:$0.0万
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财政年份:2001
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负责人:Benjamin Coifman
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依托单位:
海外基金