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Appl. Sci. 2016, 6(3), 87; doi:10.3390/app6030087

Dynamically Determining the Toll Plaza Capacity by Monitoring Approaching Traffic Conditions in Real-Time

Department of Civil and Environmental Engineering, Seoul National University, Seoul 151-744, Korea
School of Civil, Architectural and Environmental Engineering, Korea University, Seoul 136-713, Korea
California Department of Transportation, Operations, Oakland, CA 94612, USA
Authors to whom correspondence should be addressed.
Academic Editor: Wen-Hsiang Hsieh
Received: 4 January 2016 / Revised: 4 March 2016 / Accepted: 9 March 2016 / Published: 18 March 2016
View Full-Text   |   Download PDF [1845 KB, uploaded 18 March 2016]   |  


This study presents an analytical method for dynamically adjusting toll plaza capacity to cope with a sudden shift in demand. The proposed method uses a proxy measure developed using discharge rate observed at toll plazas and segment travel times measured by probe vehicles. The effectiveness of the method has been evaluated by analyzing the empirical data obtained from toll plazas in the San Francisco Bay Area before and after toll plaza capacity changed. Findings indicate that the estimated number of vehicles stored near the upstream of toll plaza based on discharge rate and their travel times can be used as a proxy measure for predicting the effect of changes in toll plaza capacity. The proposed model can aid government agencies to dynamically adjust the toll plaza capacity in response to a sudden shift in demand due to various situations of failure. View Full-Text
Keywords: analytical model; toll plaza capacity; traffic conditions; proxy measure analytical model; toll plaza capacity; traffic conditions; proxy measure

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Kim, C.; Kim, D.-K.; Kho, S.-Y.; Kang, S.; Chung, K. Dynamically Determining the Toll Plaza Capacity by Monitoring Approaching Traffic Conditions in Real-Time. Appl. Sci. 2016, 6, 87.

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