Sequence Optimization at Signalized Diamond Interchanges Using High-Resolution Event-Based Data

Hainen, Alexander M.; Li, Howell; Stevens, A.L.; Day, Christopher M.; Sturdevant, James R; Bullock, Darcy M.

doi:10.3141/2487-02

Cited by 4 publications

(7 citation statements)

References 11 publications

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“…This both visually confirmed the operation and validated the identification of ramp and upstream vehicles in the PCDs [93,94].…”

Section: Diverging Diamond Interchange Examplessupporting

confidence: 65%

“…There are relatively few vehicles arriving at other times in the cycle. Figure 6.14 shows results from an evaluation of two alternative DDI signal phasing plans from an interchange in Utah [93]. Figure 6.14a shows the prior plan, which used two-phase operation at each signal, yet led to a situation where there was more traffic entering the interchange than could exit at the other end.…”

Section: Diverging Diamond Interchange Examplesmentioning

confidence: 99%

“…N Figure 6.18b shows an experimental scheme where the signal is preempted at regular intervals to account for Figure 6.14 ''Three-phase'' operation of a DDI [93]. Data shown are from SR 201 and Bangerter Highway in Salt Lake platoon arrivals from the upstream intersection.…”

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confidence: 99%

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Integrating Traffic Signal Performance Measures into Agency Business Processes

Day¹,

Bullock²,

Li³

et al. 2015

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Federal Highway Administration Office of Operations and Resource Center. Some material in this monograph was compiled from previous studies that were made possible under National Cooperative Highway Research Program project 3-79a, INDOT State Planning and Research (SPR) projects, Indiana LTAP projects, and USDOT through Small Business Innovation Research (SBIR) projects with Traffax, Inc., and through a joint research project with Marshall University. We would like to thank Rick Schuman and colleagues at Inrix, Inc., for provision of sample vehicle trajectory data in Chapter 7. We are grateful to these sponsors and research partners for their support over the years.The contents of this paper reflect the views of the authors, who are responsible for the facts and the accuracy of the data presented herein, and do not necessarily reflect the official views or policies of the sponsoring organizations. These contents do not constitute a standard, specification, or regulation. CopyrightCopyright 2015 by Purdue University. All rights reserved.Print ISBN: 978-1-62260-376-3 ePUB ISBN: 978-1-62260-377-0 ABSTRACT INTEGRATING TRAFFIC SIGNAL PERFORMANCE MEASURES INTO AGENCY BUSINESS PROCESSESThis report discusses uses of and requirements for performance measures in traffic signal systems facilitated by high-resolution controller event data. Uses of external travel time measurements are also discussed. The discussion is led by a high-level synthesis of the systems engineering concepts for traffic signal control, considering technical and nontechnical aspects of the problem. This is followed by a presentation of the requirements for implementing data collection and processing of the data into signal performance measures. The remaining portion of the report uses an example-oriented approach to show a variety of uses of performance measures for communication and detector system health, quality of local control (including capacity allocation, safety, pedestrian performance, preemption, and advanced control analysis), and quality of progression (including evaluation and optimization).

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“…This both visually confirmed the operation and validated the identification of ramp and upstream vehicles in the PCDs [93,94].…”

Section: Diverging Diamond Interchange Examplessupporting

confidence: 65%

Section: Diverging Diamond Interchange Examplesmentioning

confidence: 99%

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Integrating Traffic Signal Performance Measures into Agency Business Processes

Day¹,

Bullock²,

Li³

et al. 2015

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“…Conventional diamond interchanges (CDI) transfer traffic between freeways and two-way surface streets [1]. Full CDIs consist of a pair of ramp intersections with relatively close interlocked left turns, four entry points, and four exit points [2] [3] [4] [5]. CDIs are crucial for the correct operation of urban transportation networks; hence, their safe and efficient operation are critical agency objectives [3] [4].…”

Section: Introductionmentioning

confidence: 99%

Diamond Interchange Performance Measures Using Connected Vehicle Data

Saldivar-Carranza¹,

Rogers²,

Li³

et al. 2022

JTTs

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Diamond interchanges are frequently used where a freeway intersects a two-way surface street. Most of the techniques to evaluate the performance of diamond interchanges rely on the Highway Capacity Manual (HCM), simulation, Automated Traffic Signal Performance Measures (ATSPMs), and historical crash data. HCM and simulation techniques require on-site data collection to obtain models' inputs. ATSPMs need high-resolution controller event data acquired from roadway sensing equipment. Safety studies typically need 3 to 5 years of crash data to provide statistically significant results. This study utilizes commercially available connected vehicle (CV) data to assess the performance and operation of a three-and four-phase diamond interchange located in Indianapolis, Indiana, and Dallas, Texas, respectively. Over 92,000 trajectories and 1,400,000 GPS points are analyzed from August 2020 weekdays CV data. Trajectories are linear-referenced to generate Purdue Probe Diagrams (PPDs) from which arrivals on green (AOG), split failures, downstream blockage, and movement-based control delay are estimated. In addition, an extension of the PPD is presented that characterizes the complete journey of a vehicle travelling through both signals of the diamond interchange. This enhanced PPD is a significant contribution as it provides an analytical framework and graphical summary of the operational characteristics of how the external movements traverse the entire system. The four-phase control showed high internal progression (99% AOG) compared to the moderate internal progression of the three-phase operation (64% AOG). This is consistent with the design objectives of three-and four-phase control models, but historically these quantitative AOG measures were not possible to obtain with just detector data. Additionally, a graphical summary that illustrates the spatial distribution of hard-braking and hard-acceleration events is also provided. The presented techniques can be used by any agency to evaluate the performance of their diamond interchanges without on-site data collection or capital investments in sensing infrastructure.

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“…High-resolution traffic signal event data generated by the controller are already being used to monitor the performance of traffic signals through a variety of calculated metrics (11)(12)(13). These data have been generated using the Traffic Signal Performance Monitoring System, the Systematic Monitoring of Arterial Road Traffic and Signal system, and the data logger of the Econolite ASC/3 controller (14), among other controllers.…”

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confidence: 99%

Characterizing Emergency Vehicle Preemption Operation with High-Resolution Traffic Signal Event Data

Chou

Nichols

2016

Transportation Research Record: Journal of the Transportation R

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This paper proposes the use of a signal phase spectrum plot to analyze high-resolution traffic signal event data. Specifically, the controller performance related to emergency vehicle preemption operation is characterized in an effort to identify performance measures that will allow a traffic engineer to understand better the impact that various configurations have on intersection operations. Performance measures for individual intersections in coordinated systems include preemption duration, transition duration, and total interruption time. Performance measures for networks are based on an emergency vehicle reidentification process for deriving an emergency vehicle’s trajectory through a network, and the results can further be used to estimate travel time, travel speed, and origin–destination. These performance measures are illustrated by simulated signal system in Morgantown, West Virginia. Transition modes are varied in the simulation network to determine the relative performance measures. Case studies are presented for using high-resolution data to troubleshoot field preemption operation using signal systems in Morgantown and Huntington, West Virginia.

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Sequence Optimization at Signalized Diamond Interchanges Using High-Resolution Event-Based Data

Cited by 4 publications

References 11 publications

Integrating Traffic Signal Performance Measures into Agency Business Processes

Integrating Traffic Signal Performance Measures into Agency Business Processes

Diamond Interchange Performance Measures Using Connected Vehicle Data

Characterizing Emergency Vehicle Preemption Operation with High-Resolution Traffic Signal Event Data

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