working paper

Design, Field Implementation and Evaluation of Adaptive Ramp Metering Algorithms

Abstract

The main objectives of Task Order 4136 are (1) the design of improved freeway on-ramp metering strategies that make use of recent developments in traffic data collection, traffic simulation, and control theory, and (2) the testing of these methods on a 14-mile segment of Interstate 210 Westbound in southern California. To date, the major accomplishments of this project include (i) the development of a complete procedure for constructing and calibrating a microscopic freeway traffic model using the Vissim microsimulator, which was applied successfully to the full I-210 test site, (ii) a simulation study, using the calibrated Vissim I-210 model, comparing the fixed-rate, Percent Occupancy, and Alinea local ramp metering schemes, which showed that Alinea can improve freeway conditions when mainline occupancies are measured upstream of the on-ramp (as on I-210 and most California freeways), as well as when occupancy sensors are downstream of the on-ramp, (iii) development of computationally efficient macroscopic freeway traffic models, the Modified Cell Transmission Model (MCTM) and Switching-Mode Model (SMM), validation of these models on a 2-mile segment of I-210, and determination of observability and controllability properties of the SMM modes, (iv) design of a semi-automated method for calibrating the parameters of the MCTM and SMM, which, when applied to an MCTM representation of the full I-210 segment, was able to reproduce the approximate behavior of traffic congestion, yielding about 2% average error in the predicted Total Travel Time (TTT), and (v) development of a new technique for generating optimal coordinated ramp metering plans, which minimizes a TTT-like objective function. Simulation results for a macroscopic model of the 14-mile I-210 segment have shown that the optimal plan predicts an 8.4% savings in TTT, with queue constraints, over the 5-hour peak period.

working paper

The Making and Un-Making of the San Francisco-Oakland Bay Bridge: A Case in Megaproject Planning and Decisionmaking

Publication Date

December 31, 2004

Author(s)

Karen Frick

Abstract

After over a decade of debate, construction of the San Francisco-Oakland Bay Bridge’s eastern span finally began in 2002 at a current approximate cost estimate of $6 billion. The intense and controversial debate ranged from whether the bridge should be seismically retrofitted or replaced, how it should be designed, where it should be located, and how it should be funded. Decisions on these issues provided fertile ground for a highly contested process as public agencies at every level of government and mobilized groups and citizens participated and significantly altered the decisionmaking process. The design process also signified a fundamental change in how state and regional agencies plan and manage projects of this magnitude. This dissertation provides a detailed history and analysis of the new span’s state and regional decisionmaking processes.

To guide this case study of a major transportation infrastructure project (also known as a “megaproject”), the research questions addressed are: What are the key characteristics and issues of debate for a major infrastructure project, such as the new Bay Bridge, and how do these impact policy decisions and project outcomes? These questions were designed to set the Bay Bridge case within a larger theoretical context while at the same time allowing the analysis to be of practical interest. This research contributes to the literature by knitting together the themes of megaproject planning, problem definition, agenda setting and policy implementation, as well as the “technological sublime,” which details how large scale projects capture the public’s attention and imagination. For the analysis, a megaproject typology and a conceptual framework focusing on megaproject characteristics and results are developed and applied to the Bay Bridge case. Lastly, several recurring themes throughout the bridge’s development process are examined, including substantial conflicts over the project’s purpose and definition; varying perceptions of crisis; and, disputes over accountability for cost overruns and delay that impeded the project’s implementation.

working paper

Estimating Commuters' "Value of Time" and Noisy Data: a Multiple Imputation Approach

Abstract

We estimate how motorists value their time savings and characterize the degree of heterogeneity in these values by observable traits. We obtain these estimates by analyzing the choices that commuters make in a real market situation, where they are offered a free-flow alternative to congested travel. We do so, however, in an empirical setting where several key observations are missing. To overcome this, we apply Rubin’s Multiple Imputation Method to generate consistent estimates and valid statistical inferences. We also compare these estimates to those produced in a “single imputation” scenario to illustrate the potential hazards of single imputation methods when multiple imputation methods are warranted. Our results show the importance of properly accounting for errors in the imputation process, and they also show that value of time savings varies greatly according to motorist characteristics.

working paper

Considering Risk-Taking Behavior in Travel Time Reliability

Publication Date

December 31, 2004

Abstract

Travel time variability is increasingly being recognized as a major factor influencing travel decisions and, consequently, as an important performance measure in transportation management. In this research project, we examine a number of questions related to travel time variability: How should travel time variability be quantified at both the section level as well as at the route level?; How do travelers value travel time and its reliability?; How much does the travel time reliability contribute to travelers’ route choices?; How much variation is there in travelers’ preferences regarding the potential tradeoff between reliability and travel time itself?; How can travel time variability be incorporated into the route choice models for transportation planning purposes?; and, How can the effects of travel time reliability be incorporated in considering risk-taking behavior in route choice models? Answering these questions can help in the design and evaluation of transportation planning and managing strategies.

working paper

Large-Scale Traffic Simulation Through Distributed Computing of Paramics

Abstract

Simulation modeling is an increasingly popular and effective tool for analyzing transportation problems, which are not amendable to study by other means. We examine the need for parallel or distributed simulation approaches from the need for computational speed-ups, availability of options towards that, and then at the need to distribute the effort to develop network simulation contexts and datasets. After an overview of the general techniques for the distributed discrete-event simulation and previous efforts on the distributed traffic simulation, we present the general architecture of the proposed distributed modeling framework. Two categories of modeling strategies, namely, light global control / independent subnets vs. heavy global control / coordinated subnets are described. We have implemented the distributed scheme of light global control / independent subnets and the implemented details, such as communication techniques and vehicle transferring across the boundary of two subnets are discussed. Unlike the previous studies using the dedicated high performance machines, our efforts are to utilize the low-cost networked PCs that are commonly available. By using the API supported by off-the-shelf Paramics software, we are able to distribute the computational load of microscopic simulation to multiple single-processor PCs without access the proprietary source codes of the simulation program. Performance testing and analysis of the implemented prototype demonstrate that the proposed framework is very promising.

Phd Dissertation

Vehicle monitoring for traffic surveillance and performance using multi-sensor data fusion

Abstract

As traffic surveillance technology continues to advance, more complete and intelligent traffic information are available by processing detector data. The proposed dissertation aims to investigate thoroughly the use of recent detector technology in order to obtain useful freeway performance measurements by integrating multi sensor data fusion with a vehicle monitoring algorithm. Vehicle monitoring refers to the identification of the same vehicles at different locations. In this dissertation, two different state-of-the-art traffic detectors are introduced and the subsequent datasets are fused in order to obtain a more robust and effective traffic dataset for vehicle monitoring. Algorithm development for data fusion and real-time vehicle monitoring for traffic surveillance and performance, TRASURF (TRAffic SURveillance and performance) is developed, described, and investigated. Examinations of feature vector extraction from each advanced traffic sensor, fusion across multiple technologies, and analysis of sensor performance are major tasks prior to the development of the vehicle monitoring algorithm-TRASURF. A real dataset was used for single freeway section vehicle monitoring algorithm development and evaluation. Based on extensive field dataset analysis, PARAMICS (PARAllel MICroscopic Simulation), a microscopic traffic simulation model, was used for simulated fused data generation. Based on simulation dataset, multi-section vehicle monitoring algorithm, TRASURF, was tested and evaluated. The proposed simulation framework could be of great value for both testing and performance comparison of traffic surveillance algorithms. Developed vehicle monitoring system, TRASURF, will reconstruct individual vehicle trajectories, which will contribute to effective and efficient traffic surveillance. Furthermore, this enables the derivation of a variety of useful traffic information including network-wide traffic information such as path travel times and origin destination matrices. In addition to the multi-section TRASURF development, this dissertation also investigates and describes various applications of new detector data. Moreover, investigations on various applications of advanced detectors in transportation fields, and especially in single loop configuration, are also presented. The benefit of this approach can be explained by the fact that most of the freeway loop configurations in California, as well as in many other locations, adopt the single loop concept. Unavailable directly from conventional loop detectors, accurate traffic data extraction based on advanced loop detectors will make a vital contribution in many traffic operation and management fields.

working paper

Development of a Path Flow Estimator for Deriving Steady-State and Time-Dependent Origin-Destination Trip Tables

Publication Date

August 31, 2004

Abstract

The origin-destination (O-D) trip table is a key input required for traffic assignment and simulation models utilized to analyze a wide variety of transportation applications. The main goal of this research is to develop an economical and quick method for estimating O-D trip tables from traffic counts. Path flow estimator (PFE), originally developed by Bell and Shield (1995), has been further developed to improve the reliability and efficiency of O-D trip table estimates. The research reported herein includes only the development of the steady-state O-D estimator. In this study, the original PFE model was carefully examined in several aspects to gain more insight for further improvements. Currently, the PFE has been successfully applied to estimate the steady-state O-D trip tables for the Irvine Testbed network in Orange County, California as well as some other real networks. The primary results demonstrate that PFE has the capability to correctly estimate the total and individual O-D demands when proper information is provided. They also indicate that the number and locations of traffic counts significantly influence the quality of O-D estimates as each observation contributes different amount and quality of information.  The most difficult task observed thus far is the estimation of spatial pattern of O-D demands even when traffic counts were collected on all network links.  These issues and the development of time-dependent PFE will be investigated in the second phase under Task Order 5502.

Phd Dissertation

New Methods for Modeling and Estimating the Social Costs of Motor Vehicle Use

Publication Date

June 29, 2004

Author(s)

Abstract

The body of this dissertation comprises two standalone essays, presented in two respective chapters.

Chapter One develops estimates of how motorists value their travel-time savings and characterizes the degree of heterogeneity in these values by observable traits. These estimates are obtained by analyzing the choices that commuters make in a real market situation, where they are offered a free-flow alternative to congested travel. They are generated, however, in an empirical setting where several key observations are missing. To overcome this, Rubin’s Multiple Imputation Method is employed to produce consistent estimates and valid statistical inferences. These estimates are then compared to those produced in a “single imputation” scenario to illustrate the potential hazards of single imputation methods when multiple imputation methods are warranted. A preferred model suggests that the median commuter is willing to pay $30 to save an hour of travel time. However, taking observed heterogeneity into account, median estimates range from $7 to $65 according to varying, observable motorist characteristics.

Chapter Two develops a theoretical framework for jointly modeling the marginal external accident and travel-delay costs of driving. The framework explicitly accounts for the optimal tradeoffs that motorists make between accident risk and risk-reducing effort. Accident and travel-delay externalities are decomposed into components that correspond to physical accident risk, efforts to offset this risk, and their effects on travel times. An empirical model is developed from this framework, suggesting that joint external costs are $1.80 per vehicle-mile and external accident costs are $0.80 per vehicle-mile during a typical peak-period commute. The analysis does not require observations on accident rates and illustrates how the commonly-adopted approach to modeling accident externalities tends to understate these costs.

published journal article

On-Line Algorithms for the Dynamic Traveling Repair Problem

Abstract

We consider the dynamic traveling repair problem in which requests with deadlines arrive through time on points in a metric space. Servers move from point to point at constant speed. The goal is to plan the motion of servers so that the maximum number of requests are met by their deadline. We consider a restricted version of the problem in which there is a single server and the length of time between the arrival of a request and its deadline is constant. We give upper bounds for the competitive ratio of two very natural algorithms as well as several lower bounds for any deterministic algorithm. Most of the results in this paper are expressed as a function of β, the diameter of the metric space. In particular, we prove that the upper bound given for one of the two algorithms is within a constant factor of the best possible competitive ratio.