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Fine grid management is one of the important development directions of transportation planning that has not been fully considered in previous literature. This paper explores the application of the fine grid management method in transportation planning. Based on a case study of Chuanhui, China, this paper proposes a data-driven fine grid partitioning method for determining traffic analysis zones (TAZs). The TAZs are partitioned based on quadrilateral and hexagonal grids. This paper also summarizes a set of criteria for evaluating the impact of different fine grid partitioning methods based on the geographically and temporally weighted regression (GTWR) model. The results show that our fine grid partitioning method for determining TAZs based on quadrilateral grids can achieve a relatively low level of predicted value bias and variable correlation degree bias when the number of TAZs is larger, and it has obvious advantages. Finally, policy implications are proposed to promote the refinement of transportation planning. [ABSTRACT FROM AUTHOR]

The article discusses the goal in publishing papers is to make useful contributions to the state of knowledge and practice in transportation engineering. It mentions that the papers receiving at least one award-quality designation in the review process are considered; winners generally have multiple award-quality designations; and the role of the referees in selecting the best papers as well as in enhancing the quality of the journal is absolutely critical.

The article offers information on goal in publishing papers is to make useful contributions to the state of knowledge and practice for transportation engineering. Topics include the papers receiving at least one award quality designation in the review process are considered like winners generally have multiple award quality designations, and the role of the referees in selecting the best papers as well as in enhancing the quality of the Journal is absolutely critical.

Quality control (QC) is an essential component of quality assurance (QA) programs used to monitor and ensure the highway construction projects' quality. After receiving the contractor's QC plan, state departments of transportation (DOTs) conduct review and acceptance, monitor the QC process, and ensure construction quality by performing inspection activities. Given that state DOTs are increasingly implementing alternative contracting methods (ACMs), including construction manager/general contractor (CM/GC), design-build (D-B), and public–private partnerships (P3), it is essential to consider the impact of shifting more responsibility to the contractor on quality management activities, including developing and monitoring QC plans throughout the project development. The objective of this paper was to investigate the implementation of QC plans for administering QA specifications in highway infrastructure projects delivered using ACMs. The data collected from a national survey questionnaire of 43 DOTs in the US and structured interviews with seven DOT representatives were employed to investigate this research's objective. As a result, eight typical requirements of QC plans in ACM projects were identified in terms of certification and qualification of QC personnel and process control. Additionally, the standard of care of QC staff in ACMs was not found to be higher than that in design-bid-build. Nine risk factors related to the oversight of QC plans in D-B, CM/GC, and P3 highway projects were identified. There was no statistical difference in the nine risk scores among D-B, CM/GC, and P3 projects. The findings from seven case studies provide insights regarding the implementation of QC plans for ACM highway projects. This study contributes to the body of knowledge by advancing the understanding of how state agencies execute and oversee QC activities in ACM projects. The outcomes of this study may help state DOTs identify optimal QC practices to administer the QA process in ACM projects. This study investigates the current state of practice in implementing QC plans to manage and improve QA processes for highway projects delivered using ACMs such as CM/GC, D-B, and P3. This study synthesized and documented typical QC requirements used by state DOTs in reviewing, accepting, and monitoring contractor compliance with their QC plans. Additionally, the descriptive and inferential testing results of nine risk factors in implementing QC plans in highway projects found in this study enable highway agencies to effectively justify their monitoring process of the QC plan implementation. Further, the results from seven case studies provide insights and key lessons learned regarding (1) the guidance and templates for developing a QC plan; and (2) risk perceptions in managing the QC plan implementation in ACM highway projects that can benefit both the contractors and state DOTs. The outcomes of this study also shed light on exploring the optimal allocation of responsibilities between state DOTs and contractors in implementing QC activities to administer QA programs in ACM highway projects. [ABSTRACT FROM AUTHOR]

With the rapid development of global industrialization, the consumption of refined oil is at a high level. The scale of refined oil transportation is huge. For refined oil sales enterprises, determining a method for making reasonable transportation plans and reducing transportation cost has become an important means to improve competitiveness. The current method of developing a primary logistics plan does not consider the characteristics of various transportation modes, which can lead to an increase in overall costs. The logistics system in this case has multiple transportation modes, including road, rail, and pipeline. In addition, a multiproduct pipeline has multiple injection points. For such a complex system, this work unifies the time dimension of continuous transportation by pipeline and discrete transportation by rail and road based on the idea of multimodal transportation. This paper couples a pipeline scheduling submodel and a logistics optimization submodel to construct a daily scheduling model for refined oil which is close to the actual operation in the field. This model was validated using a refined oil logistics system in China, and the results show that the optimized logistics solution decreased total transportation costs by 14.5% compared with the actual cost. This model can serve as a guide for actual operations. [ABSTRACT FROM AUTHOR]

Connected vehicle (CV) data in this paper refer to the in-vehicle telematic data, including trajectories and driving events (e.g., hard braking) collected by vehicle manufacturers when vehicles are moving. Recently manufactured vehicles are equipped with cellular modems and Internet of Things (IoT) devices to collect vehicle data. Such data, after removing personal information, are being redistributed to third-party organizations. Compared to other probe vehicle data, the CV data has a higher penetration rate, ubiquitous coverage, and almost lane-level positioning accuracy. These features pave the road for novel transportation applications in transportation planning and traffic operations. In this paper, we represent a novel framework to estimate the regional link volumes based on the CV data and a deep neural network (DNN) model. The training data are generated according to the link volumes (targeted model output) and the corresponding CV counts (input features) at the same locations. The DNN model's performance was compared with other estimation methods like linear regression and random forest and showed superior performance. The trained DNN model takes ubiquitous CV counts from other locations to estimate the corresponding link volumes. As a case study, the proposed DNN model was trained with a large training data set derived from CV data and time-dependent link counts collected at over 1,200 locations on freeways in the Dallas FortWorth, Texas, area. The results reveal good accuracy and robustness. [ABSTRACT FROM AUTHOR]

Uncertainty quantification is important for making reliable decisions in transportation planning and operations. In the field of short-term traffic condition forecasting, uncertainty quantification methods include primarily distribution-based approaches and nondistributionbased approaches. For the former, the generalized autoregressive conditional heteroscedasticity (GARCH) model has been widely applied to model and quantify traffic condition uncertainty in terms of prediction interval under normality assumption. However, this normality assumption has not been systematically investigated yet. Therefore, this paper attempts to investigate this normality assumption and thereby quantify traffic condition uncertainty, using a method with steps of residual calculation and investigation, normality investigation, distribution estimation, uncertainty quantification, and performance measurement. Using real-world traffic flow data, the distributions of the selected samples are shown to be nonnormal using the Kolmogorov-Smirnov test and normal probability plot. Distribution estimation using nonnormal models shows that the t location-scale distribution and generalized error distribution (GED) can be used to model traffic condition uncertainty. Uncertainty quantification using GARCH under these nonnormal distributions further show that nonnormal models outperform the normal model, with the GARCH model under t location-scale distribution yielding the best performance. Future studies are recommended to promote the investigation into traffic condition uncertainty quantification and application. [ABSTRACT FROM AUTHOR]

In this paper, the authors present their efforts in exploring a new type of traffic data, referred to as internet-connected vehicle (ICV) data, for traffic congestion management and operational planning. Most currently manufactured vehicles contain onboard GPS and cellular modules, and they constantly connect to automobile manufacturers' clouds via cellular networks and upload their status. Some automobile manufacturers have recently redistributed the nonpersonal part of such data, such as geolocation, to third-party organizations for innovative applications. Compared with the traditional vehicle GPS data, the ICV data contain high-resolution GPS waypoints accompanied with the vehicles' abnormal moving events (e.g., hard braking). The ICV data also have huge potential in congestion management and operational planning. They explore to identify and analyze traffic congestion on both freeways and arterials using the ICV data. The ICV data adopted for this research are redistributed by Wejo Data Service, representing 10%–15% of all moving vehicles in the Dallas–Fort Worth (DFW) area in Texas. Through one case study for a freeway segment and one for an arterial segment, new traffic performance metrics based on the characteristics of ICV data have been presented. The highlights of these efforts are as follows: (I) queue length and propagation at freeway bottlenecks can be directly measured based on where and when most internet-connected vehicles slow down and join the queue; (II) an internet-connected vehicle's actual delay time on arterials can be directly measured according to its slow movement percentage, without assuming the nondelay travel speed; and (III) the ICV data set are also combined with the high-resolution traffic signal events to generate a ground-truth time-space diagram (TSD) on arterials—a common visualization of arterial signal performance for transportation planning and operations. [ABSTRACT FROM AUTHOR]

The demand for healthcare facilities in the world is growing daily, and this growth in demand exceeds general population growth. This situation has made hospital trips a vital issue during urban transportation planning. In this context, the aim of this study is twofold: (1) to investigate the hospital trip behavior as home-based hospital trips within the scope of trip production and attraction (trip generation) models and (2) to evaluate the predictive power of some robust and regularization methods in trip generation modeling. Within this scope, approximately 49,000 valid Household Survey Data (HSD) from 2001 (base year) and 2015 (target year) were used to develop comprehensive trip generation models for the home-based hospital trips. Multiple linear regression (MLR), ridge regression (RR), Liu, least trimmed squares (LTS), least trimmed squares–ridge (LTS–R), and least trimmed square–Liu (LTS–L) methods were used for the analysis, and results were evaluated in terms of specialized mean squared error (MSE) and root mean square error (RMSE). As a result, LTS–R and LTS–L increased future predictive power by approximately 55% compared with OLS. This study fills an important gap in the literature in terms of not only the use of regularization and robust methods in trip demand modeling but also examining characteristics that affect hospital trip behaviors. In addition, the paper proposes a "Hospital Mobility Coefficient" projection that could be useful in demand estimation for future hospital trips. [ABSTRACT FROM AUTHOR]

Traditionally, urban land use planning belongs to urban planning and transportation infrastructure construction belongs to transportation planning. However, it is widely recognized that the integrated optimization of urban and transportation planning is the development trend in the future. This paper will develop a methodology to model the integrated transportation and land use planning problem that will consider the stochastic characteristic of link capacity and travel demand. The integrated planning problem will be formulated as a bilevel programming model. In this programming, the upper-level decision makers are urban planners and transportation engineers that aim to maximize network performance by making integrated planning schemes. Specifically, the planners should determine how to allocate limited resources between the development of residential and working locations, and improvement of the traffic network. The lower-level decision maker is the heterogenous traveler that makes residential and working location decisions, and the choice of travel path. The land use pattern is indicated by the spatial distribution of residential and working locations. Finally, the particle swarm optimization (PSO) algorithm will be used to solve the bilevel model. A set of numerical experiments will be carried out to illustrate the application of this model. [ABSTRACT FROM AUTHOR]

A call for papers for the special issue on the challenges in transportation planning for cities in Asia is presented.

This paper aims to evaluate the accessibility of multimode transport facilities to suburban tourist attractions, under the background of detailed needs of tour transportation planning and urban development. Accessible, convenient, and sustainable tour transportation network is the prerequisite for tourists entering tourist attractions and completing activities. Based on multisource data and the GIS network analysis method, an accessibility model of suburban tourist attractions at community scale was constructed combining population with average shortest travel distances (ASTD) or the average minimum travel time (AMTT) by auto, public transport, and bike. Taking Beijing as an empirical analysis, the main conclusions are as follows. (1) The spatial distribution of suburban tourist attractions is fan-shaped with tourism resources mainly gathering on the north, west, and south of Beijing. (2) The ASTDs of tourist attractions and communities are 73.11 and 69.40 km, respectively. The average nonlinearity coefficient of ASTD of tourist attractions is divided into three categories including high, medium and low convenience, accounting for 0%, 78.57%, and 21.43%, respectively. (3) The accessibility of suburban tourist attractions has obvious spatial difference under multimode traffic network, showing an attenuation phenomenon of diffusion from the city center to suburbs. A total of 98.21% of them can be reached within 2 h by auto, while that number drops to 37.50% by public transport, and 32.14% by bike. The proposed model applicable for the accessibility of suburban tourist attractions provides reference for in-depth description and optimization of the actual traffic accessibility, as well as tourism transportation planning within the city region. [ABSTRACT FROM AUTHOR]

Owing to recent advances in information communication technologies, trail data, i.e., movement logs of people on the road or on trains, can be acquired on a 24-h, 365-day basis, some of which have yielded real-world applications. Generating highly granular origin-destination trip data from the operational data of mobile networks would significantly advance the methodology for actualizing and broadening the field of applications in urban transportation planning. This paper proposes a method that estimates origin-destination trips on the basis of mobile network operational data, referred to as mobile spatial dynamics. Statistics are generated using a three-step process comprising anonymization, estimation, and disclosure limitation. Unlike other studies conducted thus far, this study uses large-scale person trip survey data to validate the reliability of estimated origin-destination trips between regions. Analysis of the use cases shows that the proposed method has the potential for mobile spatial dynamics to complement person trip surveys and road traffic censuses. [ABSTRACT FROM AUTHOR]

Although transportation practitioners nowadays have an unprecedented level of access to information, substantial gaps still exist in their ability to efficiently and reliably find the right information, at the right time, for the task or decision at hand. To address this gap, this paper proposes a context-aware information retrieval (IR) approach that can capture and exploit the conceptualization of user needs, decision context, and content meanings in order to support the retrieval of information that is more relevant to decision making. The proposed IR approach includes three primary components: semantic annotation (SA), semantic query processing (SQP), and semantic document ranking (SDR). This paper focuses on SA for IR for supporting the transportation project environmental review (TPER) decision-making process. It proposes an epistemology-based SA algorithm for automatically annotating Web pages in the TPER domain with contextual concepts from an epistemological model. The TPER epistemology is a semantic model for representing and reasoning about information and IR in the TPER domain. In developing the proposed algorithm, a number of shallow and deep SA algorithms were developed and tested. For the shallow SA algorithms, the effects of syntactic expansion and filtering were investigated. For the deep SA algorithms, different semantic similarity (SS) calculation methods were evaluated. All the algorithms were tested on a data set of 1,328 Web pages, which were collected from the Federal Highway Administration (FHWA) Environmental Review Toolkit Web site, and they were evaluated in terms of mean precision (MP) and mean average precision (MAP). The final, proposed SA algorithm achieved over 91% MP and over 86% MAP at the top 10, 20, 30, 40, and 50 documents on the testing data. [ABSTRACT FROM AUTHOR]

The 2012 transportation bill, Moving Ahead for Progress in the 21st Century, formalizes the application of risk management in transportation asset management decision making. The bill requires departments of transportation to have a formal risk management plan for the national highway system. When carried out successfully, risk planning can be a very powerful framework to effectively and efficiently manage transportation infrastructure. However, if there is lack of experience with and insight into risk planning, it can go wrong, leading to a counterproductive plan that contributes to ineffectiveness and inefficiencies in the organization and transportation system and to wasted resources. This paper reviews a broad spectrum of literature on risk methods and applications to identify and discuss some common pitfalls-failure to communicate, failure to monitor, proportionality, failure to involve knowledgeable individuals. It synthesizes the results for purposeful use in transportation asset management decision making. The literature review indicates that pitfalls are pervasive and usually familiar to the new generation of industries adopting the principles of risk in their management practices. Accordingly, the paper recommends that decision makers and analysts become more familiar with these pitfalls before embarking on risk implementation programs. [ABSTRACT FROM AUTHOR]

The field of transportation engineering has become more sustainable as challenges of the twenty-first century continue. Sustainable mobility topics such as pedestrian and cycling travel, smart growth development, and transit-oriented design are being adopted and implemented. As a result, there is the need for higher-education curriculum on transportation engineering to adapt as well. Efforts to integrate sustainable and multimodal design into introductory transportation courses have emerged, as well as new courses in the transportation field. This paper describes the development and implementation of an upper-level course, Sustainable Transportation Planning, at Bucknell University. Course objectives, pedagogical tools, activities, and assessment methods are discussed in depth to provide insight into how other institutions can adopt a similar course. An emphasis is placed on active learning techniques and the need to balance the three components of sustainability (environment, economy, and society) into the course material. Courses such as this can expose students to transportation planning challenges and inspire them to pursue careers in sustainable transportation. [ABSTRACT FROM AUTHOR]

The operational functionality of the nation's transportation network determines how efficiently the network moves goods and people from where they are to their destinations. The nation has needs for far more highways that it can afford to build. Currently, highway maintenance, including corrective maintenance and reconstruction, consumes most of the budget in many states. With the shortage of funds for adding capacity and new routes, it has become extremely important to preserve the functionality of existing highways at a high level through effective planning, operational and safety management, and proactive infrastructure maintenance. It is imperative that functionality is considered in all stages of a highway's lifecycle and that functionality is protected, preserved, and where possible enhanced during the course of planning, operations, and maintenance. Recognizing that importance, the Texas DOT initiated a comprehensive research project to examine what losses to state highway functionality occur over time, the causes of those functionality reductions, and actions that can be taken to preserve, recover, and enhance functionality over time. This paper presents the findings of the research relevant to planning. The paper also presents two in-depth case studies through which the writers investigated in detail how the functionality of two major highways evolved. The products of the associated research and findings presented in this paper serve as valuable guidelines for state and local transportation agencies to select a proactive approach to preserve and enhance the functionality of the transportation system. [ABSTRACT FROM AUTHOR]

Sustainability assessment in transportation planning and selection of the best transportation mode among alternatives is a challenging process. The technological differences among conventional, hybrid, and alternative fuel vehicles and buses, the large number of variables in the sustainability assessment of transportation systems, and the subjective judgment of decision makers introduce uncertainty. The objective of this paper is thus twofold: (1) to demonstrate a sustainability framework that focuses specifically on vehicle characteristics and (2) to compare two multicriteria decision making (MCDM) methods in terms of ranking sustainability performance of transportation vehicles and applicability to selected indicators. The two most widely adopted MCDM methods for decision making were used, the weighted sum method for its simplicity and the fuzzy logic method for its ability to incorporate imprecise and vague information. The assessment includes five vehicle types and various mode share scenarios. The results from the two methods were compared by using traffic composition data by vehicle technology from a 33.2-km (20.6-mi) network in urban Honolulu. Both methods provided vehicle rankings on a continuous scale and integrate vehicle technology and fuel characteristics in the assessment. The differences between the two methods appear to be systematic with the weighted sum method generating results with greater fluctuations. The fuzzy logic method is more stable. It is also more flexible because it is capable of incorporating quantitative and qualitative judgment criteria. [ABSTRACT FROM AUTHOR]

Transport agencies around the world recognize the importance of on-time on-budget delivery of highway projects and understand the need for an efficient transport development process. Past studies of highway project duration and cost estimation were focused on construction, and few studies have focused on preconstruction project delivery from an agency's perspective. This paper proposes the use of hazard-based duration models for investigating the potential risk factors that could affect project development time from planning to letting. A database containing over 35 years of highway project data from the state of Indiana was used to develop appropriate models. Of the three model forms (Weibull, Weibull with gamma heterogeneity, and log-logistic) considered in the paper, it was found that the log-logistic model is the most appropriate for modeling project development time. For each work category (pavement, bridge, and road/interchange projects), risk factors were identified, and their influences on project development time (and consequently, on letting time) were investigated. The developed hazard-based duration models were further applied to demonstrate their ability to predict expected project development time for delivery and the project-related factors that influence this duration, thereby providing the agency with a useful interpretation of associated delivery risks. [ABSTRACT FROM AUTHOR]

Transportation planning agencies receive requests from both public and private entities to share their transportation planning data, models, and model output. In addition, some agencies receive requests from these entities to undertake special model runs on their behalf. Planning agencies have to respond to these requests with consideration, first, of state laws governing access to public information and, second, of the professional staff time required and the significant monetary expenses incurred in the process. Given the adverse state of public finances, planning agencies may face resource challenges in responding to such requests. This paper, first, presents the results of a literature review on data sharing/release policies for the transportation sector. Second, results of a nationwide survey of transportation planning agencies, conducted to identify primary concerns related to data release and cost recovery, are presented. Finally, the paper discusses the implications of these findings for public agencies seeking to develop policies. The literature review points to the need to develop data release and sharing arrangements so that limited public resources can be maximized and to ensure data that is released is well documented so that misuse does not occur. The survey findings indicate that the area of greatest concern for most planning agencies in sharing information is the potential for misinterpretation or misuse of data or models because they have found that often, requesters do not understand the limitations or appropriate uses of the data or models. To address these concerns, this paper makes a strong case for agencies to develop formal data and model release policies and to define a specific cost recovery structure if the agency intends to charge for services. [ABSTRACT FROM AUTHOR]

A key to the use of weigh-in-motion (WIM) traffic data for the Mechanistic-Empirical Pavement Design Guide (MEPDG) is to be able to successfully recognize the differences in loading patterns and to estimate the full axle-load spectrum data occurring under different conditions. However, how to identify these patterns on the basis of the large amount of WIM data remains a challenge. In this paper, WIM data collected in the state of Arkansas are analyzed by using cluster analysis methodologies to identify groups of WIM sites with similar traffic characteristics on the basis of the MEPDG-required traffic attributes. Case studies are presented and the cluster results are discussed. Combining the loading clusters, four long-term transportation planning factors currently adopted in Arkansas, including the modified Arkansas primary highway network (APHN) classification, demography, geography, and region attribute (rural or urban) of a highway under design, are adopted as the influencing criteria to develop the truck loading groups. The most significant influencing criteria are identified by using Fisher's exact test. Consequently, truck loading groups and their categorical logit models are developed in the paper. The developed method for determining truck loading groups will simplify the understanding and applicability of the traffic patterns and ultimately ease the preparation of the traffic load spectra inputs on the basis of WIM data for the MEPDG procedure. [ABSTRACT FROM AUTHOR]

Nested logit models calibrated on revealed preference (RP) and stated preference (SP) data have been used in this paper to study the potential market of a cybernetic transportation system for airport ground access. This innovative concept of transit mode could complement mass transit and nonmotorized transport modes, providing passenger service for any location at any time. Our analysis is based on a data set collected at Baltimore Washington Thurgood Marshall International (BWI) airport; the proposed cybercar service was designed to connect the Greenbelt metro station to the airport. The explanatory variables used in the utility functions of the RP/SP joint models are level of service attributes, characteristic specific to the new service offered, and socioeconomic variables. The estimated models are used to predict the market share of automobile, taxi, cybercar, and modified transit. In addition, elasticity tests are performed in order to study individuals’ sensitivity to the change of travel time and travel cost for automobile and cybercar. The estimation and application results in this paper can be used as a reference for the CityMobil program of the European Union to popularize this fast, convenient, and environmentally friendly cybercar. Meanwhile, the results provide useful behavioral data and models on the potential of advanced technological transportation system for airport ground planning in the United States. [ABSTRACT FROM AUTHOR]

Transportation agencies worldwide increasingly seek to abandon reactive approaches for safety enhancement in favor of approaches that incorporate safety in their transportation planning processes in a proactive, comprehensive, and systemwide context. To facilitate this task, this paper presents a framework which identifies candidate facilities in a transportation network for safety enhancement over a specified analysis period. Then for each candidate facility, the framework identifies safety enhancement projects on the basis of existing facility deficiencies and predominant accident patterns. Thus, a safety plan is developed to specify for each candidate facility, the year of the enhancement, the expected cost, and the resulting safety benefits. Also, where the safety budget is limited, the framework determines the subset of candidate facilities that should receive safety investment. At most transportation agencies, the typical transportation planning process is carried out only for engineering interventions. As such, the developed framework is engineering interventions only and thus excludes safety interventions related to road-user education, enforcement, and policy. With requisite data, the developed framework can be applied in safety planning and programming in the different modes of transportation–highway, airport, rail, and marine. Using an example in highway transportation, the paper applies the framework to develop a safety plan for a chosen network and thus demonstrates how safety could be included proactively in the network-level (systemwide) transportation planning process. [ABSTRACT FROM AUTHOR]

Utility conflicts are unfortunately a common occurrence on many construction roadway projects. Through a combination of case studies and statistical analyses of variance, this paper examines the cost, frequency, and severity of utility conflicts by both type and location (urban versus rural roadway projects). Understanding the true costs of utility conflicts sheds light on the significant magnitude of added construction costs that utility conflicts impose on state transportation agencies, utility companies, contractors, and the public during roadway construction. Understanding when and what type of utility conflicts most likely occur will help state transportation agencies better understand the risk of utility conflicts on future projects. The analyses presented in this paper are a result of a survey completed by state utility directors from 45 different United States state transportation agencies as well as four in-depth case studies of Kentucky roadway projects that experienced utility conflicts during construction. In addition to examining the frequency and severity of different utility conflicts, the paper also examines practices being utilized by different state transportation agencies and their impact on the frequency and severity of the conflicts. [ABSTRACT FROM AUTHOR]

Entropy maximization approach has been widely used in transportation planning. It provides theoretical basis for a class of forecast models on traffic demand. In this paper, the concept of entropy from information theory is borrowed to describe inhabitant trip distribution and then a trip distribution model is presented under constraints of typical characteristics based on origin moments. The model is characteristic of generality. The concrete form of the model depends on the order of the highest origin moment which has a great impact on the precision of the model and the labor of parameters calibration. The paper expatiates on this situation and puts forward an iteration method to ascertain the parameters in the model. And then, an entropy method is given to compare the difference of the models for selection. The application of the models and the methods is illustrated via 2001 trip data from the city of Changchun, China. [ABSTRACT FROM AUTHOR]

This paper discusses a model for optimally aligning an urban rail transit system within an integrated framework, on a demand-oriented corridor on a city transport network, using geographical information system (GIS) tools. The model is part of a methodology to develop a demand-oriented effective and efficient integrated urban mass transit system for a city which has a potential demand for a new rail-based mass transit system besides the street transit system and existing rail-based system (if any). Besides the proposed model the methodology consists of identifying the feeder routes and integrated schedules, but they are not within the scope of this paper. The objective of the model is to identify the new rail corridor, which is optimum from both the users’ and operators’ point of view. It consists of two stages: public transport travel demand forecasting, and rail transit corridor identification using a GIS-based heuristic algorithm. Thane City, which is a part of Mumbai Metropolitan Region India, was taken as the case study. The corridors were identified based on the demand obtained using user equilibrium approach, which consists of two routes. The maximum peak hour ridership on these routes was found to be ideal for recommending a light rail transit system for the identified corridors. The successful application of the model shows the capability of proposed model for a typical Indian city, which has the potential demand for a new rail system. [ABSTRACT FROM AUTHOR]

The network signal design problem (NSDP) seeks the optimal deployment of traffic signals in a growing urban area. This paper is especially concerned with how signals may be optimally deployed over a very long period of time for the purpose of creating realistic networks for travel forecasting. The NSDP is very difficult to solve for long-range problems because of the large number of possible solutions, the high cost of evaluating the merits of just a single solution, and the complexities of how signal delay affects traffic patterns and how traffic patterns affect signal delay. The paper describes the NSDP, introduces a reasonable set of simplifications based on transportation planning and traffic engineering practice, describes experiences with a possible heuristic algorithm for problem solution, and contrasts this method with current planning practice and other research. The long-range algorithm embeds a “strategic” algorithm for finding an optimal deployment for a single time period with constant travel demands. The strategic algorithm draws upon two well-known techniques of combinatorial optimization: a greedy constructive search coupled with a restricted neighborhood search. The strategic algorithm was able to find exact solutions on a small test network with eight stop-controlled intersections. The long-range algorithm is demonstrated on a full-sized planning network with about 380 stop-controlled intersections that could be signalized. [ABSTRACT FROM AUTHOR]

This paper proposes a framework for using business and organizational scenario-planning techniques for regional strategic transportation-planning purposes. The paper provides a brief history of scenario planning as it emerged from business-strategic planning activities and gives an overview of its goals and limitations. The paper then reviews the context for scenario planning in regional transportation planning as well as precedents of its application in this field. The paper continues with a presentation of a scenario-planning framework for transportation as refined and applied to the Houston metropolitan area. The major findings and lessons from this application are discussed, together with conclusions and observations regarding further potentials and refinements. [ABSTRACT FROM AUTHOR]

This paper adopts the World Bank’s 1996 definition of sustainable transportation and attempts to identify ways of improving the urban transportation planning process and methodology. After a literature review of related studies conducted in different parts of the world over the past decade or so, the major theoretical and methodological advances in stated preference (SP) surveys are summarized. Then, the paper continues to suggest ways of how SP techniques can be used side-by-side with the traditional four-stage transportation planning model. Lastly, it concludes with some future directions of change if these useful techniques are to play a more important role in planning for sustainable urban transportation. [ABSTRACT FROM AUTHOR]

This paper examines the practically of using a single internal trip purpose to generate the production and attraction values for traffic analysis zones in small urban community travel models. In previous research efforts, Quick-Response techniques, originally developed for cities with populations between 50,000 and 199,999, have been successfully applied to perform trip generation in small urban community travel models. Focusing on the reduction of data requirements and complexity of the trip generation analysis, a single trip purpose technique, based solely on aggregate numbers of households and businesses in a traffic analysis zone, has been proposed as a method to simplify the trip generation computation and reduce data requirements. This paper presents the fundamentals of the Quick-Response and single trip purpose techniques, tests the advantage of multiple trip purposes in a small sample network, and applies the two methodologies in a small urban community within Alabama to determine if significant differences exist when performing trip generation. The paper concludes that, for smaller urban community travel models, where different trip purposes are assumed to have similar trip lengths, both the Quick-Response and the single trip purpose technique produce similar results for the total productions and attractions in a traffic analysis zone. This similarity, and the results of the test showing that different trip purposes are not vital for trip distribution in small networks, substantiate the use of the simplified single trip purpose technique for trip generation. [ABSTRACT FROM AUTHOR]

When the National Environmental Policy Act (NEPA) process and the transportation project planning process are not streamlined, the NEPA process may lead to duplication of work and project delays. This paper presents research work in discovering state-suitable integration practices for integrating NEPA into statewide and metropolitan transportation project planning processes for the state of Illinois. The discovery of practices was based on an analytical review of existing integration guidelines and efforts in other states and using a survey of experts from relevant federal, state, and metropolitan planning, regulatory, and resource agencies. Two types of integration practices were identified: process-oriented and collaboration-oriented integration practices. The selected practices were integrated into existing transportation project planning processes and formalized into an integrated process flow with detailed implementation guidance. The integrated process was validated through a second expert survey. The validation results indicate that the integrated process, including its implementation detail and process representation, provides appropriate guidance for integrating NEPA into transportation project planning processes in Illinois. The implementation of the integrated process would improve interagency coordination and communication, enable early identification of potential environmental issues, reduce duplication of effort, and enhance project delivery in terms of time and cost. [ABSTRACT FROM AUTHOR]

Link level annual average daily traffic (AADT) or travel demand is used in several urban planning, roadway design, operational, and safety analyses by transportation planners and engineers. Existing AADT estimation methods do not adequately account for spatial proximity, variations, and dependency to address modeling needs. The primary focus of this paper, therefore, is to incorporate these aspects and develop a method to estimate link level AADT by the urban road functional class. Geospatial analytical techniques were explored to capture spatial data within proximal areas of selected roadway links and develop statistical models to estimate link level AADT. Polygon-based network buffers were generated within the proximal roadway distance of each study link to account for actual connectivity and capture off-network data instead of Euclidean distance-based buffers. On-network characteristics of the study links and upstream, downstream, and cross-street network links were considered to account for the spatial dependency of on-network characteristics. The applicability of the method and predictive capability of the models to estimate link level AADT, considering all of the selected study links and by each road functional class, was researched. The working of the method and development of the models is illustrated using data for the city of Charlotte in the state of North Carolina. The generalized estimating equation (GEE) models developed indicate that a negative binomial distribution fits better than a Poisson distribution for the data considered in this research. The ideal proximal distance to capture spatial data and accurately estimate AADT was observed to vary when all study links and different road functional classes were modeled separately. Overall, the results obtained indicate that spatial proximity and dependency play a vital role in accurately estimating travel demand on various urban road functional classes. [ABSTRACT FROM AUTHOR]

This paper presents the findings and outcomes of an assessment of transit needs in Nebraska. Specifically, the paper presents data from Scottsbluff/Gering, Kearney, and Norfollk, Nebraska, because data for these communities were gathered through both a survey and a focus group. The study builds upon a previous statewide transit needs assessment, but uses an alternative approach—a qualitative research design. This research design steers the study toward findings that identify personal transit needs, which would not emerge from a traditional, quantitative assessment, and outcomes that are more locally applicable. Among the findings of this study are the perceived need for more service hours and a greater flexibility for seniors' needs. Outcomes include changes in service hours and new collaborative efforts. [ABSTRACT FROM AUTHOR]

Transportation planning is multidimensional, complex, and dynamic in nature. The decision-making process often involves multiple stakeholders with conflicting preferences. Effective decision outcomes can only be reached by explicitly addressing such conflicts. Over the last several decades, optimization techniques have been used for project-selection decisions to achieve maximized overall returns on investments. The existing methods for project selection capable of conducting trade-off analyses mainly focus on assessing trade-offs between project construction time, duration, and cost, as well as swapping between transportation agency costs and user costs. However, they have largely not addressed impacts on the overall economic returns by changing a few important decision factors such as differentiating relative importance of various transportation performance goals and measures, and different types of highway facilities, and further relaxing the budget constraints by management programs dealing with physical facilities and system operations while keeping the total budget unchanged. This paper introduces a trade-off analysis approach that uses a multicommodity minimum-cost network (MMCN) model to establish traffic details for the transportation network needed for estimating the benefits of implementing a single project or multiple projects jointly, and a surrogate worth trade-off (SWT) method for multiobjective project selection based on the estimated project benefits. A computational study has revealed that the proposed trade-off approach can generate noninferior solutions and increase the total benefits by 18-20%. [ABSTRACT FROM AUTHOR]

High-speed rail (HSR) networks require large investments, and the performance of the infrastructure is affected by varying local environments, while subject to tight layout restrictions. This paper presents a fully integrated three-dimensional model to optimize the HSR alignment at a planning scale, which sets boundaries for the final project design. The model considers mandatory and desirable specifics for the locations to link and the geometry in both the plan view and the longitudinal profile. It also allows one to define prohibited and restricted land-use areas. A computational tool has been developed that takes into account the problem specifics using a simulated annealing algorithm to optimize the problem solution. The capabilities of the model and the tool are demonstrated with the application to an intentionally simple and synthetic case study, considering construction costs and problem constraints, for which sound results are obtained. Both the model and the tool can be expanded to incorporate additional complexity, establishing the basis for real applications and for further integration of geotechnical and hydrological risk factors that affect the HSR performance. [ABSTRACT FROM AUTHOR]

Transportation has contributed to climate change and will most likely be impacted by changes in sea level, temperature, precipitation, and wind, for example. As the risk of climate change impacts become more imminent, pressure for adaptation within transportation agencies to address these impacts continues to rise. The most logical strategy is to integrate consideration of adaptation projects into the long-range transportation planning (LRTP) process. To do this, tools and experience are needed to assist transportation agencies. The Climate Change Adaptation Tool for Transportation (CCATT) is a step-by-step method to evaluate climate change scenarios and impacts, inventory at-risk existing and proposed infrastructure, and assess mitigation practices to identify supporting adaptation efforts. This paper focuses on the application of CCATT to the Mid-Atlantic region using a case study on the Wilmington Area Planning Council (WILMAPCO), the Metropolitan Planning Organization for northern Delaware. The results of the application and case study demonstrate the importance of climate change adaptation practices in long-range transportation planning. [ABSTRACT FROM AUTHOR]

Rural feeder service between villages and bus stops is largely a missing component in developing countries such as India. Traditionally, planning of rural feeder service has been carried out without due consideration to indirect costs associated with hard factors (e.g., walking distance and waiting time) and soft factors (e.g., crowding inside vehicles) of the service. A case study is presented for the planning of rural feeder service with due consideration to direct and indirect costs to users and operational viability of the service. Direct and indirect costs to users are expressed in terms of a comprehensive measure called generalized cost (GC). GC is developed on the basis of the willingness to pay (WTP) of rural commuters with respect to various attributes of rural feeder service. The work demonstrates the effect of catchment characteristics (i.e., number of villages, size of villages, and spatial separation represented by road network connecting villages to bus stop) on feeder service attributes (i.e., type of vehicle, route, headway of service and fare). It is also shown that planning of feeder service could be instrumental in bringing benefits to rural communities. The results presented in the paper are case specific, but the methodology can be applied to the planning of feeder services in other rural regions. [ABSTRACT FROM AUTHOR]

This paper investigates a number of alternative methods for addressing the empty-cell problem of traditional cross-classification analysis. Data used in the study were collected in the Toronto region in 1986, 1996, 2001, and 2006. Alternative models, developed on each year's data, were assessed for how well they predicted travel at the disaggregate household level and at the aggregate traffic analysis zone level in the respective years. In addition, the alternative models estimated on the 1986 data set were assessed for their ability to replicate travel in 1996 and 2006. The results show that a method proposed by Mandel and a model developed in this research, which estimates the household trip rate for an empty cell through a linear combination of the predictions yielded by row and column models, overall give the best forecast performance of travel. They perform better than multiple classification analysis, which is the current industry standard for addressing this shortcoming of traditional cross-classification analysis. The combined categories model also performed very well, particularly in predicting travel at the aggregate level of planning interest. [ABSTRACT FROM AUTHOR]

Departments of transportation in the United States are under increasing pressure to accelerate projects to meet user-defined constraints and reduce the inconvenience to the traveling public. Although there is information about acceleration projects in other industries, there has been little specifically aimed at highway projects. A domestic scan sponsored by the National Cooperative Highway Research Program was tasked with providing information in this area. The objective of this paper is to synthesize the resulting information into fundamentals that support successful planned accelerated highway project delivery. Case studies of how departments of transportation successfully accelerated the construction of four very different projects in California, Florida, and Texas serve as the basis for identifying these fundamentals. The fundamentals include upfront and detailed planning, designs that facilitate accelerated construction, a collaborative environment for project stakeholders, and incentives and disincentives to motivate construction contractors. [ABSTRACT FROM AUTHOR]

Activity-based travel demand forecasting consists of modeling activity type, location, and duration with a view to improving transportation planning and creating effective traffic management systems. Research to date has focused primarily on weekday activity patterns, but given its steady increase, weekend activities and related travel demand also deserve attention. Limited research studied weekend activities, and none of them was found to provide detailed specifications with respect to best-fit hazard functions and lifetime regression models. This study, which took place in Calgary, Alberta (a Canadian city of 1,000,000+), is meant to address that gap. Ten activity patterns of eight demographic groups were assessed and nearly 13,000 observations analyzed. Results affirm that most weekend activities are neither work nor school related and tend to begin mid-day or later; analysis of activity participation by demographic group shows that adults (19–64 years old) are the most active components of our society. Likelihood ratio tests confirm that a two-level modeling exercise is required to handle the heterogeneity within the data: first, analysis by activity type and second, analysis by demographic group. Eleven candidate hazard functions were examined for 10 weekend activities such as shopping or entertainment, then best-fit hazard functions and lifetime regression models were determined. The results show a high degree of fit. It was found that the best-fit parametric models for demographic subgroups are generally consistent with those based on activity type at the aggregate level, a discovery that should simplify future applications. Lifetime regression models show that the starting time of a given activity and personal mobility are the most significant factors influencing activity duration. The applicability of fully parametric, nonparametric, and semiparametric model is discussed and addressed at various points within the paper. The rounding problem of reported durations is also noticed and discussed during the process of identifying best-fit hazard functions and lifetime regression models. [ABSTRACT FROM AUTHOR]

Transportation infrastructure asset management efforts have historically focused on collecting data on assets with high capital costs, such as bridges and pavements. Road signs and pavement markings, on the other hand, are high quantity, low capital cost assets but are also critical elements of the transportation infrastructure. These high quantity assets serve a critical function, safety, and thus they are receiving attention. Mandated by law, the Federal Highway Administration has been working to establish minimum retroreflectivity standards for signs and pavement markings. This paper seeks to address the information technology (IT) problems that emerge when developing an overall asset management system for high-quantity, low-cost assets. These IT problems include asset identification, asset location, data availability, data fragmentation, and automated data collection. A discussion of the issues related to these problems is presented to promote awareness of the myriad problems that do exist and to facilitate the development of more comprehensive systems to manage the automation of infrastructure asset management systems. [ABSTRACT FROM AUTHOR]

The build-operate-transfer (BOT) scheme is being used increasingly by governments in their drive to privatize major public transportation projects. In a BOT scheme, the main objective for the private investors in determining the viability of a BOT project is profit, whereas the main objective for the government is whether the construction of the BOT project will give a positive social welfare to the society. These two objectives are often seen to conflict with each other. In this paper, modeling and analysis of highway pricing and capacity choice of a BOT scheme are provided to illustrate the tradeoff between the two objectives. Regulation is normally imposed by the government to ensure that the BOT project satisfies certain requirements. Five cases of the BOT network design problem are analyzed: (1) BOT without regulation; (2) BOT with positive performance measures; (3) BOT with a maximum toll charge level; (4) BOT with a minimum roadway capacity; and (5) BOT with a maximum toll charge and a minimum roadway capacity. Numerical results using a case study of the intercity expressway in the Pearl River Delta Region in China are provided to examine the various effects of regulation on a BOT project. [ABSTRACT FROM AUTHOR]

Several state Departments of Transportation (DOTs) and metropolitan planning organizations (MPOs) in the United States are considering environmental issues in the early stages of the transportation planning process, recognizing that there are benefits to be gained from better decisions, reduced public controversy, and shortened times to project implementation. This paper examines the current practice of such consideration, with special emphasis on best case examples. The study was conducted through a literature review, a survey of state DOTs and MPOs, and the identification of best case examples. The findings indicate the emergence, both in the literature and in practice, of more formal recognition of the need to consider environmental factors earlier in the planning process. State DOTs and MPOs agree that air quality, land use, socio-economic, environmental justice, and community cohesion impacts are of greatest concern today, and will be so in 10 years. Different approaches for considering environmental factors in planning include scenario analysis, environmental analysis of plans, environmental performance measures, consideration of equity issues, new data and analysis tools, and innovative institutional partnerships. [ABSTRACT FROM AUTHOR]

Buses, and more generally at-grade public transportation, remain the most important component of transit services in all urban areas but the steady increase in travel demand, especially in private automobiles, has resulted in a growing level of congestion, affecting both cars and public transportation. The innovative introduction of preferential treatment is surprisingly not generalized in spite of its benefits, raising the question of whether preferential treatment is transferable. By applying the agenda-building theory to the context of public transportation, the paper outlines how innovative policy making can be introduced and determines if the presence of a policy entrepreneur is a necessary and sufficient condition. Using 11 cities in Europe and America as case studies, essential elements have been identified for addressing public reaction, institutional fragmentation, and the stance of decision makers. It can be concluded that the rising concerns about transportation and the emergence of mixed decision-making models allow cities to implement preferential treatment without a policy entrepreneur. [ABSTRACT FROM AUTHOR]

This paper presents a procedure for the estimation of multiclass origin-destination (O-D) matrices for a highway network. The system consists of a number of vehicle classes. Demand is assigned to the network in a user equilibrium manner. An entropy maximization procedure is proposed to simultaneously estimate the O-D demand matrices of all vehicle classes, which are consistent with the multiclass traffic counts that are observed directly in the network. A case study of the Hong Kong highway network demonstrates the effectiveness of the proposed methodology for a real large-scale network. [ABSTRACT FROM AUTHOR]

The Small Business Liability and Brownfields Revitalization Act of 2002 reflects a continuing national commitment to redevelop and return brownfields to productive use. As brownfields are being redeveloped, there are a growing number of projects where transportation has played a critical role. Through ten case studies of contemporary brownfield redevelopments, this paper discusses the roles that transportation can play in promoting brownfields redevelopment. The cases show that transportation can either hinder or drive brownfields redevelopment. While obsolete transportation infrastructure makes brownfield corridors or areas less attractive to potential developers, transportation projects strategically designed and located to improve accessibility between brownfield corridors and major economic centers tend to drive brownfields redevelopment. Such projects can be accelerated by including them in the metropolitan and state transportation improvement programs. The cases show that municipal, county, and other officials can proactively use their long-range transportation planning activities to stimulate brownfields redevelopment and accelerate the associated economic, environmental, and social benefits. [ABSTRACT FROM AUTHOR]

Most transport models for short-term strategic planning are required to be calibrated with current planning parameters and updated traffic data. There are basically two steps involved in transport model calibration, namely, trip matrix updating and network calibration. These two steps are carried out iteratively in the conventional approach and may not achieve a stable solution. This paper proposes a bilevel programming model that integrates the two steps of trip matrix updating and network calibration into one stage. A solution algorithm is developed on the basis of genetic algorithms. Numerical examples are presented to illustrate the performance of the proposed model and solution algorithm under various conditions where different source data are available. [ABSTRACT FROM AUTHOR]

Understanding and predicting individual mode choice decisions can help address issues ranging from forecasting demand for new modes of transport to understanding the underlying traveler behavior and characteristics. Early research in mode choice modeling revolved, almost exclusively, around the family of logit models. But a number of researchers have recently argued that these models place restrictions on their parameters that compromise their performance and have thus experimented with a number of newly developed, flexible mathematical techniques. The present paper extends prior research by developing a methodology for predicting individual mode choice based on a nonparametric classification methodology that imposes very few constraining assumptions in yielding mode choice predictions. Preliminary results, using data from three vastly different international settings, are promising, especially when considering that the models are successful while using only a limited number of independent variables to achieve these predictions. [ABSTRACT FROM AUTHOR]

The sequential travel forecasting procedure is widely accepted without question by transportation planners, yet its origins are obscure, its effects on practice and research may well be negative, and by focusing attention on individual steps, it tends to impede overall progress in improving forecasting methods. Alternatives to the sequential procedure proposed by researchers over the past 30 years are examined, and recent advances are presented. A call for a new travel forecasting paradigm concludes the paper. [ABSTRACT FROM AUTHOR]

There is general agreement that the Rational Planning Model (RPM) used widely in the context of urban systems planning has problems coping with recalcitrant or “wicked” problems. This paper explores the use of pragmatic reasoning and abductive inferencing for improving this situation. First, the congruence of planning theory, pragmatic philosophy, and organizational learning theory is investigated, then a basic framework incorporating abductive inferencing in the RPM is demonstrated, with the objective of improving the current planning process. A case study drawn from transportation systems planning demonstrates the use of abductive inferencing. This introductory inquiry indicates that a learning process to supplement the RPM through the use of abductive inferencing advances the model's capability for coping with “wicked” problems. [ABSTRACT FROM AUTHOR]