Browsing by Subject "Traffic signal control systems"

Now showing 1 - 8 of 8
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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 Despite that, traffic delay increases 3-5% per year with outdated timing plans.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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    Development of Algorithms for Travel Time-Based Traffic Signal Timing, Phase I – A Hybrid Extended Kalman Filtering Approach for Traffic Density Estimation along Signalized Arterials
    (2010-12) Liu, Henry X.; Di, Xuan
    As technologies continue to mature, the concept of IntelliDrive has gained significant interest. Besides its application on traffic safety, IntelliDrive also has great potential to improve traffic operations. In this context, an interesting question arises: If the trajectories of a small percentage of vehicles (IntelliDrive vehicles) can be measured in real time, how can we use such data to improve traffic management? This research serves as a starting point that aims to produce a paradigm shift to optimize the traffic signal control from the use of the conventional fixed-point loop detector data to the use of mobile vehicle trajectory-based data. Since the change of density on arterials can help traffic engineers to track the queue length at intersections, which is important for traffic signal optimization, in this project we will focus on the estimation of traffic density on urban arterials when trajectories from a small percentage of vehicles are available. Most previous work, however, focuses on freeway density estimation based merely on detector data. In this research, we adopt the MARCOM (Markov Compartment) model developed by Davis and Kang (1994) to describe arterial traffic states. We then implement a hybrid extended Kalman filter to integrate the approximated MARCOM with fixed-point and vehicle-trajectory measurements. We test the proposed model on a single signal link simulated using VisSim. Test results show that the hybrid extended Kalman filter with vehicle-trajectory data can significantly improve density estimation.
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    Development of Mobile Accessible Pedestrian Signals (MAPS) for Blind Pedestrians at Signalized Intersections
    (Center for Transportation Studies, 2011-06) Liao, Chen-fu; Rakauskas, Michael; Rayankula, Avanish
    People with vision impairment have different perception and spatial cognition as compared to the sighted people. Blind pedestrians primarily rely on auditory, olfactory, or tactile feedback to determine spatial location and find their way. They generally have difficulty crossing intersections due to lack of traffic information at intersections. Among the intersection crossing sub-tasks, locating crosswalk, determining when to cross and maintaining alignment to crosswalk while crossing are the most difficult tasks for the blind and visually impaired. To understand how the blind pedestrians make safe crossing decisions, ten blind and low-vision individuals were interviewed. The purpose of these interviews was to understand the types of information they use while making safe intersection crossings and identify new information types that could assist them. A Mobile Accessible Pedestrian Signals (MAPS) prototype was developed to support decision making at signalized intersections. The MAPS integrates sensors on a Smartphone, Wi-Fi, and Bluetooth technologies, and traffic signal controllers were developed to provide intersection geometry information and Signal Phasing and Timing (SPaT) to pedestrians who are blind at signalized intersections. A single-tap command on the Smartphone screen allows users to request for intersection geometry information, such as street name, direction and number of lanes at a corner of an intersection. A double-tap input while pointing toward desired direction of crossing will confirm the crossing direction, request for pedestrian phase, and the Smartphone application will then wirelessly request for signal timing and phasing information from traffic signal controller.
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    Development of Novel Hydrogen-Based Power Systems for ITS Applications: Phase-I
    (Intelligent Transportation Systems Institute, Center for Transportation Studies, University of Minnesota, 2012-12) Mereddy, Venkatram R.
    There are many remote traffic signals on the road that don’t have access to a regular power supply, so they use batteries that need to be changed quite often. A hydrogen fuel cell is an electrochemical device that combines hydrogen and oxygen to produce electricity. It offers a clean and high-efficiency energy source to circumvent the problems associated with the conventional batteries. However, one major drawback that limits its utility is the use of compressed metal cylinders as a source of hydrogen. Chemical-based hydrogen production can provide a very compact and low-pressure storage option for the controlled release of hydrogen gas in large amounts. The hydrogen-based fuel cells can also be used as a backup power source at critical traffic signals to prevent accidents during power outages. The other possible applications include alternating-traffic signs, directional signals, speed-limit signs, blinkers in series, and warning blinkers etc. The project deals with the development of novel chemical-based hydrogen storage materials, efficient generation of hydrogen and recycling of spent materials. In this regard, we have explored several boron-based chemical hydrides as hydrogen storage materials. These hydrides offer an attractive solution to our quest in finding out materials that are safe, compact, and readily provide large quantities of hydrogen on demand. In this work, we have carried out generation of hydrogen from several boron hydrides such as sodium borohydride (SBH) and ammonia-borane (AB), etc., utilizing solvents such as water and alcohols under catalytic and non-catalytic conditions.
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    Development of the Next Generation Stratified Ramp Metering Algorithm Based on Freeway Density
    (Center for Transportation Studies, 2011-03) Geroliminis, Nikolas; Srivastava, Anupam; Michalopoulos, Panos
    A new coordinated, traffic-responsive ramp metering algorithm has been designed for Minnesota’s freeways based on density measurements, rather than flows. This is motivated in view of recent research indicating that the critical value of density at which capacity is observed is less sensitive and more stable than the value of capacity, thereby resulting in m ore effective control. Firstly, we develop a methodology to estimate densities with space and time based on data from loop detectors. The methodology is based on solving a flow conservation differential equation (using LWR theory) with intermediate (internal) freeway mainline boundaries, which is fast er and more accurate from previous resear ch using only external boundaries. To capture the capacity drop phenomenon into the first-order model we utilize a fundamental diagram with two values of capacity and we provide a memory-based methodology to choose the appropriate value in the numerical solution of the problem. Secondly, with respect to ramp metering, the main goals of the algorithm are to delay the onset of the breakdown and to accelerate system recovery when ramp metering is unable due to the violation of maximum allowable ramp waiting time. The effectiveness of the new control strategy is being assessed by comparison with the currently deployed version of the Stratified Zone Algorithm (SZM) through microscopic simulation of a real 12-mile, 17 ramp freeway section. Simulations show a decrease in the delays of mainline and ramp traffic, an improvement 8% in the overall delays and avoidance of the maximum ramp delay violations.
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    Estimating and Measuring Arterial Travel Time and Delay
    (Intelligent Transportation Systems Institute, Center for Transportation Studies, University of Minnesota, 2012-08) Liu, Henry X.; Wu, Xinkai
    To estimate arterial travel time/delay, the key element is to estimate intersection queue length, since travel time, delay, and level of services can be easily derived from queue length information. In this study, we developed a new traffic flow model, named shockwave profile model (SPM), to describe queuing dynamics for congested arterial networks. Taking advantage of the fact that traffic states within a congested link can be simplified as free-flow, saturated, and jammed conditions, the SPM simulates traffic dynamics by analytically deriving the trajectories of four major shockwaves. This model is particularly suitable for simulating congested traffic especially with queue spillover. In the SPM, a novel approach is proposed as part of the SPM, in which queue spillover is treated as either extending a red phase or creating new cycles. Since only the essential features, i.e. queue build-up and dissipation, are considered, the SPM significantly reduces the computational load and improves the numerical efficiency. We further validated the SPM using real-world traffic signal data collected from a major arterial in the Twin Cities. The results clearly demonstrate its effectiveness and accuracy. This model can be applied to estimate arterial travel time and delay and optimize signal timing in real time.
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    Evaluation of a Central Traffic Signal System and Best Practices for Implementation
    (Minnesota Department of Transportation., 2019-03) Parikh, Gordon; Hourdos, John
    Detailed Intersection Control Information (ICI), including timing, phasing, geometric, and demand attributes, is an increasingly important resource for researchers, consultants, and private sector companies for many applications, including development of traffic models and technologies such as vehicle information or automation systems. While this information has historically been difficult to distribute due to variations in the availability and format across the numerous jurisdictions that operate signals, recent trends toward increased use of Central Traffic Signal Control Systems (CTSCSs) have made creation of a unified, standardized system for organizing ICI more feasible. To help work toward this, in this project researchers interviewed and surveyed signal operation engineers and transportation modelers throughout Minnesota to learn how different jurisdictions manage information relating to their signals and how this information is used for operations and planning. With this information, researchers developed a comprehensive Unified Set of Intersection Control Information (U-ICI) that contains all the information required to describe the control of an intersection in a format that is readable by both humans and machines. Along with this, researchers evaluated the availability of this information and the feasibility of using existing CTSCS applications to store this information. While the researchers conclude that it is not feasible to use these applications to store all of the U-ICI, the applications will likely make the process of implementing and populating such a system easier. Though some information may be contained in formats that will require manual effort to digitize, the up-front effort to do so will be a worthwhile pursuit.
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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.