Development of a transit network from a street map database with spatial analysis and dynamic segmentation

This paper presents an integrated transit-oriented travel demand modeling procedure within the framework of geographic information systems (GIS). Focusing on transit network development, this paper presents both the procedure and algorithm for automatically generating both link and line data for transit demand modeling from the conventional street network data using spatial analysis and dynamic segmentation. For this purpose, transit stop digitizing, topology and route system building, and the conversion of route and stop data into link and line data sets are performed. Using spatial analysis, such as the functionality to search arcs nearest from a given node, the nearest stops are identified along the associated links of the transit line, while the topological relation between links and line data sets can also be computed using dynamic segmentation. The advantage of this approach is that street map databases represented by a centerline can be directly used along with the existing legacy urban transportation planning systems (UTPS) type travel modeling packages and existing GIS without incurring the additional cost of purchasing a full-blown transportation GIS package. A small test network is adopted to demonstrate the process and the results. The authors anticipate that the procedure set forth in this paper will be useful to many cities and regional transit agencies in their transit demand modeling process within the integrated GIS-based computing environment.     

What transportation modeling needs from a GIS: a conceptual framework

Both the geographic information system (GIS) and transportation modeling environments have seen continually developing analytic concepts and techniques. However, these developments have seldom resulted in the integration of GISs and transportation models. This paper explores the potential inherent in merging of these environments through a systematic investigation of the fundamental basis of integration. To do this, the traditional four step transportation modeling process is extended to include input and output steps. We then define functional components for GIS data handling — data management, manipulation, and analysis. The steps of modeling are matched against the list of GIS data handling functions within a matrix‐based framework. GIS functions that enhance a land‐use based urban transportation modeling process are then categorized. Conclusions are drawn and directions for future developments are discussed.     

Geographic information system design for network equilibrium-based travel demand models

Travel demand analyses are useful for transportation planning and policy development in a study area. However, travel demand modeling faces two obstacles. First, standard practice solves the four travel components (trip generation, trip distribution, modal split and network assignment) in a sequential manner. This can result in inconsistencies and non-convergence. Second, the data required are often complex and difficult to manage. Recent advances in formal methods for network equilibrium-based travel demand modeling and computational platforms for spatial data handling can overcome these obstacles. In this paper we report on the development of a prototype geographic information system (GIS) design to support network equilibrium-based travel demand models. The GIS design has several key features, including: (i) realistic representation of the multimodal transportation network, (ii) increased likelihood of database integrity after updates, (iii) effective user interfaces, and (iv) efficient implementation of network equilibrium solution algorithms.     

Data attribution and network representation issues in GIS and transportation

Geographic Information System (GIS) is an “intelligent” technology which integrates attribute data and spatial features and manages the relationship between them. GIS is widely used in many activities, but its application in transportation is less common. The extension of GIS into transportation (GIS‐T) offers the potential to integrate transportation data into GIS. The integration of transportation data in GIS faces a number of barriers that are discussed in the paper. These barriers can be broadly categorized into data attribution and network representation issues. This paper analyzes these issues and reviews the potential for overcoming these constraints with current GIS technology. A fully developed GIS‐T has to meet many diverse needs including transportation inventory, modeling and operational problems. If GIS is to succeed as a transportation technology, it must be capable of integrating different levels of network representation and data attribution and have the ability to link with other transportation technologies.     

Path flow estimator for planning applications in small communities

This paper presents an alternative planning framework to model and forecast network traffic for planning applications in small communities, where limited resources debilitate the development and applications of the conventional four-step travel demand forecasting model. The core idea is to use the Path Flow Estimator (PFE) to estimate current and forecast future traffic demand while taking into account of various field and planning data as modeling constraints. Specifically, two versions of PFE are developed: a base year PFE for estimating the current network traffic conditions using field data and planning data, if available, and a future year PFE for predicting future network traffic conditions using forecast planning data and the estimated base year origin–destination trip table as constraints. In the absence of travel survey data, the proposed method uses similar data (traffic counts and land use data) as a four-step model for model development and calibration. Since the Institute of Transportation Engineers (ITE) trip generation rates and Highway Capacity Manual (HCM) are both utilized in the modeling process, the analysis scope and results are consistent with those of common traffic impact studies and other short-range, localized transportation improvement programs. Solution algorithms are also developed to solve the two PFE models and integrated into a GIS-based software called Visual PFE. For proof of concept, two case studies in northern California are performed to demonstrate how the tool can be used in practice. The first case study is a small community of St. Helena, where the city’s planning department has neither an existing travel demand model nor the budget for developing a full four-step model. The second case study is in the city of Eureka, where there is a four-step model developed for the Humboldt County that can be used for comparison. The results show that the proposed approach is applicable for small communities with limited resources.     

Retrospect and prospect for subarea travel demand modeling: an empirical study

Abstract

At present, customized subarea models have been widely used in local transportation planning throughout the USA. A subarea model's biggest strengths lie in its more detailed and accurate modeling outputs which better meet local planning requirements. In addition, a subarea model can substantially reduce database size and model running time. In spite of these advantages, subarea models remain quite weak in modeling transit projects, smart growth measures, air quality conformity, and other areas. In addition to evaluating subarea models, this paper uses the Irvine Transportation Analysis Model (ITAM) as an empirical case of subarea model to illustrate the remedial procedures in maintaining its consistency with the regional model of the Orange County Transportation Analysis Model (OCTAM). Looking into the future, subarea models face both opportunities and challenges. More GIS applications, travel surveys, micro-simulation software utilization, and modeling improvements are expected to be incorporated into the subarea modeling process.     

A planning methodology for intelligent urban transportation systems

Recent developments in intelligent transportation systems pose new challenges and opportunities for urban transportation planning. To meet these challenges and to exploit these opportunities, a framework for a new transportation planning methodology has been developed. The methodology operates in a computer environment, called PLANiTS (Planning and Analysis Integration for Intelligent Transportation Systems), designed to facilitate the entire planning process form problem identification, through idea generation and analysis, on to prioritization and programming. To assist in problem identification, PLANiTS provides graphic representation of current conditions, including traffic, air pollution, accidents, and projections of future conditions. A computerized knowledge base, containing information about possible strategies and their effects, and a model base, containing transportation and other analysis models, are used to guide the user in identifying potentially effective strategies and performing the appropriate analysis. To facilitate the use of these tools, PLANiTS provides computer support of group processes such as brainstorming, deliberation, and consensus seeking. PLANiTS is designed for use in urban transportation planning at the local, regional, and state levels; it is intended to support a variety of participants in the planning process including transportation professionals, decision makers in transportation agencies (often local elected officials), citizens, and interest groups. Recognizing that transportation planning is essentially a deliberative, political process, PLANiTS is designed to inform and facilitate, but not replace, the political decision-making process.     

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.     

Characterizing the fragmentation level of Italian’s National Parks due to transportation infrastructures

In the last decades, due to the population increase and the relative need of new land to cultivate, expand urban centers and develop transportation networks, most of the Italian natural protected areas are subject to different typologies of human pressures that generally cause habitat fragmentation. This process represents a major concern for biodiversity conservation and a key driver of species loss.The main purpose of this paper was to investigate levels of natural habitat fragmentation due to roads and railways networks in the Italian National Parks (INP_S) through the use of an Infrastructural Fragmentation Index (IFI).All the operations (geospatial analysis, image classification, and fragmentation analysis) were performed using a Geographic Information System (GIS) software for elaborating a national database. The obtained results include an IFI value for each natural territorial unit inside any INP. Moreover, in order to highlight which are the INP_S characterized by higher infrastructural fragmentations, an IFI weighted mean was calculated for each INP. These results represent important indicators for the prioritization of biodiversity conservation interventions and the planning of a INP_S sustainable management.     

Integrated modeling of urban hierarchy and transportation network planning

A major problem addressed during the preparation of spatial development plans relates to the accessibility to facilities where services of general interest such as education, health care, public safety, and justice are offered to the population. In this context, planners typically aim at redefining the level of hierarchy to assign to the urban centers of the region under study (with a class of facilities associated with each level of hierarchy) and redesigning the region’s transportation network. Traditionally, these two subjects – urban hierarchy and transportation network planning – have been addressed separately in the scientific literature. This paper presents an optimization model that simultaneously determines which urban centers and which network links should be promoted to a new level of hierarchy so as to maximize accessibility to all classes of facilities. The possible usefulness of the model for solving real-world problems of integrated urban hierarchy and transportation network planning is illustrated through an application to the Centro Region of Portugal.     

A GIS‐based traffic analysis zone design: technique

The main purpose of this paper is to develop an efficient method to design traffic analysis zones (TAZs), which is necessary for implementing a planning process with Geographic Information System (GIS) for Transportation (GIS‐T), using statistical spatial data analyses and GIS technology. The major roles of GIS in this method are: (1) to produce basic spatial units (BSUs) with topological data structure; (2) to integrate various procedures during the TAZ generation including computer program routines; and (3) to visualize the output of each TAZ generation. One of the most significant reasons for obtaining well‐defined TAZs is the fact that they are defined at the outset of transportation demand modeling, used from trip generation to trip assignment, and will ultimately affect transportation policy decisions.

Toward obtaining well‐defined TAZs, this paper concentrates on two important constraints: homogeneity and contiguity. Iterative partitioning technique is adopted to promote the optimum homogeneity of generated TAZs, while a contiguity checking algorithm is developed to ensure contiguous TAZs are generated by the iterative partitioning technique.     

A combined land use-transportation model when zonal travel demand is endogenously determined

A combined transportation-land use model is proposed in this paper. Unlike other existing urban land use and transportation planning models in which a “fixed demand” for services is assumed to be known at the zonal level of an urban area, zonal travel demand is endogenously determined together with link congestion costs, optimal amounts of production and resulting efficient densities of land uses, once the transportation network is given. Some characteristics of alternative solutions are demonstrated. The proposed model represents progress over previous efforts in combining land use-transportation problems since the travel choice as to origin, destination and routes as well as amounts of goods to be produced at the optimal density of land uses are integrated into a consistent mathematical programming framework.     

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.     

Planning of integrated transit network for bus and LRT

An integrated approach is suggested for the planning and evaluation of mass transport systems which includes a bus network and LRT/RTS in urban areas. This approach involves a simplified procedure for determining mass transit demand, bus route network generation and evaluation, light or rapid transit corridor identification and its patronage determination in the presence of bus networks. Scheduling of a mass transportation system based on marginal ridership concept is also suggested for a given fleet size. All the three major components (demand estimation, route network generation and scheduling) iterate and interact each other with a feedback mechanism for the desired optimal solution in terms of performance indicators. Necessary interactive software packages for all the above subsystems have been developed.     

Evaluating the feasibility of a passive travel survey collection in a complex urban environment: Lessons learned from the New York City case study

The combination of increasing challenges in administering household travel surveys and advances in global positioning systems (GPS)/geographic information systems (GIS) technologies motivated this project. It tests the feasibility of using a passive travel data collection methodology in a complex urban environment, by developing GIS algorithms to automatically detect travel modes and trip purposes. The study was conducted in New York City where the multi-dimensional challenges include urban canyon effects, an extreme dense and diverse set of land use patterns, and a complex transit network. Our study uses a multi-modal transportation network, a set of rules to achieve both complexity and flexibility for travel mode detection, and develops procedures and models for trip end clustering and trip purpose prediction. The study results are promising, reporting success rates ranging from 60% to 95%, suggesting that in the future, conventional self-reported travel surveys may be supplemented, or even replaced, by passive data collection methods.     

The sequenced activity mobility simulator (SAMS): an integrated approach to modeling transportation, land use and air quality

The persistence of environmental problems in urban areas and the prospect of increasing congestion have precipitated a variety of new policies in the USA, with concomitant analytical and modeling requirements for transportation planning. This paper introduces the Sequenced Activity-Mobility Simulator (SAMS), a dynamic and integrated microsimulation forecasting system for transportation, land use and air quality, designed to overcome the deficiencies of conventional four-step travel demand forecasting systems. The proposed SAMS framework represents a departure from many of the conventional paradigms in travel demand forecasting. In particular, it aims at replicating the adaptative dynamics underlying transportation phenomena; explicitly incorporates the time-of-day dimension; represents human behavior based on the satisficing, as opposed to optimizing, principle; and endogenously forecasts socio-demographic, land use, vehicle fleet mix, and other variables that have traditionally been projected externally to be input into the forecasting process.     

Comprehensive regional modeling for long-range planning: linking integrated urban models and geographic information systems

This study demonstrates the sequential linking of two types of models to permit the comprehensive evaluation of regional transportation and land use policies. First, we operate an integrated urban model (TRANUS), which represents both land and travel markets with zones and networks. The travel and land use projections from TRANUS are outlined, to demonstrate the general reasonableness of the results, as this is the first application of a market-based urban model in the US. Second, the land use projections for each of the 58 zones in the urban model were fed into a Geographic Information System (GIS)-based land allocation model, which spatially allocates the several land uses within each zone according to simple accessibility rules. While neither model is new, this is one of the first attempts to link these two types of models for regional policy assessments. Other integrated urban models may be linked to other GIS land allocation models in this fashion. Pairing these two types of models allows the user to gain the advantages of the urban models, which represent spatial competition across a region and produce measures of user welfare (traveler and locator surplus), and the advantages of the GIS land allocation models, which produce detailed land use maps that can then be used for environmental impact assessment.     

Transportation modeling: Lessons from the past and tasks for the future

In spite of the recent progress made in household activity analysis and travel budget studies, urban transportation modeling still remains a “not-too-well developed” research field. There are conflicting theories, analysis units are not uniform, terms are not precisely defined, basic studies of sub-systems involved are not yet completed, and many models lack behavioral background as well as basic attributes such as simplicity, sensitivity, compatibility, transferability and forecasting ability. Gaps in methodology may be partially responsible for this situation. There is an urgent need for simple, yet not primitive, easily applicable urban transportation models which can respond to the technical needs of planners and engineers. Lessons from the past, as well as experiences from other disciplines, suggest that future research should concentrate on: (1) new, “unconventional” approaches based on systematic, basic studies of all sub-systems involved; (2) proper definition and stratification of an analysis unit; (3) revision and unification of definitions, classifications, etc., in order to improve the behavioral background of the models; (4) dynamic rather than static approaches, able to describe feedbacks between transportation and land-use as well as between transportation demand and supply; (5) interrelations between subsequent sub-models, particularly between car availability, trip generation and modal split; (6) developing models which are not only sensitive to transportation policies but also to other local policies (e.g. land use, city development, social, etc.).     

A GIS-based planning approach to locating urban rail terminals

This paper develops a flexible GIS-based methodology for evaluating the potential locations of terminal park-and-ride facilities along urban rail lines. The methodology differs from political-based approaches and traditional travel demand modeling in its use of an objective measure of accessibility to gage the suitability of a site. The methodology begins by constructing an index of derived demand for rail usage based on the local demographics. Principal component analysis (PCA) is used as a means of constructing an index of derived demand consistent with other passenger surveys. Next, trade areas or commutersheds are calculated for each candidate park-and-ride location based on realistic measures of accessibility and network based drive times, taking into account competition among candidates for riders. Following the analysis, the candidate locations and their commutersheds are delineated and visualized in the GIS environment. In summary, application of this method produces a site-specific suitability index that may be used to rank and compare potential park-and-ride locations. We illustrate how our approach fits within the context of the larger-scale corridor study as a complimentary means of refining the location of urban rail stations. The analysis uses the proposed rail system for Columbus Ohio as a case study. This revised version was published online in June 2006 with corrections to the Cover Date.