Browsing by Author "Liu, Henry X."

Now showing 1 - 9 of 9
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    Development of a Queue Warning System Utilizing ATM Infrastructure System Development and Field-Testing
    (Minnesota Department of Transportation, 2017-06) Hourdos, John; Liu, Zhejun; Dirks, Peter; Liu, Henry X.; Huang, Shihong; Sun, Weili; Xiao, Lin
    MnDOT has already deployed an extensive infrastructure for Active Traffic Management (ATM) on I-35W and I-94 with plans to expand on other segments of the Twin Cities freeway network. The ATM system includes intelligent lane control signals (ILCS) spaced every half mile over every lane to warn motorists of incidents or hazards on the roadway ahead. This project developed two separate systems that can identify lane-specific shockwave or queuing conditions on the freeway and use existing ILCS to warn motorists upstream for rear-end collision prevention. The two systems were field tested at two locations in the ATM equipped network that have a high frequency of rear- end collisions. These locations experience significantly different traffic-flow conditions, allowing for the development and testing of two different approaches to the same problem. The I-94 westbound segment in downtown Minneapolis is known for its high crash rate due to rapidly evolving shockwaves while the I-35W southbound segment north of the TH-62 interchange experiences longstanding queues extending into the freeway mainline. The Minnesota Traffic Observatory developed the I-94 Queue Warning system while the University of Michigan, under contract, developed the I-35W system. Prior to the I-94 installation, based on data collected in 2013, there were 11.9 crashes per VMT and 111.8 near crashes per VMT. In the first three months of the system’s deployment, event frequency reduced to 9.34 crashes per million vehicle miles of travel (MVMT) and 51.8 near crashes per MVMT, a 22% decrease in crashes and a 54% decrease in near crashes. The I-35W system did not undergo a similarly thorough evaluation, but for most of the lane segments involved, it showed that queue warning messages help reduce the speed variance near the queue locations and the speed difference between upstream and downstream locations. This also implicated a satisfactory level of compliance rate from travelers.
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    Development of a Real-Time Arterial Performance Monitoring System Using Traffic Data Available from Existing Signal Systems
    (Minnesota Department of Transportation, 2008-12) Liu, Henry X.; Ma, Wenteng; Wu, Xinkai; Hu, Heng
    Data collection and performance measurement for signalized arterial roads is an area of emerging focus in the United States. As indicated by the results of the 2005 Traffic Signal Operation Self-Assessment Survey, a majority of agencies involved in the operation and maintenance of traffic signal systems do not monitor or archive traffic system performance and thus have limited means to improve their operation. With support from the Transportation Department of Hennepin County, Minneapolis, MN, a system for high resolution traffic signal data collection and arterial performance measurement has been successfully built. The system, named SMART-SIGNAL (Systematic Monitoring of Arterial Road Traffic Signals), is able to collect and archive event-based traffic signal data simultaneously at multiple intersections. Using the event-based traffic data, SMART-SIGNAL can generate timedependent performance measures for both individual intersections and arterials including intersection queue length and arterial travel time. The SMART-SIGNAL system has been deployed at an 11-intersection corridor along France Avenue in south Minneapolis and the estimated performance measures for both intersection queue length and arterial travel times are highly consistent with the observed data.
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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 the Next Generation Metro-Wide Simulation Models for the Twin Cities' Metropolitan Area: Mesoscopic Modeling
    (2011-01) Liu, Henry X.; Danczyk, Adam; He, Xiaozheng
    The collapse of the Interstate 35W Bridge over the Mississippi River in Minneapolis resulted in unexpected loss of life and had serious consequences on mobility and accessibility in the Twin Cities metropolitan area. In response to the network disruption caused by the bridge collapse, a number of traffic restoration projects were proposed and rapidly implemented by MnDOT. Selection and prioritization of these projects, however, was based mainly on engineering judgment and experience. The only decision-support tool available to traffic engineers was the regional transportation planning model, which is static in nature and decennial. In this work, the Twin Cities metropolitan area is simulated using a mesoscopic traffic simulator in the AIMSUN software. After establishing the mesoscopic simulation model, we attempt to utilize the calibrated mesoscopic simulation model to evaluate drivers’ perceived cost evolution to explain the traffic dynamics on the Twin Cities road network after the unexpected collapse of the I-35W Bridge over the Mississippi River. Given the observation of largely underutilized sections of network, it is proposed that the tragedy generated a perceived travel cost to discourage commuters from using these sections. Applying a mesoscopic simulation model provided by AIMSUN, the perceived costs on cordon lines after the I-35W Bridge collapse were suggested to be best described as an exponential decay cost curve. The proposed model is applicable to both practitioners and researchers in traffic-related fields by providing an understanding of how traffic dynamics will evolve after a long-term, unexpected network disruption.
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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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    Estimation of Crossing Conflict at Signalized Intersection Using High-Resolution Traffic Data
    (Minnesota Department of Transportation, 2017-03) Liu, Henry X.; Davis, Gary A.; Shen, Shengyin; Di, Xuan; Chatterjee, Indrajit
    This project explores the possibility of using high-resolution traffic signal data to evaluate intersection safety. Traditional methods using historical crash data collected from infrequently and randomly occurring vehicle collisions can require several years to identify potentially risky situations. By contrast, the proposed method estimates potential traffic conflicts using high-resolution traffic signal data collected from the SMART-Signal system. The potential conflicts estimated in this research include both red-light running events, when stop-bar detectors are available, and crossing (i.e. right-angle) conflicts. Preliminary testing based on limited data showed that estimated conflict frequencies were better than AADT for predicting frequencies of angle crashes. With additional validation this could provide a low-cost and easy-to-use tool for traffic engineers to evaluate traffic safety performance at signalized intersections.
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    Improving Traffic Signal Operations for Integrated Corridor Management
    (Minnesota Department of Transportation, 2013-07) Liu, Henry X.; Hu, Heng
    The Integrated Corridor Management (ICM) approach has drawn increasingly more attention in recent years because it is believed to be a promising tool to mitigate urban traffic congestion. In this project, a maximum flow based control model was first developed to handle oversaturated traffic conditions at signalized arterials. Based on the arterial control model, an integrated control model was proposed to manage network congestion. Through diversion control, the model aims to fully utilize the available capacity along parallel routes. The impact of the diversion traffic is considered, especially for signalized arterials, so that traffic congestion on the diversion route can be reduced or eliminated by proper adjustment of signal timings. This model does not rely on time-dependent traffic demand as model inputs and it is ready to be implemented at typical parallel traffic corridors where the standard detection system is available. The performance of the proposed model was tested using microscopic traffic simulation in the I-394 and TH 55 corridor in Minneapolis, Minnesota. The results indicate that the proposed model can significantly reduce network congestion.
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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.
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    Responding to the Unexpected: Development of a Dynamic Data-Driven Model for Effective Evacuation
    (Minnesota Department of Transportation, 2009-12) Liu, Henry X.; Jabari, Saif Eddin
    This research proposes a framework for real-time traffic management under emergency evacuation. A theoretical framework is first proposed for adaptive system control that involves control updating based on real-world traffic data. A heuristic solution framework is then developed to address the computation complexities that come with real-time computations of evacuee routing strategies that aim at minimizing total evacuee exposure time to harm. Further improvements to network traffic throughput are also considered by incorporating officer deployment strategies to critical network intersections. A genetic algorithms based solution scheme is proposed for the combined evacuee routing and officer deployment problem. An evacuation software tool is developed with embedded GIS capabilities that allows users to build evacuation scenarios and run the developed heuristic algorithms. Finally, the quality and efficiency of the developed solution techniques are demonstrated via hypothetical real-world size evacuation scenarios using the software tools.