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Title:Improving the Effectiveness of Smart Work Zone Technologies
Author(s):Li, Yanning; Martinez Mori, Juan Carlos; Work, Daniel B.
Subject(s):smart work zone systems
traffic estimation
microsimulation
Geographic Coverage:Illinois
Abstract:This project evaluates the effectiveness of sensor network systems for work zone traffic estimation. The comparative analysis is performed on a work zone modeled in microsimulation and calibrated with field data from two Illinois work zones. Realistic error models are used to generate noisy measurements corresponding to Doppler radar sensors, remote traffic microwave sensors (RTMS), and low-energy radar (LER). The velocity, queue length, and travel time are estimated with three algorithms based on (1) interpolation, (2) spatio-temporal smoothing, and a (3) flow model–based Kalman filter. More than 700 sensor and algorithm configurations are evaluated, and the accuracy of the resulting traffic estimates are compared with the true traffic state from the microsimulation. The nonlinear Kalman filter provides up to 30% error reduction over other velocity estimators when the RTMS spacing exceeds 2 miles and generally offers the best performance for queue and travel time estimation.
Issue Date:2016-11
Publisher:Illinois Center for Transportation/Illinois Department of Transportation
Citation Info:Li, Yanning, Juan Carlos Martinez Mori, and Daniel B. Work 2016. Evaluation of PCC Pavement and Structure Coring and In Situ Testing Improving the Effectiveness of Smart Work Zone Technologies. A report of the findings of ICT-27-155. Illinois Center for Transportation Series No. 16-023. Research Report No. FHWA-ICT-16-021. Illinois Center for Transportation, Rantoul, IL.
Series/Report:Illinois Center for Transportation Series No. 16‐023
Genre:Technical Report
Type:Text
Language:English
URI:http://hdl.handle.net/2142/94999
ISSN:0197-9191
Sponsor:Illinois Department of Transportation, R27-155
Rights Information:No restrictions. This document is available through the National Technical Information Service, Springfield, VA 22161.
Date Available in IDEALS:2017-01-13


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