Browsing by Author "Sun, Jie"

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    Improving Freeway Traffic Speed Estimation Using High-Resolution Loop Detector Data
    (Intelligent Transportation Systems Institute, Center for Transportation Studies, University of Minnesota, 2013-04) Liu, Henry; Sun, Jie
    In this project, we developed an innovative methodology to solve a long-standing traffic engineering problem, i.e. measuring traffic speed using data from single inductive loop detectors. Traditionally, traffic speeds are estimated using aggregated detector data with a manually calibrated effective vehicle length. The calibration effort (usually through running probe vehicles), however, is time consuming and costly. Instead of using aggregated data, in this project, our data collection system records every vehicle-detector actuation "event" so that for each vehicle we can identify the time gap and the detector occupation time. With such high-resolution "event-based" data, we devised a method to differentiate regular cars with longer vehicles. The proposed method is based on the observation that longer vehicles will have longer detector occupation time. Therefore, we can identify longer vehicles by detecting the changes of occupation time in a vehicle platoon. The "event-based" detector data can be obtained through the implementation of the SMART-Signal (Systematic Monitoring of Arterial Road Traffic Signals) system, which was developed by the principal investigator and his students in the last five years. The method is tested using the data from Trunk Highway 55, which is a high-speed arterial corridor controlled by coordinated traffic signals. The result shows that the proposed method can correctly identify most of the vehicles passing by inductive loop detectors. The identification of long vehicles will improve the estimation of effective vehicle length on roads. Consequently, speed estimation from the inductive loop detector is improved.
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    Investigating the Properties and Existence of a Macroscopic Fundamental Diagram for Arterial and Freeway Traffic Systems
    (2009-09) Sun, Jie
    A field experiment in Yokohama (Japan) revealed that a macroscopic fundamental diagram (MFD) linking space-mean flow , density and speed exists on a large urban area. Despite these and other recent findings for the existence of well defined MFDs for urban areas, these MFDs should not be universally expected. In this thesis, the properties of a well defined MFD are investigated and it is found out that the spatial distribution of density/occupancy in the network is one of the key components that affect the scatter of an MFD and its shape. An analytical derivation of the spatial distribution that considers correlation between adjacent links has also been proposed. The scatter of an MFD in terms of errors in probability density function of spatial occupancy and errors of individual links' fundamental diagram (FD) have also been investigated and an analytical estimation of the errors is provided. Using real data from detectors for an urban arterial and a freeway network we validate the proposed derivations and we show that an MFD is not well defined in freeway networks as hysteresis effects are present. The hysteresis phenomenon in network is investigated at different levels of the network and it is found out that the heterogeneity of the network and the hysteresis in the individual detectors should account for this phenomenon. The datasets in this paper consist of flow and occupancy measures from 500 fixed sensors in the Yokohama downtown area and 600 loop detectors in the Twin Cities Metropolitan Area Freeway network (Minnesota, USA).
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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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    Vehicle routing problems in signalized traffic networks
    (2014-08) Sun, Jie
    This dissertation studied various path search problems when traffic signal information and traffic state is explicitly considered. The research is motivated by the increasing availability of high-resolution traffic data including signal information, which is seldom available in the past. In order to properly account for the randomness resulting from vehicle-actuated traffic signals and the correlation from signal coordination, the theory of Markov decision process (MDP) is used. By taking advantage of the cyclic property of traffic signals, the problem is formulated as an infinite horizon and finite state space MDP with absorbing state set. The objective is to find the optimal policy that gives the minimum expected total cost to the destination.The state space of the problem is generated based on underlying traffic network geometry and signal control information. Delay distributions at intersections together with signal control parameters, such as cycle length and offset, are used to construct the transition probabilities between states. It will be shown that the required delay distributions can be estimated from readily available field traffic data. The problem where the cost is travel time is first studied. When the cost of concern is the travel time, it includes intersection delays and link travel times. Value iteration method is used to solve the MDP problem when there is only one cost of concern.In addition, the problem whose cost of concern is environmentally related is also studied. Vehicle trajectories are estimated based on traffic signal information and queuing dynamics at intersections, and put into microscopic vehicle emission models, the results from which are used to calculate the environmental costs for the path search problem. When multiple costs of concern present, the problem is formulated as a constrained MDP problem. Linear programming formulation of MDP is introduced to solve constrained MDP problem. The proposed methods are tested in a hypothetical traffic network, as well as a real world traffic network in the City of Pasadena, CA.