bluuebunny/crossref_metadata_2025 huggingface dataset:
Analytic Hierarchy Process as a Tool for Infrastructure Management
Authors: Smith James T. , Tighe Susan L.
Published: May 2018

The role of infrastructure management has been continuously changing since the late 1980s. Public agencies have started to incorporate private-sector practices. These new practices include the use of customer inputs to develop new goals and policies, development of new evaluation procedures for priority programming optimization, and addition of feedback loops into infrastructure management systems. One of the new evaluation procedures adopted into infrastructure management is the analytic hierarchy process (AHP). AHP is a decision-making tool that incorporates both qualitative and quantitative factors. AHP has increased in use and popularity because of its ability to reflect the way people think and make decisions by simplifying a complex decision into a series of one-on-one comparisons. The results are then synthesized and presented as a percentage of all the options evaluated. This presentation will illustrate AHP with two examples. In the first example, AHP was used to compare fast-track concrete repair products on the basis of the priorities set by a public agency. Three fast-track concrete repair products were compared with the use of 16 criteria comprised of construction procedures and physical properties. Without field testing, AHP showed that two of the tested products were superior to the other. In the second example, AHP was used to compare seven maintenance, rehabilitation, and reconstruction strategies for asphalt pavements. This comparison was based on nine priorities compiled from a survey of road users.
Modeling Crack Deterioration of Flexible Pavements
Authors: Yang Jidong , Lu Jian John , Gunaratne Manjriker , Dietrich Bruce
Published: May 2018

Pavement cracking and rutting are two of the most critical distress types manifested on flexible pavements, and they often govern the overall pavement condition. Hence, many models have been developed for forecasting the deterioration of the crack condition accurately, with the traditionally preferred technique being the use of a regression relationship developed from laboratory or field statistical data, or both. However, it becomes tedious for regression techniques to predict crack performance accurately and robustly in the presence of the multitude of tributary factors, material nonlinearity, and uncertainty involved in the cracking process. With the advancement of modeling techniques, two innovative breeds of models, neural networks and recurrent Markov chains, have drawn increasing attention from researchers for their use in modeling complex phenomena such as pavement cracking. This paper compares the ability of neural networks and recurrent Markov chains to model crack performance, using the Florida Department of Transportation's pavement condition data. Comparable forecasting accuracies have been indicated for single-year forecasts using both models. When the models were applied for multiple-year prediction of crack performance, the recurrent Markov chain tends to produce more consistent forecasts as compared to the neural network, which exhibits a tendency toward overpredicting crack deterioration. Finally, further discussion gives an insight into the structure of each model.
Decision-Making Model for Base Material Options
Authors: Choi Jaehyun , Minchin R. Edward , Herbsman Zohar J.
Published: May 2018

On the majority of Florida Department of Transportation (FDOT) highway projects, each bidder may choose which base material to use to construct a project. The choice usually comes down to an aggregate base (typically limerock) or a hot-mix asphalt base. When only initial cost parameters are used, the limerock alternative appears to be the most cost-effective. However, some or all of the savings experienced in the purchase may be offset when the total costs, including road user and construction engineering and inspection costs, are considered. An economic model that includes life-cycle cost is needed to evaluate fully the many trade-offs encountered when these decisions are being made. However, state highway officials report that life-cycle costs are not considered in selection of base material; therefore, the scope of this paper is limited to the construction costs associated with each option. The objective of this paper is to report on the development of a method to determine which alternative would be the most economical on a given project on the basis of total cost. Through data analysis, the research team developed a process that will enable an owner to make a more reasonable and informed decision on base material predicated on total cost parameters.
Factors Contributing to Differences between Profiler and the International Roughness Index
Authors: Perera Rohan W. , Kohn Starr D. , Wiser Larry J.
Published: May 2018

One of the data elements included in a pavement management system is the roughness of each highway segment. State highway agencies use inertial profilers to collect profile data of the pavements and then use these data to compute the International Roughness Index (IRI) of each highway segment. An issue concerning the use of inertial profilers is whether the IRI values computed from the profile data are accurate. This issue is usually investigated by the establishment of several test sections, the collection of profile data on these sections with a reference device as well as the profiler, and then a comparison of the IRI values. In many cases, a given profiler will have excellent agreement in IRI with the reference device at some sections but noticeable differences in IRI at others. Data collected for Long-Term Pavement Performance profiler comparison studies were analyzed to identify factors that could contribute to differences between profiler and reference device IRI. The analysis indicated that the following factors can contribute to differences in IRI values: sampling qualities of the reference device, variability in the path followed by the profiler, averaging effects of profiler data, reference device data errors, IRI computational procedure of the profiler, and operational procedures during profiler data collection. Procedures that can be followed to minimize the difference in IRI and the application of roughness profiles to identify the cause for such differences are presented.
Evaluation of Coarse- and Fine-Graded Superpave Mixtures under Accelerated Pavement Testing
Authors: Choubane Bouzid , Gokhale Salil , Sholar Gregory , Moseley Howard
Published: May 2018

Initial Superpave® implementation guidelines encouraged mix designers to develop coarse gradations for higher-traffic-level mixtures, as this was thought to produce a more robust aggregate structure. Consequently, many agencies have specified the use of a coarse-graded asphalt mixture on high-volume facilities. However, target density can be difficult to obtain while compacting coarse-graded mixtures, and control of volumetric properties is harder to maintain than it is for fine-graded mixtures. The Florida Department of Transportation (FDOT) conducted an experiment to assess the rutting performance of coarse- and fine-graded Superpave mixtures under accelerated pavement testing (APT). Both mixtures consisted of aggregate from the same source and were made with virgin binder meeting the requirements of performance grade 67-22. Both mixtures contained the same effective binder content and were designed for 10 million to 30 million equivalent single axle loads, according to the standard Superpave mix design methodology. During placement of these mixtures, all standard FDOT density requirements and acceptance criteria were applicable. The subsequent investigation showed that under similarly controlled conditions, the fine-graded mixture performed slightly better than the coarse-graded mixture in terms of rutting resistance. This paper describes the testing program, data collection efforts, and subsequent analysis and findings and focuses primarily on rutting as generated and observed under APT.
Durability of Galvanized Soil Reinforcement
Authors: Gladstone Robert A. , Anderson Peter L. , Fishman Kenneth L. , Withiam James L.
Published: May 2018

AASHTO promulgated specifications for the design of mechanically stabilized earth (MSE) walls that define the characteristics of both the galvanized steel reinforcements and the backfill soils to be used in MSE wall construction. Although a few cases of poor performance have been documented, these occurrences are always correlated with a corrosive environment attributed to backfill or to site conditions that do not conform to the current design specifications. Data demonstrate that when good design and construction practices, as prescribed by AASHTO, are followed, the performance of metallic reinforcements exceeds current expectations for service life performance. The data also demonstrate that the current AASHTO metal loss model is unnecessarily conservative and that the AASHTO specifications should be revised to reflect documented in situ performance. To support this conclusion, the performance of galvanized steel reinforcements documented from nearly 150 observations distributed among 75 different sites throughout the United States and Europe are described, and these data are used as a basis to evaluate the metal loss model in the current AASHTO specifications.
Seismic Vulnerability of Highway Bridge Embankments
Authors: Zatar Wael A. , Harik Issam E. , Sutterer Kevin G.
Published: May 2018

The objective of this study was to provide a simple methodology to conduct preliminary seismic vulnerability assessment of bridge embankments to identify and prioritize embankments susceptible to failure. A ranking model that provides a priority list of embankments with the highest seismic risk of failure is generated. A step-by-step methodology is presented to estimate the seismic slope stability capacity–demand ratio, displacement, and liquefaction potential of the bridge embankments. Three categories are presented to identify the failure risk of the embankments. The ranking model is useful for a quick assessment of the sensitivity of the effect of various site conditions, earthquake magnitudes, and site geometry on possible movement of the designated embankments. The methodology is applied to identify the seismic risk of 127 bridge embankments along I-24 in western Kentucky. The variables of the embankments are the geometry, material, type, and properties of underneath soil and the elevation of both the natural ground line and the upper level of bedrock. A priority list of the embankments with the highest risk of seismic failure is generated for I-24 bridge embankments in western Kentucky during designated seismic events. The priority list will enable decision makers to decide on either carrying out further detailed evaluation or considering other appropriate actions for the bridge embankments with the highest risk of seismic failure.
Use of Mixed Revealed-Preference and Stated-Preference Models with Nonlinear Effects in Forecasting
Authors: Cherchi Elisabetta , Ortúzar Juan de Dios
Published: May 2018

Estimation of mixed revealed-preference (RP) and stated-preference (SP) data has become almost common practice. However, most attention has gone to estimation, with the correct use of these much-improved models in forecasting left in need of better understanding. In particular, their potentiality in accounting for nonlinear effect has not been fully explored, either in estimation or in prediction. The problem of using an RP-SP mixed model for accounting for nonlinear effects in the attributes in forecasting, especially when the nonlinearities have been specifically estimated only for the SP data, is addressed. By using a mixed RP-SP data set gathered especially for a modal choice context in Cagliari, Italy, several nested logit models with nonlinear systematic utility functions were estimated and used to provide empirical evidence on the effect of incorrect use of RP-SP specifications in forecasting under different policies. It was concluded that the partial data enrichment approach is well suited to treat nonlinearities and allows for consistent improvements in model estimation results. More important, nonlinearities might impose severe limitations in the applicability of these models in forecasting because of more restrictive microeconomic conditions. Failure to treat these problems correctly can lead to serious forecasting errors, even in the case of relatively mild policies.
Dynamics and Variability in Within-Day Mode Choice Decisions
Authors: Ramadurai Gitakrishnan , Srinivasan Karthik K.
Published: May 2018

This research investigated within-day dynamics and variations in mode choice within and across individuals at the activity-episode level. Specifically, dynamics and variability were examined at four levels: ( a) effect of variation over time of explanatory attributes such as episode–trip characteristics, ( b) influence of state-dependence (past choice decisions) on current choice, ( c) role of habit persistence (i.e., the influence of lagged explanatory variables), and ( d) the effect of unobserved preference heterogeneity that persists over repeated choices of individuals. A mixed-logit model was calibrated by using the rich activity-diary data from a 2000 activity-travel survey for the San Francisco Bay Area in California. Several alternative specifications of dynamics were tested. The aforementioned sources of variability and dynamics were found to be significant, and the empirical results showed a substantial improvement in model fit with the inclusion of these factors. The within-day dynamic model also outperformed alternative models in validation tests. The proposed model has important implications for improved activity-based demand models, travel demand forecasting, and evaluation of transportation control measures.
Endogeneity in Residential Location Choice Models
Authors: Guevara Cristian Angelo , Ben-Akiva Moshe
Published: May 2018

Empirical residential location choice models have occasionally reported estimated coefficients of dwelling-unit price that are small, statistically insignificant, or even positive. This would imply that households are insensitive to changes in dwelling-unit prices and taxes; this not only is counterintuitive but makes the models useless for policy analysis. One explanation for this result is price endogeneity, which means that the included dwelling unit's price variable is correlated with the model's error term. In discrete choice models this problem is caused principally by the omission of attributes correlated with price. An application of the control-function method is presented as the most suitable to correct for endogeneity in choice models of residential location. The method is tested for robustness to different error structures by using two Monte Carlo experiments, and it is also applied to real data from Santiago, Chile. The results show that price endogeneity is significant in choice models of residential location and that the control function method is suitable to account for it.
Bilevel Negotiation Protocol for Multiagent Simulation of Housing Transactions and Market Clearing Processes
Authors: Devisch Oswald , Arentze Theo , Borgers Aloys , Timmermans Harry
Published: May 2018

Models of residential choice behavior play a central role in integrated land use–transportation models. An agent-based model was developed of the negotiation process between selling and buying agents to represent price formation and clearance processes in housing markets. The model takes into account the heterogeneity of the goods traded, behavior protocols, imperfect knowledge, and strategic behavior of interacting households and real estate agents in price negotiations. A framework was developed, and the results of numerical experiments conducted to test the model are discussed.
Effects of Land Use Characteristics on Residence and Employment Location and Travel Behavior of Urban Adult Workers
Authors: Silva João de Abreu e , Golob Thomas F. , Goulias Konstadinos G.
Published: May 2018

The relationships between socioeconomic and demographic characteristics, land use characteristics around the residence and work locations, and a variety of travel behavior indicators are examined by using a structural equations model. This simultaneous equations system allows one to model the effects of land use characteristics on travel behavior while controlling for self-selection bias: certain types of persons choose to live and work in areas that suit their lifestyles and resources. In the model, travel behavior choices are multidimensional; total time away from home, trips and trip distances by three types of modes, car ownership, and possession of a transit pass are included. Land use is captured in geographic information system–based measures of land use and transport supply variables centered on both home and work locations. These measures are reduced to eight land use factors. The analysis provides strong evidence in favor of using land use and urban form designs and planning both around residential neighborhoods and workplace areas. Results provide quantitative evidence of the extent to which workers living in denser, central, compact, and mixed zones make more intense use of transit and non-motorized modes and tend to have lower car ownership levels. Workers in areas well served by freeways tend to make more intense use of their cars, although this does not inhibit use of transit. The results show that land use measures differ in their ability to explain different travel demands even when controlling for socioeconomic and demographic effects.
Infrastructure and Firm Dynamics
Authors: De Bok Michiel , Bliemer Michiel C. J.
Published: May 2018

Firm location is an important component in integrated land use and transport models. However, representation of firm behavior and firm locations is often too aggregated to model firm behavior adequately. A calibrated simulation approach that models dynamics in the firm population at the level of individual firms is presented. A number of firm demographic events and transitions in the state of individual firms are simulated: firm migration, growth, formation, and dissolution. This provides the opportunity to account for firm-specific behavior and allows a large variety in responses to changes in urban environment. The model quantifies the effects of different spatial and transport planning scenarios on firm population and mobility. Moreover, the firm-level simulation output provides improved possibilities to evaluate the impact of spatial scenarios. It can be linked to an urban transport model to obtain a dynamic simulation of urban development and mobility. The model specification is presented, as well as the calibration of the individual firm demographic processes. The behavior of the calibrated model is verified with multiple test runs.
Relationship between Transport Accessibility and Land Value
Authors: Du Hongbo , Mulley Corinne
Published: May 2018

In recent years, land value capture has attracted increasing attention because of its potential for funding transport infrastructure. It is well acknowledged that transport infrastructure can improve accessibility to employment and amenities; thus one might expect that it is the improved accessibility that adds value to land. Therefore, the issues in the relationship between transport accessibility and land value rise in connection with the concept of land value capture. A study looked at the relationship between transport accessibility and land value with the implication of a local model, geographically weighted regression (GWR). Traditional techniques, such as hedonic models, used to understand the attributes of land value, are global models that could be misleading in examining the spatially varying relationships, such as transport accessibility and land value. By using the Tyne and Wear region in the United Kingdom as a case study, the study revealed that nonstationarity existing in the relationship between transport accessibility and land value indicates that transport accessibility may have a positive effect on land value in some areas but a negative or no effect in others; this suggests that a uniform land value capture would be inappropriate. The use of GWR allows such spatially varying relationships to be revealed, leading to a better understanding of the factors determining positive land value uplift and the implications of spatially dependent transport access premiums in housing values in the context of value capture policies.
Employer Expectations for Commuting and Business-Related Travel in an Environment Rich in Information and Communication Technologies
Authors: Bonsall Peter , Shires Jeremy
Published: May 2018

The collection and the analysis of data on working from home (teleworking) and on the use of information and communication technologies (ICT) to substitute for business travel are described, and conclusions are drawn. Data were collected from senior management by using a web-based questionnaire incorporating several innovative features; in addition to data on current and expected levels of home-working and business travel in a range of ICT scenarios, data were collected on the respondent's perception of the impact of different factors on future levels of these activities. Also, to test the robustness of respondent opinions, the impact of alternative versions of a briefing text–-one positive and one negative about the role of ICT–-on respondent expectations was evaluated. Analysis revealed that a number of factors that are often ignored or taken as constant would be influential in the future levels of home-working and business travel. Generally, issues of cost appeared to be much less influential than the speed and security of communications. Assumptions about future travel conditions were seen to have considerable influence on expected levels of home-working and business travel. Respondent opinions about home-working were found to be more robust than those relating to business travel. Models were specified and calibrated on respondent expectations. Predictions by these models appear reasonable and in line with recently published trends. The work was conducted within the European Union–funded POET (Prediction of E-Economy Impacts on Transport) project and provided models that were used to inform predictions of travel demand in European city regions in a hypothesized ICT-rich future.
Evaluation of Flow-Based Traffic Signal Control Using Advanced Detection Concepts
Authors: Smaglik Edward J. , Bullock Darcy M. , Urbanik Thomas , Bryant Dan
Published: May 2018

State-of-the-practice signal timing techniques used at isolated actuated controlled intersections can result in suboptimal operation. This paper proposes a new tactical control algorithm that integrates real-time stop bar presence detection with real-time flow rate information to identify a downstream flow restriction. If a flow restriction is identified, a phase with a constant call could be terminated earlier than its specified maximum or split time. This algorithm was validated with real-time data to predict downstream bottleneck conditions and then by viewing the archived video for confirmation of the condition. The algorithm was applied during a 504-h period of signal operation. During this period, the algorithm identified 76 bottlenecks. Overall, 75.0% of these events were visually confirmed. Algorithm failures were caused by a variety of conditions such as large trucks, inattentive drivers, and detector errors.
Traffic Signal Phase Truncation in Event of Traffic Flow Restriction
Authors: Beaird Scott , Urbanik Thomas , Bullock Darcy M.
Published: May 2018

This paper proposes an improvement to traffic signal controller logic. The concept consists of truncating a phase on which there is demand but with zero or minimal flow owing to a restriction of traffic. Flow restrictions occur for a variety of reasons including queue spillback, stalled vehicles, and railroad blockages. The logic presented in this paper recognizes such a flow restriction and, consequently, terminates the phase in favor of a conflicting call for service. The theory of the concept is addressed, and methods of implementation are explored. Although this research focuses on phase truncation, terminating a phase may not always be the most strategic decision; other priorities can override tactical detection of minimal flow. Therefore, this research considers the feasibility and potential benefit of including phase truncation logic as one component of a more intelligent and strategic controller algorithm. A limited experimental analysis was conducted to qualify the benefit of the phase truncation concept. This analysis was conducted with VISSIM simulation software in conjunction with a hardware-in-the-loop configuration. On the basis of the results of this analysis, which was limited in scope, it was concluded that the phase truncation concept could result in reduced vehicle delay under at least one traffic scenario.
Practical Procedure to Collect Arterial Travel Time Data Using GPS-Instrumented Test Vehicles
Authors: Hunter Michael P. , Kook Wu Seung , Kyoung Kim Hoe
Published: May 2018

Arterial streets are interrupted flow facilities that balance two purposes: serving through trips and providing commercial and residential access to adjacent land. A dominant factor in urban arterial street operations is the presence of traffic signals, which govern the flow of vehicles entering and exiting an arterial segment. Consequently, the performance of an arterial street is predominately influenced by delays incurred at traffic signals, with measures of effectiveness primarily a function of the performance at the arterial segment level. This paper presents a practical procedure to collect and analyze travel time data, based on Global Positioning Systems (GPS), that readily reflect measures of performance for both segments and extended arterial sections. Underlying this procedure is an assumption that both average travel speed and average intersection approach delay can be calculated as a function of arterial segment travel time, resulting in travel time as a primary field measurement used for gauging arterial performance. Procedures developed include both field data collection techniques that center on GPS technologies and algorithms for processing the gathered GPS-based travel time data.
Decision Model for Priority Control of Traffic Signals
Authors: Head Larry , Gettman Douglas , Wei Zhiping
Published: May 2018

This paper presents a model of the core logic of a traffic signal controller. The model is formulated on the basis of the traditional North American ring, phase, and barrier construct and includes phase intervals such as minimum and maximum times, pedestrian service, alternative minimum times, and a priority service extension. The mathematical model is based on precedence graphs that are familiar to engineers involved with project management techniques such as Gantt charts, the critical path method, and the program evaluation and review technique. The model presents an analytical framework for the analysis of complex controller behaviors and is demonstrated for the case of multiple priority requests. An example shows that a first-come, first-served policy for serving priority requests can result in more delay than will a multiple-priority-request policy generated by the model developed in this paper. Additional controller behaviors, such as preemption, coordination, and offset transition, can be analyzed with this model.
Design Structure Matrices to Improve Decentralized Urban Transportation Systems
Authors: Dunn Travis P. , Sussman Joseph M.
Published: May 2018

Managing large, complex urban transportation systems involves numerous stakeholders because of decentralized ownership and operation of distinct pieces of the physical network and services. To deliver better service to users, many urban regions are adopting technological and operational solutions, both of which necessitate interaction among the decentralized organizations. This research applies systems engineering analysis techniques—design structure matrix and clustering—to improve efficiency and effectiveness of organizational interactions between agencies as they deploy intelligent transportation systems (ITS) and attempt to integrate their operations. Specifically, this paper examines the application of clustering to the institutional structure set forth by the regional ITS architecture for metropolitan Seattle, Washington. Clustering of Seattle area organizations noted previously unidentified multilateral relationships that offer potential for more efficient interagency interactions and, ultimately by extension, delivery of more effective transportation services to users.
Weather Integration in Transportation Management Centers
Authors: Cluett Chris , Kitchener Fred M. , Osborne Leon , Conger Steve
Published: May 2018

Traffic management centers (TMCs) serve to integrate technologies, agencies, and information to improve the safety and efficiency of transportation and transit systems. The thesis of this paper is that the integration of weather systems and information into transportation operations, specifically in TMCs, will improve operational performance and offer travelers increased mobility and safety benefits. The findings that are presented are based on a study of integrated operations at 38 TMCs across the country and reflect a range of weather experience, size and type of transportation system, and integration concepts and strategies. The paper offers a conceptual framework for understanding weather integration in traffic operations. The framework identifies a set of determinants of integration that are linked to operational performance and illustrates five key dimensions of integration. Field research showed how TMCs differ on these dimensions and the integration strategies they employ to achieve their desired concept of integration. The state of the practice in weather integration is described, and future opportunities that build on today's best practices in TMCs are identified. A number of benefits to be derived from enhanced weather integration in TMCs are presented. The paper concludes that to achieve effective and efficient weather integration in traffic operations, it will be necessary to change existing operational paradigms and modify present TMC cultures. Many concepts of integration are exemplified in the best practices in use today, and they form the foundation on which to build integrated transportation operations for tomorrow.
Activation Energy of Alkali–Silica Reaction and Dilatometer Method
Authors: Mukhopadhyay Anal K. , Shon Chang-Seon , Zollinger Dan G.
Published: May 2018

Alkali–silica reaction (ASR) continues to be a detriment to the long-term performance of concrete. Certain initial conditions related to material alkalinity, aggregate reactivity, humidity, and temperature conditions are known to initiate ASR. A key factor in the prediction of ASR in concrete over time is the reactivity of the aggregate, but current test methodology is largely simulative in nature and yields mainly empirical results that apply to only a narrow band of conditions, and leave many questions as to whether these methods have any relevance to concrete performance under field conditions. Improvement can be found by using a performance-based approach that can address the ASR potential of concrete at levels of alkali, temperature, and moisture that are realistic and representative of actual field conditions. In the present study, the concept of ASR-related activation energy is introduced as a representative single parameter of the ASR. An attempt has been made to introduce the dilatometer test method as a part of a performance-based testing protocol for predicting potential ASR aggregate reactivity in terms of activation energy. It is observed that this new test method can categorize minerals and aggregates based on their reactivity within a short period. The use of the activation energy provides a unique parameter for evaluating ASR susceptibility of minerals and aggregates.
Hindsight Judgment of Driver Fault in Traffic Accident Analysis
Authors: Dilich Michael , Kopernik Dror , Goebelbecker John
Published: May 2018

A warning is raised about how the science of traffic accident reconstruction is naively misused by inviting and exacerbating “hindsight bias” when the reasonableness of a driver's unsuccessful attempt to avoid an accident is judged. “Those who know how things turned out have trouble believing others didn't see what was coming.” In highway safety research, where a reliable understanding of the causes of accidents is prerequisite to developing safer roads, hindsight compromises the validity of research results. In the legal arena, where the stakes are high in judgments of fault, hindsight will bias judgments against drivers involved in accidents, especially when there are serious injuries. Researched by cognitive psychologists since the early 1970s, hindsight bias is reviewed within the context of causal analysis and attribution of fault for the typical accident that arises when one driver suddenly interferes with the path of another, demanding evasive action. An example accident reconstruction is presented to demonstrate how science that helps to explain how an accident happened inherently provides an after-the-fact reference for precisely how the reactive driver should not have responded and how she or he could have done better. The typical reconstruction diagram is dubbed a hindsight diagram to emphasize how such graphic designs can bias judgment by illustrating conclusive facts about an accident that did not exist just seconds before, at the time the reactive driver had to respond. Although debiasing techniques, including the concept of a foresight diagram, are discussed, hindsight bias remains a major factor in accident analysis.
Analysis of New Starts Project by Using Tour-Based Model of San Francisco, California
Authors: Freedman Joel , Castiglione Joe , Charlton Billy
Published: May 2018

Activity-based models are increasingly attractive as alternatives to traditional trip-based travel demand forecasting models because of growing dissatisfaction with the internal consistency, aggregation bias, and lack of detail of trip-based approaches. New policy analysis requirements demand that forecasting models represent travel choices and the contexts in which these travel choices are made with ever-increasing geographic, temporal, and behavioral detail. Activity-based models can incorporate this detail and can provide decision makers with more precise insights into potential outcomes of transportation and land use investment and development strategies. The model of San Francisco, California, is a tour-based microsimulation model that forecasts daily activity patterns for individual San Francisco residents and has been used in transportation planning practice since 2000. The San Francisco model uses the daily activity pattern approach, first introduced by Bowman and Ben-Akiva, within a disaggregate microsimulation framework. This paper describes an application of the San Francisco model to the proposed new Central Subway project in downtown San Francisco. This is the first application of an activity-based travel demand model in the United States to a major infrastructure project in support of a submission to FTA for project funding through the New Starts program. To enable the submittal of a New Starts request, software was developed to collapse the microsimulation output of the tour and trip mode choice models into a format compatible with the FTA SUMMIT program. SUMMIT was then successfully used to summarize and analyze user benefits accruing to the project and to prepare an acceptable New Starts submittal.
Modeling Time-of-Day Choice in Context of Tour- and Activity-Based Models
Authors: Zeid Maya Abou , Rossi Thomas F. , Gardner Brian
Published: May 2018

Understanding the variations in travel by time of day is essential to predicting transportation system performance and air quality impacts of the transportation sector. As tour- and activity-based modeling procedures become more commonplace, the need for accurate time-of-day modeling procedures that are sensitive to changes in policies or travel conditions, such as congestion, that affect time-of-day choices, is clear. FHWA recently conducted a research project to develop new methods of modeling travel by time of day that are sensitive to these concerns. One of the products of this project is a time-of-day choice modeling procedure designed to be applied within tour- or activity-based travel modeling processes. This procedure was designed to be compatible with most existing tour- and activity-based models in the United States. The time-of-day choice model is estimated by using household activity survey data and transportation level-of-service information from the highway network. This procedure was tested by using the activity-based travel model for San Francisco County, California. The time-of-day modeling procedure is described, including the model estimation process, data requirements for estimation and application, and the results of the San Francisco test application. The test application included alternative scenarios designed to validate the model's sensitivity to land use, transit level of service, traffic congestion, and time-of-day pricing.
Consensus Building in Transportation Planning Practice
Authors: Chaves Ernesto , Garcia Esmeralda , Gilmore Susan
Published: May 2018

Resolving conflicts in major transportation corridors remains a challenge. Many times the need to increase access has led to seemingly insurmountable divisions between stakeholders representing widely divergent interests. The case evaluated here, the I-710 corridor in Los Angeles, addresses a unique situation: the transportation planning process was redirected midcourse in response to the public's negative reaction toward the first set of transportation alternatives. An adaptive public participation process more aligned to the complex political and social realities of the I-710 corridor was introduced to replace a more traditional process that had not achieved the needed consensus. Transportation planners initiated a new series of consensus-building efforts with the objective of generating strategies and alternatives that would be acceptable to the affected communities while meeting the purpose and need for mobility improvements in the corridor. The consensus subsequently reached through the more adaptive process helped to reprioritize and bring out latent problems in the study area. Previously, either these problems had not been identified or their importance had been underestimated. Through the process of clearly identifying the problems and potential solutions, participants were able to come to consensus on an alternative set of strategies. By helping to clarify the public debate, this process strengthened the overall transportation planning effort.
Selection and Scheduling of Interdependent Transportation Projects with Island Models
Authors: Tao Xianding , Schonfeld Paul
Published: May 2018

One major issue in solving the problem of selecting and scheduling interdependent transportation projects is the complex interdependence between projects that makes it difficult to evaluate the effects of individual projects or sets of projects. Previous researchers have developed mathematical models that capture some benefit and cost interactions among projects. Such models usually can handle some simple cases in which only pairwise interactions between projects exist, but they may not be realistic enough to capture the complex project interdependence for general transportation networks. Other issues arise in developing the algorithms to optimize the selection and scheduling of projects under resource constraints. For real applications, the developed algorithms should be effective and efficient in solving the problems for sizable transportation networks. To deal with these issues, this paper develops island models, which are variations of traditional genetic algorithms, for optimizing project selection and scheduling under resource constraints, while relying on a simulation model or an equilibrium traffic assignment model to evaluate the transportation project impacts. As a test case, a highway network is analyzed with equilibrium traffic assignment to evaluate the impacts of different combinations of transportation projects. The study investigates the island models with different domain partitioning and solution migration methods. The results show an island model generally can achieve better solutions than a traditional genetic algorithm.
Access Management Plan and Program for Des Moines, Iowa, Metropolitan Area
Authors: Plazak David , Garms Adam , Rees Jon
Published: May 2018

According to the Iowa Department of Transportation's crash database (GIS-ALAS), between 5% and 10% of all crashes in Iowa occur at commercial driveways. Most of these occur at arterials within municipalities. In recent years, nearly one-quarter of these crashes occurred in the Des Moines metropolitan area, making the area a prime candidate for improved access management. Case study research in Iowa has shown that access management is an effective highway safety tool: well-managed routes can be 40% to 50% safer than poorly managed routes. The Des Moines metropolitan area has many miles of older arterials that were constructed before access management was considered. This paper describes a cooperative effort of the Des Moines Area Metropolitan Planning Organization and the Center for Transportation Research and Education at Iowa State University to develop an access management study and program for the Des Moines metro area. The overall goal of the study is to use the knowledge developed to make improvements that will reduce access-related crashes. This project will also help local officials better consider access to avoid future safety and operational problems. The major task described in this paper was to identify and rank the Des Moines metro area's access management problems by using Iowa's GIS-ALAS database and other geospatial data. This process was developed to identify arterial segments in the metro area most promising for further investigation with regard to access management.
Development of an Intersection Prioritization Tool for Accessible Pedestrian Signal Installation
Authors: Carter Daniel L. , Harkey David L. , Barlow Janet M. , Bentzen Billie Louise
Published: May 2018

Although increased complexity in intersection design and signal timing has improved intersection service to vehicle traffic, it has created additional challenges to pedestrians who are blind or who have low vision. Safe and independent crossings for pedestrians who are blind or who have low vision may require installation of accessible pedestrian signals (APSs) at some complex signalized intersections. APSs provide an audible and sometimes a tactile indication when the walk signal is on to cross the street. The goal of this study was to create a tool to prioritize locations for the installation of APS. To develop the prioritization tool, various characteristics of the intersection and the individual crosswalk were assigned point values that indicated their relative effect on the need for an APS at the crosswalk. For example, a point is assigned if the crossing is interrupted by a median; two points are assigned if there is a channelized turn lane. Field tests were conducted in which sites were ranked in order of their need for APS. The rankings were done separately by transportation engineers using the prioritization tool and by expert judgment of orientation and mobility specialists and pedestrians with visual impairments. The point values of the prioritization tool were modified on the basis of the expert judgment rankings. The final calibrated tool provides practitioners with the means to take observable characteristics of a pedestrian crossing and produce a score that reflects the relative crossing difficulty for pedestrians who are blind, thus enabling prioritization of APS installations.
Recommended Walking Speeds for Timing of Pedestrian Clearance Intervals Based on Characteristics of the Pedestrian Population
Authors: Gates Tim J. , Noyce David A. , Bill Andrea R. , Van Ee Nathanael
Published: May 2018

Data from 1,947 pedestrian crossing events measured at 11 intersections in Madison and Milwaukee, Wisconsin, were analyzed to determine the effect of subject age and disability, intersection traffic control condition, group size, and sex on walking speed. A multifactor analysis of variance indicated that pedestrian walking speed depended on age and disability, traffic control condition, and group size. Pedestrians older than 65 ( n = 326) were the slowest of all age groups, with mean and 15th percentile walking speeds of 3.81 and 3.02 ft/s, respectively, and typically would not be accommodated by pedestrian clearance intervals based on the commonly used 4.0-ft/s walking speed. Adult-assisted children and physically disabled persons had crossing speeds similar to those of persons older than 65. Groups of pedestrians crossed 0.4 to 0.6 ft/s slower than individuals. On the basis of data reported here, a 3.8-ft/s walking speed is recommended for timing pedestrian clearance intervals (flashing don't walk indication) at locations with normal pedestrian demo-graphics (downtown areas, shopping areas, most neighborhoods, school areas) and locations where the age or physical disability status of the pedestrian population is unknown. When the proportion of pedestrians over the age of 65 is equal to or exceeds 20%, 30%, 40%, 50%, and 100% of the total pedestrians at a location, walking speeds of 3.6, 3.5, 3.4, 3.3, and 2.9 ft/s, respectively, are recommended for pedestrian clearance timings. Walking speeds of 4.0 ft/s are appropriate only for locations with very few older pedestrians, assisted children, and disabled persons, such as college campuses.
Avoiding Biased Interpretation of Bicycle Surveys
Authors: Schneider Robert J. , Dunbar Lakesha C. , Toole Jennifer L. , Flink Charles
Published: May 2018

Surveys are a common technique used by transportation agencies to gather information about the socioeconomic characteristics, behavior, and preferences of the traveling public. The purpose of this paper is to help agencies and researchers understand differences in bicycle survey results when different distribution techniques are used. This study analyzes a bicycle survey that was implemented by the City of Winston-Salem, North Carolina, in early 2005. The city distributed identical survey questions in four different ways. Comparative statistics are used to show that there were significant differences in responses according to survey distribution method. Using four different methods of survey distribution allowed the City of Winston-Salem to gather feedback from a greater variety of citizens than is possible with a single survey method, target several key constituencies (people with significant interest in bicycle issues, bicyclists with less experience, and potential bicyclists), and understand potential differences in the responses to certain survey questions based on the survey method used. Practitioners can use the results of this study to help select survey distribution methods that will gather the most credible and useful data for meeting their objectives. It will also help agencies draw more informed conclusions from bicycle survey results.