Eric I. Pas

Socio-demographics, activity participation and travel behavior

This paper describes the development, estimation and interpretation of a model relating socio-demographics, activity participation (time use) and travel behavior. A complex set of interrelationships among the variables of interest is estimated simultaneously using the structural equation modeling methodology, with activity participation (time allocated to a number of activity types) and travel behavior endogenous to the model. The research reported here shows that complex relationships among socio-demographics, activity participation and travel behavior exist and can be captured by the structural equation model structure. Specifically, the results show that we can explain travel behavior better by including activity participation endogenously in the model, than through socio-demographics alone. Furthermore, the results reported here reveal the relationships between in-home and out-of-home activity participation and travel behavior. Lastly, the research shows that by examining the direct, indirect and total effects in the model system, we are able to better capture and understand the relationships among socio-demographics, activity participation and travel behavior. ©

Weekly travel-activity behavior

This paper describes a methodology for the analysis of multiday travel-activity patterns in which each multiday travel-activity pattern is characterized as a set of daily travel-activity pattern types. This approach facilitates identification of general weekly travel-activity pattern types as well as examination of the relationships between weekly travel-activity behavior and the hypothesized determinants of that behavior. This methodology is an extension of one developed previously by the author for analysis of daily travel-activity patterns. The methodology is applied to a sample of 112 weekly travel-activity patterns of employed people.The paper develops and examines a number of hypotheses concerning weekly and daily travel-activity patterns and their determinants. The empirical results show that general classes of weekly travel-activity behavior can be identified and that these classes of behavior are related to particular individual and household sociodemographic characteristics. The results also show that, for employed people, daily travel-activity pattern type selection is independent of the day-of-the-week, although there appear to be some specific day-of-week differences in the data used in this research. Further, the empirical results do not reject the hypothesis that the selection of daily travel-activity behavior in a two-stage process (selection of weekly behavior followed by conditional selection of daily behavior), is not influenced by socio-demographic characteristics beyond their impact on selection of the weekly pattern type.

TIME-USE DATA, ANALYSIS AND MODELING: TOWARD THE NEXT GENERATION OF TRANSPORTATION PLANNING METHODOLOGIES

This paper argues that transportation planning methodologies must be built on the central thesis of the activity-based approach to travel demand modeling, namely, that travel is a derived demand that reflects peoples desire and need to participate in activities. The paper discusses why this foundation for transportation planning methodologies is necessary to address contemporary planning and policy analysis issues. The paper also argues that the introduction of time-use data, analysis and modeling is a key element in the development of the next generation of transportation planning methodologies. Following a brief review of time-use studies, the paper discusses a number of planning and policy analysis areas in which time-use data will be of particular value, including the evaluation of induced or suppressed travel demand. The concepts advanced in the paper are illustrated with two brief numerical examples. These examples show how model systems based on time-use data can be used to (i) estimate the number of induced trips that would result from a reduction in commute travel time, and (ii) evaluate the impacts of alternative transportation improvement projects.

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.

An Activity-Based Microsimulation Analysis of Transportation Control Measures

This paper describes the development and application of an activity-based microsimulation model system capable of simulating changes in individual travel patterns in response to a transportation control measure. A unique activity-based time use survey was conducted to obtain information on peoples activity and travel patterns and their likely behavioral adjustment in response to various transportation control measures. This paper describes the survey and the use of the ensuing data set in estimating various components of the simulator, called AMOS. The first application in the Washington DC area demonstrated the capabilities of AMOS as a transportation policy analysis tool. Sample results from the Washington DC demonstration are presented.

State of the art and research opportunities in travel demand: Another perspective

The objective of this brief paper is to extend and enhance the state-of-the-art review and discussion of research opportunities in travel demand analysis prepared by Horowitz. The paper is organized as follows. First, a brief overview is presented of the state of the art in one stream of travel demand analysis research; namely, the activity-based approach. Second, a number of research opportunities and needs in travel demand analysis are identified and discussed. Third, data needs for advancing the state of the art in travel demand analysis are examined. Fourth, some concluding thoughts are presented. For paper by Horowitz see IRRD 287445.

Assessing the true cost of landfills

The most common means for disposing of municipal solid waste is burial in a sanitary landfill. However, many landfill owners significantly underestimate the total cost of landfill disposal by considering only land and operating costs, ignoring external physical and social costs associated with landfills. This paper proposes an approach to estimating (in monetary terms) the external costs arising from the development and operation of a landfill. All cost information is based on typical U.S. landfill cost structures. The approach is illustrated by applying it to a case study of a proposed landfill in Durham, North Carolina (U.S.A.). This case study demonstrates that the method can be applied easily and yields reasonable results.

Market segmentation analysis of potential inter-city rail travelers

This paper reports on one aspect of a study conducted to support the analysis of the performance of a proposed intercity rail passenger service in the Piedmont region of North Carolina. In particular, this paper describes a market segmentation study of potential rail travelers on the basis of the responses of 333 participants in a computer-based, mall-intercept, market research survey.The paper overviews the design and implementation of the computer-based survey of potential rail travelers and discusses the approach used in the identification and interpretation of the market segments. The five identified traveler groups are characterized and the implications of the market segmentation results are discussed. These five segments are: (1) functional traveler, (2) day tripper, (3) train lover, (4) leisure-hedonic traveler, and (5) family traveler.The five groups identified in the market segmentation analysis provide a rich description of the potential rail market in the study corridor. The composition and characteristics of these groups indicate that the intercity rail travel market may have a complex structure that would be masked by the traditional business/non-business dichotomy. The characterization of the intercity rail travel market by the five identified segments provides rail service managers with very useful information for service planning and marketing.

Generating alternative solutions for dynamic programming-based planning problems

Abstract An approach is developed for generating alternative near-optimal solutions for dynamic programming-based planning problems. The proposed methodology improves on an existing approach in three respects. First, computational efficiencies are achieved by recomputing the optimal policy for only a subset of the total number of stages. Second, the approach can be easily structured such that there is increased variation in alternatives within the first stages. Third, the maximum allowable difference in objective function value between alternative solutions can be explicitly stated by the user. A hypothetical shortest route problem is used to illustrate the characteristics of the proposed approach. Results are also presented for a facility capacity planning problem in the municipal solid waste management area.

Planning Hazardous Waste Reduction and Treatment Strategies: an Optimization Approach

An industry faced with escalating off-site waste disposal costs will often consider increasing on-site waste treatment capacity or the implementation of a waste reduction program. Waste reduction program options include input and process changes that decrease waste quantity and waste toxicity. Tradeoffs between capital investment and economy-of-scale in development are required, and will depend on the industry and the current level of waste reduction. A dynamic programming model is developed that allows the investigation of waste reduction and treatment strategies for industries in a changing regulatory and economic environment. The applicability of the optimization approach to industrial waste generators is illustrated through a hypothetical but representative industrial waste management example.