Planning for implementation

Although the urban transportation planning process has evolved into the most sophisticated of all urban planning processes, the increasirig difficulty in implementing long-range transportation plans in urban areas today suggests basic questions concerning the process which deserve critical examination.Planning for implementation of urban transportation programs, particularly during periods of rapidly changing human values, requires a continuing re-evaluation of both technical and organizational strategies and their interrelationships.This paper raises some fundamental questions about the traditional activities and relationships that have characterized most urban transportation planning programs in the past. It also suggests a number of strategies, both technical and organizational, that may contribute to the implementation of plans and programs resulting from the transportation planning process.The first portion of this paper discusses the implications of not providing transportation services to match metropolitan growth. The experience of the Washington Metropolitan Area over the past decade is used to illustrate these implications.A discussion of organizational and institutional constraints upon the planning process follows. Then, the implications for the planning process are explored, and the scale of planning is reviewed as well as the need for monitoring the performance and impact of facilities.Next, the paper deals with the need to broaden the range of solutions to transportation problems, including consideration of economic and land development policies to reduce travel demand, as well as the provision of new facilities.Finally, techniques for involving decision-makers in the planning process are discussed. Examples of special project activities in the Washington area are used to illustrate these techniques and their value.     

A land use and transportation integration method for land use allocation and transportation strategies in China

In this paper, we will first review literature of the land use and transportation interaction and then develop a new land use allocation methodology called Three Stages-Two-Feedback Method (Integration Method) for both land use allocation and the transportation policy options with a practical implementation. Then we apply this method in an urban general planning project in China with more than 1.2 million populations. In this project, we evaluated three land use allocation strategies and three transportation policy options using two application tools (with and without feedbacks) using this method implemented in a land use planning system UPlan and a transportation planning system Emme. The results show that the use of the feedback method (Application Two) results in a vehicle distance reduction and the increase in the service coverage area of transit bus stops at the same time. Due to the use of transportation accessibility and the congestion measures with a MSA implementation, the accessibility measure shows a convergent process over iterations. This nice feature can be used for alternative comparisons. Future research subjects are also discussed.     

Urban university campus transportation and parking planning through a dynamic traffic simulation and assignment approach

Abstract

Many urban university campuses are considered major trip attractors. Considering the multimodal and complex nature of university campus transportation planning and operation, this paper proposes a dynamic traffic simulation and assignment analysis approach and demonstrates how such a methodology can be successfully applied. Central to the research is the estimation of trip origin–destinations and the calibration of a parking lot choice model. Dynamic simulation is utilized to simulate multiple modes of transportation within the transportation network while further assigning these modes with respect to various mode-specific roadway accessibilities. A multiple vehicle-class simulation analysis for planning purposes becomes a critical capability to predict how faculty and staff who once parked within the campus core choose other nearby alternate parking lots. The results highlight the effectiveness of the proposed approach in providing integrated and reliable solutions for challenging questions that face urban university campus planners and local transportation jurisdictions.     

Techniques of land use/transportation planning in Australian cities

With the publication of the Sydney Area Transportation Study, land-use/transportation studies now have been conducted in all capital cities as well as in the majority of other urban areas with populations in excess of 40.000. A review of these studies is made and a qualitative assessment is attempted of the technical phases —land-use planning, trip-generation, trip-distribution, modal-split, traffic assignment and evaluation. Full summary results of this comparative survey are presented in tabular form, although themes developed in the text are illustrated with specific examples from individual studies. The methodology of land-use/transportation studies has been attacked by some Australian writers. An attempt is made to assess the relevance of these criticisms when applied to the practical planning process in Australia.     

Mapping spatial accessibility of public transportation network in an urban area – A case study of Shanghai Hongqiao Transportation Hub

Accessibility is a key metric when assessing the efficiency of an urban public transportation network. This research develops a methodology for evaluating spatial accessibility of a system with multiple transportation modes in an urban area, Shanghai Hongqiao Transportation Hub (SHTH) and its surrounding area. The method measured total traveling time as an accessibility indicator, which summed the time people spent on walking, waiting, transfer and transportation in a journey from the SHTH to destinations. Spatial accessibility was classified into five levels from very high to very low. The evaluation was conducted at a cell-by-cell basis under an overall scenario and three specific scenarios. Evaluation results were presented in a series of maps. The overall accessibility scenario shows a concentric-ring trend decreasing from the SHTH to the fringe of the study area. Areas along the metro lines generally have a much higher accessibility than those along the bus lines with some exceptions where bus routes play a more important role. Metro stations identified as either time-saving or time-consuming points are mainly distributed around the urban center. Some suggestions are proposed for improving accessibility of public transportation network in the study area. The results from this study provide a scientific basis and useful information for supporting decision-making on urban planning, and assisting dwellers to travel in a time-efficient manner. The methodology offers a simple, flexible way to the spatial evaluation, metro station identification and network modification of accessibility of public transportation systems with multiple transportation modes.     

Metadata-based Needs Assessment for Emergency Transportation Operations with a Focus on an Aging Population: A Case Study in Florida

In the aftermath of disasters, evacuating aging victims and maintaining an optimal flow of critical resources in order to serve their needs becomes problematic, especially for Gulf Coast states in the USA such as Florida, where more than 6.9 million (36.9%) of the population are over age 50. Scanning the literature, there is no substantial prior work that has synthesized the requirements for a multi-modal emergency needs assessment that could facilitate the safe and accessible evacuation of aging people, and optimize the flow of resources into the affected region to satisfy the needs of those who remain. This paper presents a review of the aging population-focused emergency literature utilizing a knowledge base development methodology supported with a geographic information system-based case study application set in Florida. Importance is given to both ensuring the resiliency of the transportation infrastructure and meeting the needs of aging populations. As a result of this metadata-based analysis, critical research needs and challenges are presented with planning recommendations and future research directions. Results clearly indicate that transportation agencies should focus on clear and fast dissemination of disaster-related information to the aging populations. The use of paratransit services for evacuating aging people, especially those living independently and/or in rural areas, is also found to be of paramount importance.     

Data display techniques for transportation analysis and planning: an investigation of three computer‐produced graphics

Graphics are a powerful but often costly means of communication. Computer‐drawn graphics offer a new and relatively inexpensive way to assist the communication of complex technical information to both planners and non‐technical people whose full potential is now beginning to be realized. This paper discusses the utility of graphics and introduces three computer‐drawn graphic techniques which may be useful, both for analysis and presentation of results, in the transportation planning process. CENVUE(S) produces a three‐dimensional, perspective‐view map, on which virtually any type of transportation data or performance indicator can be displayed. VAP is designed to display origin‐destination travel patterns in any region. TDN transforms a physical‐distance network into a time‐distance network so that effects of different speeds in the transportation network can be readily seen. The cost‐effectiveness of each technique is briefly discussed and some recommendations for evaluating computer graphics techniques are provided to aid the user in further assessing their utility in the transportation planning process.     

Urban transportation and equity: A case study of Beijing and Karachi

Development of mega cities of Pakistan and China has greatly been affected by the growth in urbanization and motorization. The uncontrolled rise in urbanization, motorization, exclusionary planning and disproportionate investment in transportation infrastructure has created a socio-economic imbalance, thereby challenging the issue of equity. This paper focuses on a comparative social equity assessment of urban development, characteristics of supply and demand of transportation and infrastructure systems and the impact of existing strategies over equity in the development of urban and transportation system of Beijing and Karachi. The paper concludes by suggesting some strategies for the development of sustainable and equitable urban transportation systems.     

Demand management as an element of transportation policy: using carrots and sticks to influence travel behavior

This paper describes the characteristics of transportation demand management. The origin of transportation demand management (TDM) as it has evolved in the US is related to federal policy initiatives that first focused on improving the efficiency of the urban transportation system through operational improvements, and then incorporated concerns such as air quality and energy conservation into the transportation planning process. The paper then examines the effectiveness of TDM actions, and concludes that those actions most likely to increase the “price” of travel for single occupant vehicle use will be most effective. The paper identifies several strategies for improving the effectiveness of TDM actions in the context of regional transportation planning, including: incorporating TDM as part of the solutions for regional transportation planning, linking TDM to land use decisions, making the costs of travel more apparent to the user, and making TDM implementation more palatable to the general public.     

Multi-criteria route planning based on a driver’s preferences in multi-criteria route selection

In this study, some different approaches were designed, implemented, and evaluated to perform multi-criteria route planning by considering a driver’s preferences in multi-criteria route selection. At first, by using a designed neuro-fuzzy toolbox, the driver’s preferences in multi-criteria route selection such as the preferred criteria in route selection, the number of route-rating classes, and the routes with the same rate were received. Next, to learn the driver’s preferences in multi-criteria route selection and to classify any route based on these preferences, a methodology was proposed using a locally linear neuro-fuzzy model (LLNFM) trained with an incremental tree based learning algorithm. In this regard, the proposed LLNFM-based methodology reached better results for running-times, as well as root mean square error (RMSE) estimations in learning and testing processes of training/checking data-set in comparison with those of the proposed adaptive neuro-fuzzy inference system (ANFIS) based methodology. Finally, the trained LLNFM-based methodology was utilized to plan and predict a driver’s preferred routes by classifying Pareto-optimal routes obtained by running the modified invasive weed optimization (IWO) algorithm between an origin and a destination of a real urban transportation network based on the driver’s preferences in multi-criteria route selection.     

Spatio-temporal analysis of rail station ridership determinants in the built environment

The development of new routes and stations, as well as changes in land use, can have significant impacts on public transit ridership. Thus, transport departments and governments should seek to determine the level and spatio-temporal dependency of these impacts with the aim of adjusting services or improving planning. However, existing studies primarily focus on predicting ridership, and pay relatively little attention to analyzing the determinants of ridership from temporal and spatial perspectives. Consequently, no comprehensive cognition of the spatio-temporal relationship between station ridership and the built environment can be obtained from previous models, which makes them unable to facilitate the optimization of transportation demands and services. To rectify this problem, we have employed a Bayesian negative binomial regression model to identify the significant impact factors associated with entry/exit ridership at different periods of the day. Based on this model, we formulated geographically weighted models to analyze the spatial dependency of these impacts over different periods. The spatio-temporal relationship between station ridership and the built environment was analyzed using data from Beijing. The results reveal that the temporal impacts of most ridership determinants are related to the passenger trip patterns. Furthermore, the spatial impacts correspond with the determinants’ spatial distribution, and the results give some implications on urban and transportation planning. This analysis gives a common analytical framework analyzing impacts of urban characteristics on ridership, and extending researches on how we capture the impacts of urban and other factors on ridership from a comprehensive perspective.

     

Reflections on citizen involvement in urban transportation planning: Towards a positive approach

The purpose of this paper is to explore an important and unique role which community participation and involvement can play in a revised transportation planning process. A review of diverse views about community participation, as well as a critique of the current urban transportation planning process, reveals that the former has played, primarily, ad hoc opportunistic and diverse roles, and that the latter is in desperate need for dynamic, subjective, impact information — required to assess attractive transportation systems. The contributions of several disciplines — economics, operations research, management science, political science, public administration, and others — are reviewed to assist in the development of a conceptual framework for a new community participation role, as a provider of key information to the planning process. An eclectic, experimental approach is recommended to explore the possibilities further.     

The Bid-rent Land Use Model of the simple,efficient, elegant,and effective model of land use and transportation

Integrated land use/transportation forecasting models add significant policy and infrastructure alternatives analysis capabilities to the urban planning process. The financial, time, and staff requirements to develop these models has put them beyond the reach of most small to medium sized urban areas. This paper presents the land use allocation submodel of the Simple, Efficient, Elegant, and Effective model of land use and transportation (SE³M), an integrated land use and transportation forecasting model founded upon Economic Base Theory and Bid-rent Theory. The Bid-rent Land Use Model (BLUM) is an agent based, spatial competition model utilizing unique utility curves for willingness to pay and incomes for budget constrained abilities to pay for each agent. The model structure, estimation, calibration, implementation, and validation are presented. With a single year of land use data available, the validation approach used the Kappa Index of Agreement to spatially check model outputs against base year control data while controlling for agreement by chance. The U.S. territory of Guam is used as the case study/proof of concept implementation for this model framework. Once calibrated, BLUM could solve the spatial competition problem on Guam in less than two minutes of processing time with over 90% accuracy.     

Evaluating unintended outcomes of regional smart-growth strategies: Environmental justice and public health concerns

Many urban areas are perusing infill, transit oriented, and other “smart-growth” strategies to address a range of important regional goals. Denser and more mixed use urban development may increase sustainability and improve public health by reducing vehicle travel and increasing the share of trips made by transit, walking and bicycling. Fewer vehicle trips results in fewer greenhouse gas and toxic vehicle emissions, and more trips made by walking and bicycle increases physical activity. Prior research has largely focused on modeling and estimating the potential size of these and other smart-growth strategy benefits. A largely overlooked area is the potential for unexpected public health costs and environmental justice concerns that may result from increasing density. We evaluate regional land-use and transportation planning scenarios developed for the year 2040 by a metropolitan planning organization with a newly developed regional air quality modeling framework. Our results find that a set of regional plans designed by the MPO to promote smart-growth that are estimated to result in less vehicle use and fewer vehicle emissions than a more typical set of plans results in higher population exposure to toxic vehicle emissions. The smart-growth plans also result in greater income-exposure inequality, raising environmental justice concerns. We conclude that a more spatially detailed regional scale air quality analysis can inform the creation of smarter smart-growth plans.     

Freight Data Assembling and Modeling: Methodologies and Practice

Abstract

In comparison to personal travel, freight movements within large metropolitan areas are much less studied. Most conventional transportation models and planning analysis that disregarded freight flows have been criticized on the plausibility of their results and conclusions. To alleviate these problems, this study proposes a non-survey based approach to assemble and process freight data in a systematic way. A freight origin–destination (OD) matrix of freight flows can be developed using secondary data sources. The estimated freight flows can be loaded together with conventional passenger flows onto the regional highway network of a large metropolitan area. As a case study, this non-survey based approach was applied to build a freight OD and study the traffic flows in Los Angeles. It concluded that this approach can be used to analyze urban freight movement in a low-cost way in which planning agencies can overcome the common omission of freight flow information in their transportation plans.     

The simple,efficient, elegant,and effective model (SE3M) of land use and transportation

Integrated land use/transportation forecasting models add significant policy and infrastructure alternatives analysis capabilities to the urban planning process. Historically, the financial, time, and staff requirements to develop one of these models has put them beyond the reach of most small- to medium-sized urban areas. The purpose of this paper is to present the large zone economic submodel of SE³M, an integrated model – founded upon economic base theory and bid-rent theory – that is reasonably accurate, yet simpler in form, function, and implementation than competing models. The US territory of Guam is used as the case study/proof of concept implementation for this model framework. The submodel presented here was validated against a horizon year with known data for zonal level population and employment totals together with control totals for the island as a whole. The model was able – across two base years and one validation, horizon year – to locate all jobs and a high percentage of the population on each zone on the island.     

Methodology for Validating Dynamic Origin–Destination Matrix Estimation Models with Implications for Advanced Traveler Information Systems

This paper describes a methodology for validating online dynamic O–D matrix estimation models using loop detector data in large-scale transportation networks. The simulation procedure focuses on travel aspects related to the collective trip structure of users, including the amount and duration of trips between O–D pairs, trip departure rates, average travel time from each origin and combinations of them. The analysis identifies emerging systematic patterns between these factors and issues related to the model performance, including network scale effects. This procedure aims to enhance the usage of prior O–D information based on, e.g. travel surveys, that are typically used in the estimation process. Moreover, it seeks to integrate the validation of dynamic O–D matrix estimation models with strategies for identifying target population groups for online planning and assessment of real-time travel information services within the context of Advanced Traveler Information Systems (ATIS).     

Campus parking supply impacts on transportation mode choice

Parking demand is a significant land-use problem in campus planning. The parking policies of universities and large corporations with facilities located in small urban areas shape the character of their campuses. These facilities will benefit from a simplified methodology to study the effects of parking availability on transportation mode mix and impacts on recruitment and staffing policies. This paper, based on a case study of North Dakota State University in the United States, introduces an analytical framework to provide planners with insights about how parking supply and demand affects campus transportation mode choice. The methodology relies only on aggregate mode choice data for the special generator zone and the average aggregate volume/capacity ratio projections for all external routes that access the zone. This reduced data requirement significantly lowers analysis cost and obviates the need for specialized modelling software and spatial network analysis tools. Results illustrate that the framework is effective for analysing mode choice changes under different scenarios of parking supply and population growth.     

A methodology for identifying similar days in air traffic flow management initiative planning

This article describes a methodology for selecting days that are comparable in terms of the conditions faced during air traffic flow management initiative planning. This methodology includes the use of specific data sources, specific features of calendar days defined using these data sources, and the application of a specific form of classification and then cluster analysis. The application of this methodology will produce results that enable historical analysis of the use of initiatives and evaluation of the relative success of different courses of action. Several challenges are overcome here including the need to identify the appropriate machine learning algorithms to apply, to quantify the differences between calendar days, to select features describing days, to obtain appropriate raw data, and to evaluate results in a meaningful way. These challenges are overcome via a review of relevant literature, the identification and trial of several useful models and data sets, and careful application of methods. For example, the cluster analysis that ultimately selects sets of similar days uses a distance metric based on variable importance measures from a separate classification model of observed initiatives. The methodology defined here is applied to the New York area, although it could be applied by other researchers to other areas.     

Ontologies for transportation research: A survey

Transportation research relies heavily on a variety of data. From sensors to surveys, data supports day-to-day operations as well as long-term planning and decision-making. The challenges that arise due to the volume and variety of data that are found in transportation research can be effectively addressed by ontologies. This opportunity has already been recognized – there are a number of existing transportation ontologies, however the relationship between them is unclear. The goal of this work is to provide an overview of the opportunities for ontologies in transportation research and operation, and to present a survey of existing transportation ontologies to serve two purposes: (1) to provide a resource for the transportation research community to aid in understanding (and potentially selecting between) existing transportation ontologies; and (2) to identify future work for the development of transportation ontologies, by identifying areas that may be lacking.