Author: Ying Liu
Type: PhD Dissertation
Status: Completed
Year: 2007
Abstract: How to effectively control evacuation traffic has emerged as one of the critical research issues in transportation community, due to the unusually high demand surge and the often limited network capacity. This dissertation has developed an integrated traffic control system for evacuation operations that may require concurrent implementation of different control options, including traffic routing, contraflow operation, staged evacuation, and intersection signal control. The system applies a hierarchical control framework to achieve a trade-off between modeling accuracy and operational efficiency for large-scale network applications. The network-level optimization formulations function to assign traffic to different evacuation corridors, select lane reversal configurations for contraflow operations, and identify the evacuation sequence of different demand zones for staged evacuation. With special constraints to approximate flow interactions at intersections, the formulations have introduced two network enhancement approaches with the aim to capture the real-world operational complexities associated with contraflow operations and staged evacuation.
Author: Kyeong-Pyo Kang
Type: PhD Dissertation
Status: Completed
Year: 2006
Abstract: To improve traffic mobility and safety on highway segments plagued by work zone activities, transportation professionals in recent years have focused on exploring the potentials of using various merge and speed control strategies to regulate traffic flows. This study is focused on developing an advanced dynamic merge and variable speed limit controls for work zone applications, including an integration of both controls for best use of their strengths in maximizing throughputs and minimizing speed variance in traffic flows. With respect to the merge control, this study has developed an advanced dynamic late merge (DLM) control model and its operation algorithm, based on the optimized control thresholds that take into account the interactions between the speed, flow, and available work zone capacity. The proposed DLM control allows potential users to select the control variables and to determine their optimal thresholds in response to traffic flow dynamics. Evaluation results with extensive simulation experiments have shown that the work zone highway segment with the proposed DLM can effectively respond to time-varying traffic conditions and yield more work-zone throughputs than that under the existing DLM control based on the static control threshold, and also result in an increase in the average speed and decrease in the speed variation.
Author: Pei-Wei Lin
Type: PhD Dissertation
Status: Completed
Year: 2006
Abstract: The purpose of this study is to develop an effective model and algorithm for estimating dynamic Origin-Destination demands for freeways. The primary challenge for this research subject lies in the fact that the number of unknown parameters is always more than the number of observable data, especially for a large network. Hence, the estimated O-D patterns may result in a large variance and insufficient reliability for use in practice. Besides, most existing approaches are grounded on the assumptions that a reliable initial O-D set is available and traffic volume data from detectors are accurate. However, in most highway network systems, both types of critical information are either unavailable or subjected to a significant level of measurement errors. To deal with those critical issues, this study has developed a set of dynamic models and solution algorithms for estimating freeway dynamic O-D matrices. The first extended model formulations can capture the speed discrepancy among drivers with an embedded travel time distribution function and the derivable interrelations between time varying ramp and mainline flows. These formulations also feature their best use of the available mainline information and travel time function, and hence substantially increase the system observability with fewer parameters.
Author: Nan Zou
Type: Ph. D. Dissertation
Status: Completed
Year: 2007
Abstract: Due to the increasing congestion in most urban networks, providing reliable trip times to commuters has emerged as one of the most critical challenges for all existing Advanced Traffic Information Systems (ATIS). However, predicting travel time is a very complex and difficult task, as the resulting accuracy varies with many variables of time-varying nature, including the day-to-day traffic demands, responses of individual drivers to daily commuting congestion, conditions of the road facility, weather, incidents, and reliability of available detectors. This study aims to develop a travel time prediction system that needs only a small number of reliable traffic detectors to perform accurate real-time travel time predictions under recurrent traffic conditions. To ensure its effectiveness, the proposed system consists of three principle modules: travel time estimation module, travel time prediction module, and the missing data estimation module.
Author: Yue Liu
Type: Ph.D. Defense
Status: Completed
Year: 2009
Abstract: This research has focused on developing an advanced dynamic corridor traffic control system that can assist responsible traffic professionals in generating effective control strategies for contending with non-recurrent congestion that often concurrently plagues both the freeway and arterial systems. The developed system features its hierarchical operating structure that consists of an integrated-level control and a local-level module for bottleneck management. The primary function of the integrated-level control is to maximize the capacity utilization of the entire corridor under incident conditions with concurrently implemented strategies over dynamically computed windows, including diversion control at critical off-ramps, on-ramp metering, and optimal arterial signal timings. The system development process starts with design of a set of innovative network formulations that can accurately and efficiently capture the operational characteristics of traffic flows in the entire corridor optimization process.
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Author: Woon Kim
Type: Master’s thesis
Status: Completed
Year: 2007
Abstract: This study presents a set of models for predicting incident duration and identifying variables associated with the incident duration in the state of Maryland. The incident database for years 2003 to 2005 from the Maryland State Highway (MDSHA) database is used for model development, and year 2006 for the model validation. This study, based on the preliminary analysis with the Classification Tree method, has employed the Rule-Based Tree Model to develop the primary prediction model. To enhance the prediction accuracy for some incidents with complex nature or limited samples, the study has also proposed and calibrated several supplemental components based on the Multinomial Logit and Regression methods. Although the prediction accuracy could still be improved if a data set with better quality is available, the developed set of models offers an effective tool for responsible agencies to estimate the approximate duration of a detected incident, which is crucial in projecting the potential impacts on the highway network.
Authors: Jie Yu, Yue Lie, and Xiaoguang Yang
Conference: 2008 TRB Annual Meeting
Type: Accepted for Presentation
Abstract:
Choosing proper locations of urban transit hubs has always been one of the critical concerns facing urban transportation planning agencies in China. This study proposes a mixed integer optimal location model for urban transit hubs, with the objective to minimize the demand-weighted total travel time, when explicitly taking into account Traffic Analysis Zones (TAZs) as demand origins or destinations in a target urban area. An Integer Non-linear Programming (INLP) reformulation was developed to significantly reduce the number of variables. Bilinear constraints in the proposed INLP formulation were then re-modeled into linear functions to ensure global optimal solutions obtained. The model was successfully applied to optimize the hub locations in Suzhou Industrial Park, China, with the result of significantly improved system performance. The impacts of several critical factors, such as the number of hubs and the travel time discount coefficient on the system performance are also investigated.
Authors: Jie Yu, Yue, Liu, and Gang-Len Chang
Journal: ASCE Journal of Infrastructure Systems
Abstract:
This paper presents a robust multi-criteria model for prioritizing highway safety improvement projects, in which a set of criteria related to the project’s technical, economic, social and environmental impacts are properly weighted in consideration. The proposed model features an analytical hierarchy process (AHP) framework to tackle the multi-criteria decision making problem. Different from the conventional AHP, this paper adds a fuzzy scale level between the criteria level and the alternative level which offers the advantage of preventing the vagueness and uncertainty on judgments of the decision-maker(s). Such a unique modeling feature is further embedded with a nonlinear optimization formulation to maximize the consistency in pair-wise comparison and weight estimation for each criterion. Case study results reveal that the proposed model is efficient not only for selecting the most suitable project for a specific site, but also for determining the priorities for implementation those suitable projects among multiple sites given the budget constraint. Comparative study between the proposed model and the existing ranking methods has also indicated its capability to capture the comprehensive impacts of all contributory factors which have been neglected by most existing approaches during the safety project selection process. The clarity of model inputs, ease of synthesizing the final score of each candidate project, and the interpretation of results with respect to different selection criteria offer its best potential to be used as an effective tool for highway infrastructure manager and transportation authorities to assess and refine the highway safety improvement investments.
Authors: Yue Liu, Gang-Len Chang, and Jie Yu
Journal: IEEE transaction on Vehicular Technology
Abstract:
This study presents an integrated model and its solution algorithm for freeway corridor control during incident management. With a parallel arterial as the detour route, the proposed model aims to produce the optimal diversion rates from the freeway mainline to relieve the congestion at the incident segment, and concurrently adjust signal timings at the arterial intersections to best accommodate the detour traffic. Different from previous studies, the presented model and algorithm have the following two critical features: (1) modeling explicitly the evolution of detour traffic along the ramps and surface streets with a set of dynamic network flow formulations so as to capture the local bottlenecks caused by demand surge due to diversion operations, and to properly set the responsive signal timing plans; and (2) developing a multi-objective optimization framework to maximize the utilization of the available corridor capacity via detour operations, but not to incur excessive congestion on the arterials and ramps. This study employs a Genetic Algorithm (GA) based heuristic to efficiently yield the reliable solution depending on decision maker’s preference. Extensive numerical tests on a segment along the I-95 corridor with its neighboring arterials have demonstrated the potential of the developed model for integrated freeway corridor control.
Authors: Jie Yu, Sung Yoon Park, and Gang-Len Chang
Abstract: A real-time advanced traveler information system for traffic heading to Ocean City, Maryland, is presented. It can provide dynamic route choice guidance for en route travelers, offer web-based historical data for pretrip tourists, and perform real-time traffic monitoring as well as emergency evacuation for responsible agencies with its 40 detectors. The proposed system is designed to contend with most critical issues associated with real-time operations, including automated detection of incidents, reliable estimation of missing data, and continuous updates of historical databases. Implementation results demonstrate that the travel time information displayed by the proposed system has been well received by drivers and is viewed as the primary resource for choice of routes to Ocean City. The evolution of traffic volumes on alternative routes during congested periods reveals that the travel time information from variable message signs not only provides guidance to drivers but also leads to better use of roadway capacity and results in more throughputs for the same period of operation.