Traffic signal coordination and queue management in oversaturated intersections.

Hajbabaie, Ali; Medina, Juan C.; Benekohal, Rahim F.; University of Illinois at Urbana-Champaign

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ROSA P serves as an archival repository of USDOT-published products including scientific findings, journal articles, guidelines, recommendations, or other information authored or co-authored by USDOT or funded partners. As a repository, ROSA P retains documents in their original published format to ensure public access to scientific information.

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Traffic signal coordination and queue management in oversaturated intersections.

2011-03-18
By Hajbabaie, Ali ; Medina, Juan C. ; Benekohal, Rahim F.

[PDF-1009.34 KB]

English

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Creators:

Hajbabaie, Ali ; Medina, Juan C. ; Benekohal, Rahim F.

Hajbabaie, Ali ; Medina, Juan C. ; Benekohal, Rahim F. Less -
Corporate Creators:

University of Illinois at Urbana-Champaign
Subject/TRT Terms:

[+]

Traffic Signal Control Systems Traffic Signal Intervals Traffic Signals
Publication/ Report Number:

047IY02
Resource Type:

Tech Report
Geographical Coverage:

Illinois
Corporate Publisher:

NEXTRANS Center (U.S.)
NTL Classification:

NTL-OPERATIONS AND TRAFFIC CONTROLS-Traffic Control Devices;NTL-OPERATIONS AND TRAFFIC CONTROLS-Traffic Flow;
Abstract:

Traffic signal timing optimization when done properly, could significantly improve network performance by reducing delay, increasing network throughput, reducing number of stops, or increasing average speed in the network. The optimization can become complex due to large solution space caused by many combinations of different parameters that affect traffic operation. In this study three different methods are used to find near-optimal signal timing parameters in transportation networks. The methods are: Genetic Algorithms (GA), Evolution Strategies (ES), and Approximate Dynamic Programming (ADP). Each method is introduced, the signal timings associated with them are explained and some important measures of performance of the networks are determined and compared. One small network with 9 intersections and one medium network with 20 intersections were used for evaluating the optimizations methods. Three general cases (Cases 1, 2, 3) are discussed in this report. For the small symmetric network, three levels of traffic loading are used (no overload, 10% overload and 20% overload). For the medium network (modified Springfield IL downtown network), two levels of entry volumes are used (750 and 1000 vehicle per hour per lane).
Format:

PDF
Collection(s):

University Transportation Centers US Transportation Collection
Main Document Checksum:

[+]

urn:sha256:20335bc6d448a70ee40fddd6073c6c1a83a787ff8a34d451657ba5f2d13a9017
Download URL:

https://rosap.ntl.bts.gov/view/dot/20374/dot_20374_DS1.pdf
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Traffic signal coordination and queue management in oversaturated intersections.

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