A convex model for queue length estimation in a connected vehicle environment


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Date

2017-01

Publication Type

Conference Paper

ETH Bibliography

yes

Citations

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Abstract

This paper presents a convex model for real-time queue length estimation in a connected vehicle environment. The proposed model is based on kinematic wave theory with the assumption of a triangular fundamental diagram. It first identifies the critical points where the traffic state changes, and then estimates the piecewise linear back of queue (BoQ) curve using a convex model. The arrival flow can also be recovered from the estimated BoQ curve. The proposed model does not require a priori information on signal timing, penetration rates or traffic flows. The algorithm is tested with NGSIM data. Results show that the mean absolute error of the algorithm is within 1 cars even for low penetration rates. It is also shown that the algorithm is robust to the measurement errors.

Publication status

published

External links

Editor

Book title

TRB 96th Annual Meeting Compendium of Papers

Journal / series

Volume

Pages / Article No.

Publisher

Transportation Research Board

Event

96th Annual Meeting of the Transportation Research Board (TRB 2017)

Edition / version

Methods

Software

Geographic location

Date collected

Date created

Subject

Organisational unit

08686 - Gruppe Strassenverkehrstechnik check_circle
02226 - NSL - Netzwerk Stadt und Landschaft / NSL - Network City and Landscape
02655 - Netzwerk Stadt u. Landschaft ARCH u BAUG / Network City and Landscape ARCH and BAUG

Notes

Funding

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