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Estimation of incident-induced congestion on signalized arteries using traffic sensor data

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5 Author(s)
Hou, Lin ; Tsinghua National Laboratory for Information Science and Technology, Department of Automation, Tsinghua University, Beijing 100084, China ; Zhang, Zuo ; Lu, Binghao ; Xu, Runmin
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This paper describes how to derive quantitative information about the effect of traffic incidents on urban traffic flow from the raw measurements detected by sectional loop sensors. The two critical parameters of the travel delay and queue length, which reflect the temporal and spatial properties of incident-induced congestion, cannot be directly determined from commonly used loop sensors. The modified queuing diagram is used here to quantify incident-induced queues and travel delays on signalized arteries using sensor data from the targeted and upstream links. The method is tested using data generated by the VISSIM simulation model, with results indicating its efficiency and accuracy with an average relative travel delay error of 18.67% for all samples which falls to 8.07% for high volume and very high volume conditions.

Published in:

Tsinghua Science and Technology  (Volume:17 ,  Issue: 3 )

Date of Publication:

June 2012

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