Browsing by Author "Zheng, Jianfeng"

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    Automatic Generation of Traffic Signal Timing Plan
    (Minnesota Department of Transportation, 2014-09) Liu, Henry; Zheng, Jianfeng
    Due to budget constraints, most of the traffic signals in the US are retimed once every 2-5 years. Despite that, traffic delay increases 3-5% per year with outdated timing plans. It would be desirable to reduce the signal retiming costs by automating all or a portion of the manual process. This research takes one step forward in this direction. In this project, we develop a performance visualization and fine-tuning tool for arterial traffic signal systems, aimed at reducing the labor costs for signal retiming. Using high-resolution event-based data from the SMART-Signal system, a set of easy-to-use algorithms are developed to refine traffic signal systems. Specifically, a framework is developed to diagnose operational problems regarding cycle lengths, green splits and offsets. Then, algorithms for offsets and green splits fine-tuning are proposed. To fine-tune offsets, a practical procedure to construct time space diagram (TS-Diagram) to visualize the progression quality on arterials is proposed and validated. For green splits, an adjusted measure of effectiveness (MOE), the utilized green time (UGT), is proposed for performance evaluation. Moreover, a practical procedure for time of day (TOD) transitions is also developed to generate optimal timing plan schedules. Field case studies and simulation experiments are carried out to illustrate and validate the proposed algorithms. The algorithms could be used during the retiming process to help agencies reduce labor costs, or to periodically refine traffic signal systems for coordinated arterials.
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    A Performance visualization and fine-tuning tool for arterial traffic signal systems
    (2014-04) Zheng, Jianfeng
    Maintaining an efficient traffic signal operation is a challenging task for many traffic management agencies. Due to the intensive labor cost required, most of the traffic signals in the US are retimed once every 2-5 years. However, it has been shown in the past that traffic delay increases 3-5% per year simply because the timing plans are not kept up to date. For many resource-constrained agencies, it would be desirable to reduce the signal re-timing costs by automating all or portion of the manual process. The research makes one-step forward towards this direction. In this research, we developed a performance monitoring and visualization tool for arterial traffic signal systems, aiming at reducing the labor cost for signal retiming, and helping to identify signal parameter adjustment opportunities. Specifically, an automated data collection unit (DCU) was developed to collect high-resolution event-based data from signal controller cabinets. Using the high-resolution data, two parameter fine-tuning algorithms were proposed, one for offset and another for green splits. To fine-tune signal offsets, a practical procedure to construct the time space diagram (TS-Diagram) to visualize the progression quality on arterials was proposed. The TS-Diagram was calibrated and validated using the field data collected from the DCUs and the probe vehicle runs. Reasonable agreements between the field observations and the generated TS-Diagrams were found. A field experiment was then carried out, to illustrate how decisions of changes could be made by intuitively evaluating the TS-Diagram. For green splits, an adjusted measure of effectiveness (MOE), the utilized green time (UGT), was proposed for performance evaluation. The information was further tabulated in the form of ring-and-barrier diagram to facilitate evaluation. Field examples were also illustrated to demonstrate implementation potentials for green split evaluation and fine-tuning.
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    Research Implementation of the SMART SIGNAL System on Trunk Highway (TH) 13
    (Minnesota Department of Transportation, 2013-02) Liu, Henry X.; Zheng, Jianfeng; Hu, Heng; Sun, Jie
    In our previous research, the SMART-SIGNAL (Systematic Monitoring of Arterial Road Traffic and Signals) system that can collect event-based traffic data and generate comprehensive performance measures has been successfully developed by the University of Minnesota. In this research, a new set of interfaces are developed for SMART-SIGNAL system including new prototypes of data collection unit (DCU) and refined web-based user interface. To collect high resolution event-based traffic data including both vehicle detector actuation event and signal phase change event, two types of DCUs are designed, the TS-1 DCU and TS-2 DCU for corresponding traffic signal cabinet. TS-1 DCU connects with TS-1 cabinet using pin to pin interface, and the TS-2 DCU interfaces directly with SDLC bus within TS-2 cabinet. The DCUs uses high performance microcontroller modules, and are compact and easy to install. Both DCUs are designed to be vender independent add-on module for traffic cabinet, and can be used as flexible solution to enhance data collection by agencies. The refined web-based user interface features various performance measures to public users, such as Level of Service (LOS), queue length, travel time and intersection delays. The new set of interfaces have been deployed with the SMART-SIGNAL system at 13 intersections along Trunk Highway (TH) 13 in Burnsville, MN.