bluuebunny/crossref_metadata_2025 huggingface dataset:
Establishing MR&R Costs for a Network-Level Bridge Management System
Authors: Adams Teresa M. , Barut Joseph F.
Published: April 2007

The development of standardized maintenance, repair, and rehabilitation (MR&R) cost data for a network-level bridge management system (BMS) is presented. The Pontis BMS requires several data inputs, including the agency’s costs to perform bridge maintenance actions. Most states that are implementing Pontis do not have historical cost data standardized according to MR&R action, element, and condition state as required. The development of a questionnaire for collecting MR&R costs is described. The questionnaire was used to collect the estimated costs of MR&R actions on 25 bridge elements. Standard definitions of the physical characteristics for the elements were developed. Direct and indirect factors that influence MR&R costs were identified and organized into scenarios corresponding to the extreme minimum and maximum costs. The cost data collected by the questionnaire were analyzed. Procedures for assessing the variability of the estimated costs are presented. The coefficient of variation was used to measure the relative variability of estimated costs. One-way analysis of variance was used to assess the variation in estimated costs among the elements and MR&R actions. A multiple comparisons with the best analysis was used to identify certain elements and MR&R actions with greatest and least variations in cost. The results of this paper include recommended costs for the MR&R actions on 25 elements for the state of Wisconsin.
Long-Term Performance of Conductive-Paint Anodes in Cathodic Protection Systems for Inland Concrete Piers in Virginia
Authors: Clemeña Gerardo G. , Jackson Donald R.
Published: April 2007

As part of continuous efforts to identify effective and durable anodes for use in cathodic protection (CP) of reinforced concrete bridge members, a water-based, electrically conductive paint was evaluated for use as the secondary anode in CP systems for inland concrete piers. The paint was used in two CP systems—one designed and built approximately 6 years ago and the other 8 years ago—to protect the concrete piers of two pairs of twin bridges in Virginia. When adjusted properly, the two systems provided more than sufficient protection to the reinforcing steel. Natural paint deterioration occurred in both systems. In the 8-year-old system, this deterioration ranged from 0 to 0.37 percent. In the 6-year-old system, it ranged from 0 to 0.14 percent. Most of the deterioration occurred at the ends of the pier caps, where the concrete is not sheltered from rain by a deck overhang. The overall performance of the conductive paint in these CP systems was better than expected. Its effectiveness could last for at least 15 years, even longer if minor paint deterioration is touched up as early as possible. This type of conductive paint should, therefore, be considered a suitable secondary anode for use in CP of inland concrete piers.
Corrosion Protection Service Life of Low-Permeable Concretes and Low-Permeable Concrete with a Corrosion Inhibitor
Authors: Żemajtis Jerzy , Weyers Richard E. , Sprinkel Michael M.
Published: April 2007

The results of a 1.5-yr laboratory study and field investigation of three Virginia bridges are presented. Specimens with fly ash, slag cement, silica fume, silica fume with a corrosion inhibitor, and two specimens (controls) with Virginia Department of Transportation specification concrete (A-4) were built to study diffusion characteristics of these concretes and to estimate corresponding corrosion initiation times. The methodology used to estimate the corrosion initiation times is based on Fick’s Second Law of Diffusion. It uses laboratory concrete diffusion characteristics and cumulative distribution functions of the field surface concentration and diffusion coefficient values. The calculations are performed for various cover depths, and a set of curves is provided for each concrete type and for low, mean, and high values of surface concentration (exposure severity) and diffusion coefficient (concrete quality). The analysis results demonstrate the benefits of using mineral admixtures, especially when combined with a corrosion inhibitor.
Effect of Noisy Data on Pavement Performance Prediction by Artificial Neural Networks
Authors: Raja Shekharan A.
Published: April 2007

Artificial neural networks are increasingly employed in prediction modeling and are particularly advantageous when the relationship between the response and the predictor variables is complex. For the purposes of prediction, neural networks are to be trained with data that are accurately compiled. Frequently, the data collected either from field or laboratory observations are noisy in nature. The effect of noisy data on the predictive capability of neural networks has been studied. Present serviceability rating (PSR) of pavements is the attribute to be predicted. Six noisy databases are created and are employed to train the neural networks to predict PSR. Regression equations are developed with the same noisy databases, and the predictions from neural networks are compared with those of regression. The results show that the neural networks predict PSR as accurately as regression models with a given noisy data. In addition, neural networks are trained with data containing no noise. If no noise is present in the data, neural networks predict PSR accurately while properly capturing the effect of each explanatory variable on the response variable.
Pavement Deterioration, Rate of Dynamic Force, and Ride Quality
Authors: Liu Chiu , Herman Robert , Frank McCullough B.
Published: April 2007

Pavement serviceability or ride quality indices have been widely applied to monitor pavement performance and deterioration for pavement rehabilitation, design, and other purposes. It is known that the ride quality or serviceability index of roads can be explained mainly by the vertical jerk experienced by raters sitting in a moving vehicle. However, it is not known to what extent that the indices have to do with some external traffic loading variables (e.g., the rate of dynamic forces or the dynamic forces exerted on a pavement surface by an axle load). Employing some actual road profiles and a half-axle load model, both the dynamic forces and the rate of dynamic forces exerted on a pavement surface are estimated using a spectral density method and a finite difference method, respectively. A very good correlation exists between these physical variables and the ride quality index or the serviceability index, indicating that the deterioration of pavement structures is closely related to the rate of dynamic forces.
Development of a Knowledge-Based Formula to Prioritize Pavement Rehabilitation Projects
Authors: Flintsch Gerardo W. , Zaniewski John P. , Medina Alejandra
Published: April 2007

The development of a formula to prioritize pavement rehabilitation projects based on experts’ opinion is presented. This formula is used for the preparation of the Arizona Department of Transportation (ADOT) 5 yr pavement preservation program. The knowledge to determine the prioritization formula and treatment assignment criteria was captured from a group of experts using a survey design based on the rational factorial methodology. The survey questionnaire provided a set of pavement sections with different characteristics and asked the experts to indicate which sections should receive a rehabilitation treatment, what type of treatment they would recommend for each section, and which priority should be assigned to the resulting preservation project. Eight pavement characteristics (functional classification, geographical region, structural number, traffic, pavement rideability, cracking, rutting, and average maintenance cost for the past 3 yr) were identified as influence variables. A fractional factorial experiment design with four blocks was selected for the study. A questionnaire with a different set of pavement sections was prepared for each experimental block. The questionnaires were sent to pavement experts from ADOT headquarters and maintenance districts. The responses were analyzed, using linear regression analysis, to select the best models for the priority and treatment selection equations. The study showed that the rational factorial methodology is a powerful tool for capturing and quantifying expert opinions. The average opinion of the experts surveyed indicated that rutting, functional classification, roughness, cracking, traffic, and maintenance cost significantly influence the priority assigned to a preservation project. The treatment assignment model was less reliable; a larger panel of experts would be required to obtain a reliable model.
Minimum Pavement Temperature Modeling and Mapping for Alaskan Conditions
Authors: Raad Lutfi , Saboundjian Stephan , Sebaaly Peter , Epps Jon
Published: April 2007

According to the Superpave design system, the selection of asphalt binder using performance-based binder specifications depends in part on the expected high and low pavement temperatures. For low-temperature cracking considerations, the binder should satisfy minimum pavement temperature requirements selected for design. In this case, knowledge of minimum pavement temperature during the design period is essential for proper binder selection. In this study, field temperature data for a number of sites were collected and analyzed. Correlations between minimum air and pavement temperature were established for different Alaskan climatic zones. Results indicate that the minimum pavement temperature could be lower or higher than minimum air temperature. However, for low temperature ranges the pavement temperature is generally warmer than air temperature by 2 to 7° C, depending on climate zone. Comparisons of minimum pavement temperature for Alaskan conditions with Superpave and the Asphalt Institute criteria for selecting minimum pavement design temperature were made. Results show that the criteria are not appropriate for Alaskan pavements. The Superpave prediction is conservative whereas the Asphalt Institute’s prediction model is unconservative. In addition, contour maps corresponding to 50 percent and 98 percent reliability were developed for minimum air and pavement temperatures. The temperature correlations and contour maps provide a simple tool for design engineers to estimate minimum design pavement temperature for selecting appropriate binder specifications.
Switching to International Roughness Index
Authors: Hajek Jerry J. , Kazmierowski Thomas J. , Musgrove Graham
Published: April 2007

The International Roughness Index (IRI) has become a well-recognized standard for measurement of pavement roughness. The main objectives of the study were to evaluate the consequences of switching to IRI roughness measurements, and to develop a procedure for switching from measuring roughness with a response-type device, used for more than 10 years, to an IRI device. The study consisted of two parts. In the first part, the repeatability and consistency of roughness measurements obtained by three different IRI-measuring systems using a 10-section calibration circuit was evaluated. In the second part, transfer functions relating IRI with a subjectively measured ride condition rating for a large pavement network consisting of asphaltic concrete, rigid, and surface-treated pavements were developed. Based on the results of the calibration circuit, the three IRI-measuring systems were proved equally capable of providing repeatable and reliable roughness measurements for network-level monitoring purposes, and their individual results correlated very well. However, because of systematic differences between the results, the IRI-measuring systems cannot be used interchangeably and without proper calibration. Based on the results obtained for the network, different transfer functions were required and developed for the four pavement types (asphaltic concrete, composite, jointed portland cement concrete, and surface-treated). IRI roughness measurements provided better prediction of the ride condition rating than the response-type roughness measurements. These results support the switch to IRI roughness measurements.
Truck Traffic Crossing Texas–Mexico Border
Authors: Harrison Rob , Sanchez-Ruiz Luis A. , Lee Clyde E.
Published: April 2007

U.S.-Mexico trade continues to grow strongly, with much of the non-petroleum surface trade moving by truck. Trade flows through a number of key ports-of-entry at the southern border, and future truck traffic has raised concerns over infrastructure needs, congestion, and safety. Although it was known that Mexican trucks are frequently overloaded, little data were available to show whether this extended to trade movements at the border. This paper reports the results of a research study commissioned by the Texas Department of Transportation and represents the first comprehensive analysis of truck axle loads undertaken at the southern Texas border. Weigh-in-motion systems were installed at the Laredo and El Paso ports-of-entry. WIM data for 1995 show that 25 percent (El Paso) and 35 percent (Laredo) of the observed tandem-axle loads on loaded northbound five-axle trucks (three-axle tractor with tandem-axle semi-trailer) exceeded the U.S. limit (15.4 Mg). This truck type comprised about 80 percent at El Paso and 70 percent at Laredo of all observed weekday northbound border-crossing trucks. In 1995, 80 percent at El Paso and 87 percent at Laredo of the observed tridem-axle loads on loaded six-axle (three-axle tractor with tridem-axle semi-trailer) trucks exceeded the U.S. limit (19 Mg). This truck type, however, typically comprised only 43 trucks per weekday (3 percent of loaded trucks) at Laredo and 13 (2 percent) at El Paso. The occurrence of overloads on tridem axles was reduced substantially at one port-of-entry when the Texas Department of Public Safety temporarily applied enforcement activities in the Customs yard at the Laredo port-of-entry. The WIM technologies worked well under unusual conditions and indicated that they can possibly be used to aid enforcement of size and weight regulations when the next phase of the North American Free Trade Agreement is implemented.
Electronic Permitting Issuance System for Oversize/Overweight Vehicles
Authors: Nozick Linda K. , Turnquist Mark A. , List George F.
Published: April 2007

The effort reported here focuses both on improving the efficiency of the special hauling permitting processes of the New York State Department of Transportation (NYSDOT) and on improving the level of service offered to NYSDOT’s customers—truckers, construction companies, and others applying for permits. The electronic system is designed to replace a largely manual system of data checking, route verification, and permit issuance. By linking personal computers at transmission companies (third parties that prepare and submit permit applications for truckers) directly to computers at NYSDOT, and equipping these computers with automated route verification capability using a geographical information system, improved service can be offered at reduced cost to the state.
Truck Weight Enforcement Measures of Effectiveness: Development and Software Application
Authors: Hanscom F. R. , Goelzer M. W.
Published: April 2007

A software tool was developed to determine what is accomplished as the result of truck weight enforcement efforts. Traditionally applied measures (e.g., numbers of trucks weighed and citations issued) have simply provided indications of enforcement effort. These previously applied measures failed to provide results in terms of real enforcement objectives, such as deterring overweight trucks and minimizing pavement wear and tear. Consequently the need exists to develop and validate truck weight enforcement measures of effectiveness (MOE). MOEs were developed via a series of analytical procedures. They were subsequently validated in a comprehensive four-state field evaluation. Matched (weigh-in-motion) (WIM) data sets, collected under controlled baseline and enforcement conditions, were analyzed to determine the sensitivity of candidate MOEs to actual enforcement activity. Data collection conditions were controlled in order to avoid contamination from hour-of-day, day-of-week, and seasonal effects. The following MOEs, were validated on the basis of their demonstrated sensitivity to truck weight enforcement objectives and the presence of enforcement activity: (1) severity of overweight violations, (2) proportion of overweight trucks, (3) average equivalent single-axle load (ESAL), (4) excess ESALs, and (5) bridge formula violations. These measures are sensitive to legal load-limit compliance objectives of truck weight enforcement procedures as well as the potential for overweight trucks to produce pavement deterioration. The software User Guide that statistically compares calculated MOEs between observed enforcement conditions is described in this paper. The User Guide also allows users to conduct an automated pavement design life analysis estimating, the theoretical pavement-life effect resulting from the observed enforcement activity.
Field Test of Nonintrusive Traffic Detection Technologies
Authors: Bahler Stephen J. , Kranig James M. , Minge Erik D.
Published: April 2007

The results of a 2-year field test of nonintrusive traffic detection technologies are presented. Seventeen devices representing the following eight technologies were evaluated: passive infrared, active infrared, magnetic, radar, doppler microwave, pulse ultrasonic, passive acoustic, and video. The devices were tested in a variety of environmental and traffic conditions at both intersection and freeway test sites. Emphasis was placed on urban traffic conditions, such as heavy congestion; locations that typify temporary counting situations, such as 48-hour or peak hour counts; and performance in the wide variety of weather conditions found in Minnesota. The evaluation also focused on the ease of system set-up and general system reliability. The results show that nonintrusive technologies are capable of performing as well as conventional methods in some, but not all, situations. At the freeway test site, most nonintrusive devices counted within 3 percent of baseline data. At the intersection test site, however, congested stop-and-go traffic hindered the performance of the majority of the devices. Weather and other environmental variables were found to have minimal impact on the majority of devices. This test is the first phase of an ongoing project to evaluate new, nonintrusive technologies and devices. Further research will expand into areas such as real-time datacollection to support intelligent transportation system applications.
Algorithm Development for Derivation of Section-Related Measures of Traffic System Performance Using Inductive Loop Detectors
Authors: Sun Carlos , Ritchie Stephen G. , Tsai Kevin
Published: April 2007

Despite the advent of new detection systems such as video, infrared, microwave, and ultrasound, inductive loop detectors (ILD) still remain the most widely used sensors for traffic information. For example, the California Department of Transportation alone has approximately 300,000 ILD installations, and that number excludes the installations that are part of local cities and agencies. By using these ILDs in “smarter” ways, useful section-related traffic system parameters can be derived, including densities and travel times. Consequently, the existing detection infrastructure can be used for application in many areas of intelligent transportation systems and, especially, in real-time dynamic systems. The process of developing feature extraction and vehicle pattern matching algorithms and the subsequent derivation of section-related measures based on conventional inductive loops are discussed. Field data collected from State Route 24 in Lafayette, Calif., were used for algorithm development and for the testing of algorithm performance. The performance of a section-related algorithm is shown to be much better than the current method of extrapolation from local point measures.
From Particle Hopping Models to Traffic Flow Theory
Authors: Nagel Kai
Published: April 2007

Very simple models of particles hopping on a grid appear too simple to have much similarity to traffic. Yet, some of these models can be proved to generate, in the so-called fluid-dynamical limit, variations of the Lighthill-Whitham theory. For more realistic particle hopping models, the fluid-dynamical limit is not known, but insight can be obtained by observing traffic jam dynamics.
Car-Following Under Congested Conditions: Empirical Findings
Authors: Dijker Thomas , Bovy Piet H.L. , Vermijs Raymond G. M. M.
Published: April 2007

In traffic flow analysis several regimes are distinguished, such as congested and noncongested flow conditions. Indications exist that driving behavior differs by regime and that it may change discontinuously between regimes. In contrast most traffic flow models used today basically assume the same car-following behavior irrespective of the traffic flow regime. It is hypothesized that, because of this deficiency, these models do not always perform satisfactorily. To clarify this issue, differences in car-following between congested and noncongested flow are analyzed with data from two sites on Dutch freeways. It is shown that, at the same speeds, passenger car drivers follow with smaller headways in noncongested than in congested flow. Car-following of truck drivers does not show differences between regimes. Microscopic distance gap-speed models are established for several road-user classes, valid for each of the two flow regimes. To show the improvements resulting from these new microscopic relationships, the latter are implemented in a microscopic simulation model with which macroscopic patterns in traffic flow are modeled. The macroscopic findings produced with the regime-specific car-following rules show a considerable improvement in modeling performance.
Emergent Fundamental Pedestrian Flows from Cellular Automata Microsimulation
Authors: Blue Victor J. , Adler Jeffrey L.
Published: April 2007

In recent years cellular automata (CA) have been successfully applied to modeling traffic flow. Use of a CA for modeling pedestrian flows is examined here. A particle hopping model for a single-directional pedestrian flow over a multilane walkway is presented. This model offers the advantage of effectively capturing the behaviors of pedestrians at the micro-level while attaining realistic macro-level activity. The emergent group behavior is an outgrowth of the interaction of the rule set in simulation. The results indicate that a heuristically derived minimal rule set produces flow patterns that closely resemble the accepted fundamental diagrams. Important parameters for determining the shape of the fundamental diagrams are examined. Key rules used in a vehicular traffic CA are tested for their applicability to the pedestrian CA model.
Changes in Flow-Density Relationship Due to Environmental, Vehicle, and Driver Characteristics
Authors: Kockelman Kara Maria
Published: April 2007

The idea that weather conditions and driver- and vehicle-population characteristics affect a homogenous roadway segment’s flow-versus-density relationship is explored here. The interaction of third-order polynomial regressions of flow on powers of density with a variety of explanatory variables suggests that driver, vehicle, and environmental attributes significantly influence the flow-density relationship and conform in substantial part with intuitive expectations. For example, higher flows are predicted across most densities for more mature and more male traveler groups as well as for nonrainy conditions with fewer long vehicles and trucks. Moreover, under highly congested conditions, braking is associated with slightly higher flows than those predicted for accelerating vehicles.
Construction and Calibration of a Large-Scale Microsimulation Model of the Salt Lake Area
Authors: Rakha H. , Van Aerde M. , Bloomberg L. , Huang X.
Published: April 2007

The objective of this paper is threefold. First, the feasibility of modeling a large-scale network at a microscopic level of detail is presented. Second, the unique data collection challenges that are involved in constructing and calibrating a large-scale network microscopically are described. Third, the unique opportunities and applications from the use of a microscopic as opposed to a macroscopic simulation tool are described. The possibility and feasibility of modeling a large-scale network using a microscopic simulation model is demonstrated. The requirements of a validated microscopic model for large-scale modeling are: ( a) the model must be capable of modeling origin-destination demand tables, ( b) the model must be capable of modeling dynamic traffic routing, and ( c) the model must be capable of modeling the dynamic interaction of freeway/arterial facilities. The data collection and coding exercise for microscopic models is more intensive than for macroscopic models. The calibration exercise for a microscopic model to a large-scale network, although feasible, is by no means an easy task and does require expert assistance. The Salt Lake metropolitan region study has demonstrated that the data collection, coding, and calibration exercise is approximately a 4-person-year exercise. Model execution times during peak periods are still quite high (from 2 to 17 times the simulation time depending on the number of vehicles) for the PC platform (Pentium 200 with 64 megabytes of random-access memory). Consequently, tools that can extract portions of the large-scale network can allow the modeler to conduct various types of sensitivity analyses within a more realistic time frame.
Multiregime Approach for Microscopic Traffic Simulation
Authors: Zhang Yunlong , Owen Larry E. , Clark James E.
Published: April 2007

The purpose of this paper is to explore various traffic modeling aspects and theories that may overcome some of the limitations in existing microscopic simulation models. A multiregime microscopic traffic simulation approach has been formulated featuring realistic and comprehensive carfollowing and lane-changing logic. A prototype implementation of the multiregime approach was developed in C++ and extensively tested. The multiregime simulation results demonstrate the efficiency and validity of the proposed models for a broad range of traffic scenarios. The test and validation results indicate that the model and program outperformed traditional methods and other existing traffic simulation programs. The validity and efficiency of the model is attributed to the fact that the regimes were added to the model incrementally to reflect increasing agreement with real-world traffic flow. The techniques and corresponding models will be used to improve existing microscopic traffic simulation models and programs.
Simulation of an Arterial Incident Environment with Probe Reporting Capability
Authors: Thomas Natacha , Hafeez Bader
Published: April 2007

Intelligent transportation systems have created new traffic monitoring approaches and fueled new interests in automated incident detection systems. One new monitoring approach utilizes actual travel times experienced by vehicles, called probes, equipped to transmit this information in real time to a control center. The database needed to design and calibrate arterial incident detection systems based on probe travel times is nonexistent. A microscopic traffic simulation package, Integrated Traffic Simulation, was selected and enhanced to generate vehicle travel times for the incident and incident-free conditions on an arterial. We evaluated the enhanced model. Significant variations in probe travel times were observed in the event of incidents. Average travel time, contrary to average occupancy, may increase, decrease, or remain constant on arterial streets downstream of an incident.
Urban Freeway Traffic Flow Prediction: Application of Seasonal Autoregressive Integrated Moving Average and Exponential Smoothing Models
Authors: Williams Billy M. , Durvasula Priya K. , Brown Donald E.
Published: April 2007

The application of seasonal time series models to the single-interval traffic flow forecasting problem for urban freeways is addressed. Seasonal time series approaches have not been used in previous forecasting research. However, time series of traffic flow data are characterized by definite periodic cycles. Seasonal autoregressive integrated moving average (ARIMA) and Winters exponential smoothing models were developed and tested on data sets belonging to two sites: Telegraph Road and the Woodrow Wilson Bridge on the inner and outer loops of the Capital Beltway in northern Virginia. Data were 15-min flow rates and were the same as used in prior forecasting research by B. Smith. Direct comparisons with the Smith report findings were made and it was found that ARIMA (2, 0, 1)(0, 1, 1)96 and ARIMA (1, 0, 1)(0, 1, 1)96 were the best-fit models for the Telegraph Road and Wilson Bridge sites, respectively. Best-fit Winters exponential smoothing models were also developed for each site. The single-step forecasting results indicate that seasonal ARIMA models outperform the nearest-neighbor, neural network, and historical average models as reported by Smith.
Estimation of Time-Dependent Turning Fractions at Signalized Intersections
Authors: Chang Gang-Len , Tao Xianding
Published: April 2007

An effective method for estimating time-varying turning fractions at signalized intersections is described. With the inclusion of approximate intersection delay, the proposed model can account for the impacts of signal setting on the dynamic distribution of intersection flows. To improve the estimation accuracy, the use of preestimated turning fractions from a relatively longer time interval has been proposed to serve as additional constraints for the same estimation but over a short time interval. The results of extensive simulation experiments indicated that the proposed method can yield sufficiently accurate as well as efficient estimation of dynamic turning fractions for signalized intersections.
Bayesian Regression-Based Urban Traffic Models
Authors: Frechette Luc A. , Khan Ata M.
Published: April 2007

A Bayesian regression approach is used to develop equations for predicting travel time on central area streets with contributory variables that are intuitive and for which data are readily available in most transportation agencies. In development of multivariate regression models, two disparate sources of information are used: ( a) a priori (what is known before an experiment), and ( b) experimental data (information derived from an experiment). Output of traffic simulation obtained from NETSIM was used as the source of a priori information, whereas the experimental data were obtained from video recordings of traffic operations on selected central business district streets. Bayesian regression software was used in a systematic framework for predictive model development. The developed equations were assessed and results were interpreted from a Bayesian perspective in relation to the various model iterations attempted. The final models provide reasonable predictions of actual travel times that drivers would experience during peak traffic periods in medium to large central business districts.
Nested Logit Models Which Are You Using?
Authors: Koppelman Frank S. , Wen Chieh-Hua
Published: April 2007

The adoption of disaggregate analysis in transportation and other fields has led to widespread use of choice models to describe the influence of the characteristics of decision makers and the attributes of alternatives and choices. The multinomial logit model (MNL) is the most used because of its relative simplicity, the potential to add new alternatives, its ease of estimation, and the wide availability of estimation software. However, concerns about the restrictive assumptions of the MNL (independent and identical distribution of error terms) and its properties have led to a search for more robust model structures. The nested logit model has become widely used in a variety of contexts because of its ability to represent similarities (covariance of error terms) among groups of alternatives. It is not widely recognized that there are two forms of the nested logit model. These different models, the utility maximization nested logit (UMNL) and the nonnormalized nested logit (NNNL), have very different properties, which produce different estimation results, behavioral interpretations, and forecasts. The use of nested logit estimation requires a thoughtful choice from these model structures. Model structure and properties of the UMNL and NNNL models are described and compared, and the differences between them are illustrated analytically and empirically. Although the selection of a structure is a matter of judgment, the UMNL model is preferred because it is based on utility maximization and it has intuitively reasonable elasticity relationships and interpretation of utility parameters across alternatives.
Trip Generation Modeling Using CHAID, a Criterion-Based Segmentation Modeling Tool
Authors: Strambi Orlando , Van De Bilt Karin-Anne
Published: April 2007

Conventional trip generation models are identified, as are the difficulties of model application typical of segmentation problems: identification and categorization of explanatory variables and of the interactions among them. The use of CHAID (Chi-Squared Automatic Interaction Detection), a criterion-based segmentation modeling tool, is explored to analyze household trip generation rates. CHAID models are presented in the form of a tree, each final node representing a group of homogenous households concerning daily trip making. An application to data from an origin-destination survey for São Paulo produced interesting results, in agreement with theoretical expectations and amenable to interpretation based on the likely activity-travel patterns of each group of households generated by the technique. CHAID can be used as an exploratory technique for aiding model development or as a model by itself. The use of CHAID results as a trip generation model was verified through an evaluation of its predictive capability in a cross comparison of two subsamples and through a comparison of observed versus predicted trips at a zone level; the segmentation of households produced by the technique provided good estimates of trip rates and zone totals. The application of a modeling approach requiring a highly disaggregate projection of the population may become possible considering the advances in methods for the generation of synthetic populations. The use of these methods in conjunction with a segmentation model represents an alternative to conventional trip generation models and an opportunity to introduce new population forecasting techniques into transportation planning practice.
Using Travel Demand Models and Pairwise Comparisons To Evaluate Alternative Transportation Networks in Niagara
Authors: Mekky Ali
Published: April 2007

Evaluating various alternative transportation proposals is one of the most important stages in the transportation planning process. It represents the culmination of various efforts of data collection, goals and objectives formulation, and demand modeling. Some major problems in comparing alternatives are that their effects usually are numerous, affecting various socioeconomic groups in different ways; some effects are quantifiable and others are not; and the scale and the units of each effect may be different from the others. The pairwise comparisons (PWC) method, used for a Niagara-area study, offers a structured approach to deal with this situation. The Niagara study covers a large part of the peninsula between Lake Ontario and Lake Erie. A travel demand model was calibrated and used to quantify network indicators. In the comprehensive evaluation, nonnetwork criteria also were used. The PWC evaluation methodology used in this study is discussed, along with the network and nonnetwork objectives, criteria, and measures. Sensitivity analysis on the ranking results is explained. Another method of obtaining the most reliable consensus of a group of experts is compared with the PWC method. The benefits of the PWC method and conclusions are given.
Analysis of Travel Behavior Using Sequence Alignment Methods
Authors: Wilson Clarke
Published: April 2007

Sequence alignment methods are applied to daily activity data derived from the Statistics Canada 1992 General Social Survey on Time Use, with special emphasis on travel episodes and the activities that generate travel. Sequence alignment is a combinatorial procedure that gives a quantitative measure of the similarity of character sequences, which may be used to represent daily activity patterns. It accommodates all the details supplied from activity diaries including the ordering of activity episodes, their duration, and patterns of transitions from one activity to another. Analysis of daily activity patterns by using such methods offers a new way of improving understanding of travel behavior. Such an understanding is especially critical when public transport policy is being driven increasingly by budget constraints, and traffic management through congestion is considered an acceptable response to increasing travel demands. The method successfully identifies groupings of behavioral patterns, which then may be further described by using multivariate analysis of sociodemographic characteristics. A key issue in the application of the method is to determine the circumstances in which activity sequences should or should not reflect episode duration.
Disaggregate Attraction-End Choice Modeling: Formulation and Empirical Analysis
Authors: Bhat Chandra , Govindarajan Ajay , Pulugurta Vamsi
Published: April 2007

For travel demand models to provide good forecasts, they must be causal; that is, the models should represent the travel decisions made by individuals (and households) and should incorporate important demographic and policy-sensitive explanatory variables. This recognition has led to a shift from the aggregate modeling paradigm to the disaggregate modeling paradigm, evident in the widespread use of disaggregate trip production and mode choice models in practice. However, this shift toward disaggregate procedures has not yet influenced the fundamental specification of trip attraction and distribution models employed in practice. Developed and estimated were disaggregate attraction-end choice models that will facilitate the replacement of the aggregate trip attraction and distribution models currently in use. The proposed disaggregate attraction-end choice model is compared with the disaggregate equivalent of the gravity model.
Traveler Destination Choice Behavior: Effects of Time of Day, Activity Duration, and Home Location
Authors: Kitamura Ryuichi , Chen Cynthia , Narayanan Ravi
Published: April 2007

Multinomial logit destination choice models are developed and the following hypotheses are examined: ( a) time of day affects destination choice behavior, ( b) the duration of stay at the destination affects destination choice, and ( c) home location affects non-home-based destination choice. The statistical results offer strong evidence in support of the hypotheses.
Perceptions in Mode Choice Using Situational Approach “Trip-by-Trip Multivariate Analysis for Public Transportation”
Authors: Goulias Konstadinos , Brog Werner , Erl Erhard
Published: April 2007

Objective and subjective constraints that trip makers face are analyzed by using a trip-by-trip multivariate unbalanced panel analysis. These constraints emerge from trip makers’ stated reasons and dispositions for why a given mode was not used for their trips. A finite set of behavioral dimensions (situations), which are general, system, and service constraints, lack of information about the modes, negative disposition toward a mode, and time, comfort, and cost considerations were derived from open-ended questions on the respondents’ stated reasons. The presence of these situations, for each trip a person made in a day, is explained in terms of social and economic characteristics of the trip maker, place of residence, household resources, and trip characteristics. As expected, stated reasons for not using a specific mode vary with respect to the mode chosen, and they change within a day in a nonlinear manner depending on a person’s schedule. Illustrated is another facet of unobserved heterogeneity represented in the radically different individual perceptions, which have been recognized as important components in dynamic behavior simulation studies.
Modeling Incident-Related Routing Decisions by Using a Nested Logit Structure
Authors: Abdel-Aty Mohamed A.
Published: April 2007

Unusual congestion that could be caused by an incident or other traffic problems is a major source of delay for drivers in urban areas. Real-time traffic information, the building block for advanced traveler information systems (ATIS), has a promising potential for alleviating such congestion by encouraging and assisting drivers to divert to less congested routes. Traffic information is envisioned to help more informed routing decisions in case of incident-related congestion. Drivers’ routing decisions made when they are faced with such unusual congestion are investigated. The factors that influence these decisions are explored, including the effect of traffic information. A nested logit modeling structure is introduced. This model proved that the nested logit approach is superior than the simple multinomial logit in modeling the choice in cases of incident-related congestion. The model also showed that the decisions not to divert from the usual route and to divert but only around the location of the problem share unobserved terms. Familiarity and usual use of alternative routes did not affect the decision in the case of an incident. Drivers who use more than one route to work do not necessarily switch routes if they encounter unusual congestion. The nested logit model also proved the significance of traffic information, indicating a promising potential benefit of ATIS in alleviating nonrecurring congestion.
Flexibility and Time Dependence in Activity Scheduling Models
Authors: Venter Christoffel , Hansen Mark
Published: April 2007

Activity scheduling models describe how people build daily activity schedules, given the opportunities and constraints they face. Many current models fail to adequately account for interdependence of these opportunities and constraints over time. This limits their ability to model aspects of behavior such as routine patterns, the desire for flexibility, and responses to urgent needs. Time dependence issues affect user responses to many transportation policies, including ridesharing incentives, flex-time, and paratransit strategies. Time dependence can be better captured by conceptualizing the activity scheduling process as a regulation and control process, the objective of which is to obtain an activity program that is both feasible and personally optimal. Activity schedules evolve over time as a result of regulatory action taken in response to the arrival of disturbances. An example is provided to illustrate the application of these concepts to the activity scheduling process. While it can incorporate useful ideas previously forwarded by researchers, control theory provides a framework for further theoretical and empirical development.
Application of Simultaneous and Sequential Transportation Network Equilibrium Models to Riyadh, Saudi Arabia
Authors: Hasan Mohamad K. , Al-Gadhi Saad A. H.
Published: April 2007

The approach used in practice to predict short-run transport equilibria involves a sequential process, often with four stages: trip generation, trip distribution, modal split, and traffic assignment. This approach has an inherent weakness—its prediction need not be internally consistent. This deficiency has motivated attempts to predict all four stages simultaneously. The (conventional) sequential and simultaneous models are compared by calibrating and applying both models to the urban transportation network of Riyadh, Saudi Arabia. The main finding is that the simultaneous model produces better traffic flow predictions than the prediction of the conventional sequential model. These predictions are much better for the heavy volume links that are the most important links in the prediction process.
Modeling Network Travel Time Impact of Freeway Ramp Metering
Authors: Janson Bruce N.
Published: April 2007

Whether freeway ramp metering can reduce total travel time in a corridor of several alternative routes depends on changes in route volumes and travel times. Ramp metering effectiveness and ramp metering algorithms have been evaluated mainly on the basis of improved freeway operations. Most studies have not evaluated the impact on alternative routes because of the complexity of the problem (e.g., which routes and what lengths of routes should be studied). An analysis of ramp metering impact in a network corridor is presented, first for simple steady-state cases and then for more complex cases involving time-varying demand, upstream and downstream queueing on freeway and alternative routes, and variable ramp metering rates based on freeway conditions. Time-varying examples are solved with a dynamic traffic assignment model called DYMOD. The analysis shows that ramp metering yields total travel time savings if (a) downstream freeway capacities are sufficiently restrictive, and (b) competitive alternative routes exist to accommodate the diverted traffic. The conditions under which ramp metering can be effective is illustrated by an examination of these simplified cases, and a useful modeling approach to analyzing systemwide impact in a larger corridor is demonstrated.
Maximum Likelihood Estimation for Combined Travel Choice Model Parameters
Authors: Hicks James E. , Abdel-Aal Mounir M.
Published: April 2007

Equilibrium models of combined location and travel choices solve for the modal link flow pattern, which simultaneously solves a constrained minimization problem and satisfies a set of equilibrium conditions characterizing a rational behavior for traveler choices in an urban transportation system. The minimization problem typically is made to be representative of the particular urban area being studied by including coefficients of travel costs and travel choices that have been estimated from locally available observed data. For large urban areas, in practice, it is possible to derive interzonal travel times and costs only from the travel model, because suitable observed data are nonexistent. In this case, the estimation problem is a function of the travel model variables and, at the same time, the travel model is a function of the parameters determined by the estimation problem. Procedures to computationally search for a stable solution to this bilevel optimization problem have been addressed with limited success. The parameter estimation is solved in an iterative procedure in which first parameters are held fixed and the travel model is solved, then travel patterns are held fixed and the maximum likelihood parameters are solved by the Newton-Raphson method. Each successive parameter estimation resulting from these two steps results in a new set of parameter values for the next iteration until stable values for the parameters are achieved. The quality of the convergence of the parameter estimates is reported.
System Optimal Time-Dependent Path Assignment and Signal Timing in Traffic Network
Authors: Abdelfatah Akmal S. , Mahmassani Hani S.
Published: April 2007

Optimization of system performance in congested traffic networks is one of the main goals of intelligent transportation systems. A formulation and solution algorithm for the combined signal control and dynamic traffic assignment problem is presented. The solution algorithm is implemented and tested on an actual network, illustrating the benefits that could be attained through joint optimization of signal control and route guidance decisions.