Changes in perceived travel cost and time for the work trip during a period of increasing gasoline costs

This study was designed to examine the relationship between actual and perceived values of cost and time for the work trip and to examine how perceptions have changed over a period of dramatically increased travel costs. Variations in the relationship between perceived and actual values were examined as a function of situational and attitudinal variables. Two telephone surveys were conducted one year apart (Fall 1978 and Fall 1979). On the next working day following a survey, a research assistant recreated the respondent's work trip, recorded time values and used distance measures, car type information and parking costs to compute travel cost. The first survey revealed that most auto users were unable to articulate dollars-and-cents driving costs for the work trip, but auto users in the second survey were able to provide fairly accurate cost estimates. Dramatic changes in fuel prices between surveys is probably the main reason for the change in driving cost awareness. Auto users were also asked to rate relative costs of driving a car compared to using the bus for the work trip. These ratings showed that auto users tended to underestimate driving costs relative to bus costs, but this tendency decreased from the first to the second time period. Commuters in all modal groups at both time periods tended to overestimate travel times. Perception of travel time varied as a function of mode, perceived comfort (for car users), and perceived convenience and number of transfers (for bus users).To whom correspondence should be addressed.     

Synergies between Adjacent Beach-Nourishing Communities in a Morpho-Economic Coupled Coastline Model

Beach “nourishment” consists of placing sand on an eroding beach. The widened beach provides increased storm protection to adjacent structures and improved recreational benefits, but is most often transient, requiring on-going, repeated nourishment episodes. Numerical models of beach nourishment typically address such questions as how long a widened beach will last; economic models compare the benefits and costs of preserving a stretch of beach without regard to its geomorphic evolution. Neither have addressed the physical nor economic interactions between adjacent nourishing communities. Here, we couple a numerical model of coastline evolution and a cost-benefit model of beach nourishment, allowing adjacent communities to make dynamic nourishment decisions. Beach nourishment benefits adjacent communities both “updrift” and “downdrift.” The total amount of money spent on nourishment activities can decrease by as much as 25% when adjacent communities both conduct on-going nourishment projects, as opposed to the case where each community nourishes in isolation.     

Can agents measure up? A comparative study of an agent-based and on-line optimization approach for a drayage problem with uncertainty

Experiments studying the behavior of agent-based methods over varying levels of uncertainty in comparison to traditional optimization methods are generally absent from the literature. In this paper we apply two structurally distinct solution approaches, an on-line optimization and an agent-based approach, to a drayage problem with time windows under two types of uncertainty. Both solution approaches are able to respond to dynamic events. The on-line optimization approach utilizes a mixed integer program to obtain a feasible route at 30-s intervals. The second solution approach deploys agents that engage in auctions to satisfy their own objectives based on the information they perceive and maintain locally. Our results reveal that the agent-based system can outperform the on-line optimization when service time duration is highly uncertain. The on-line optimization approach, on the other hand, performs competitively with the agent-based system under conditions of job-arrival uncertainty. When both moderate service time and job-arrival uncertainties are combined, the agent system outperforms the on-line optimization; however, in the case of extremely high combined uncertainty, the on-line optimization outperforms the agent-based approach.     

Truck backhauling on two terminal networks

Truck backhauling reduces empty truck-miles by having drivers haul loads on trips back to their home terminal. This paper 1) examines the impact on backhauling opportunities of terminal locations and directional imbalances in the flow of freight from the terminals, and 2) develops a method for determining which truckloads should be backhauled. Backhauling is studied for two terminals sending full truckloads to many customers under steady-state conditions. This research develops two backhauling models. The first is a continuous model that makes simplifying assumptions about customer locations and travel distances. It results in formulae showing that 1) savings from backhauling increase at a decreasing rate as the directional flow of freight between two terminals becomes more balanced and 2) backhauling is an important, but often ignored, factor in terminal (e.g. trucking terminal, warehouse, or plant) location and supplier selection decisions. The second model is a more general discrete model that determines which loads should be backhauled to minimize empty truck-miles.     

Behavioral analysis and transportation planning: Inputs to transit planning

The purpose of this paper is to discuss various types of behavioral data of potential relevance to transit planning. In particular a distinction is drawn between behavorial information regarding feelings, attitudes, opinions, and the like and more sophisticated types of data dealing with individuals' intentions to respond in certain ways given certain configurations of stimuli (transportation variables). The former is shown to be an important input to incremental planning, i.e., where information as to system performance is desired. The latter is shown to be critical to decisions regarding manipulations of transit system parameters, i.e., where knowledge of the outcome of manipulating system parameters is desired.A methodological example as to how the first type of data — informational level data — can be collected and utilized in system planning is presented. Specifically, data collected along the lines of traditional attitude surveys is collected in an attempt to monitor changes in public satisfaction with the Iowa City, Iowa, bus system before and after major system innovations. Implications of the collection and analytical procedures are discussed.This report was produced as part of a program of research and training in urban transportation sponsored by the Urban Mass Transportation Administration of the Department of Transportation.     

Information Presentation of Coastal Morphological Change: Potential Implications for Perceptions of Climate Change Impacts

Visual imagery of costal morphological change processes must be accompanied by supporting information to make change processes understandable. We explored the influence of supporting information (graphs and numeric values) on perceptions of coastal morphological change processes through an experiment delivered to coastal recreationists. Supporting information was presented alongside four imagery types: human perspective digital elevation models (DEMs), human perspective digital photographs, aerial views of DEMs and aerial photography. We found neither the use of graphs nor numeric values influenced respondents' perceptions of coastal environmental change. However, perceptions varied significantly across imagery type; human perspective digital photographs and aerial photographs yielded higher ratings compared to human perspective DEMs and aerial views of DEMs. The results suggest supporting information representing increasingly severe rates of beach erosion and shoreline movement does not translate into perceptions of increasingly dramatic geophysical processes; this is consistent with previous empirical findings. The results also suggest individuals perceive coastal change processes as more severe when those processes are presented through photographs, particularly aerial photographs. Scientists, educators and coastal land use managers struggling to communicate the magnitude and severity associated with coastal geophysical processes are advised to use comparative aerial photography when possible.     

A composite attitude-behavior model of traveler decision making

A general model for the behavioral analysis of traveler decision making is described. The model is one which blends research in human information processing with probabilistic choice theory. The model is used as a basis for discussing two studies of grocery store choice behavior. In these studies, algebraic models of individuals' grocery store preferences which are derived using controlled hypothetical choice situations are related to real-world choice behavior. Results show a high monotonic correspondence between laboratory and real-world behavior. Implications of the research for existing approaches to behavioral modeling are described.     

A sequential approach to exploiting the combined strengths of SP and RP data: Application to freight shipper choice

The possibility of and procedure for pooling RP and SP data have been discussed in recent research work. In that literature, the RP data has been viewed as the yardstick against which the SP data must be compared. In this paper we take a fresh look at the two data types. Based on the peculiar strengths and weaknesses of each we propose a new, sequential approach to exploiting the strengths and avoiding the weaknesses of each data source. This approach is based on the premise that SP data, characterized by a well-conditioned design matrix and a less constrained decision environment than the real world, is able to capture respondents' tradeoffs more robustly than is possible in RP data. (This, in turn, results in more robust estimates of share changes due to changes in independent variables.) The RP data, however, represent the current market situation better than the SP data, hence should be used to establish the aggregate equilibrium level represented by the final model. The approachfixes the RP parameters for independent variables at the estimated SP parameters but uses the RP data to establish alternative-specific constants. Simultaneously, the RP data are rescaled to correct for error-in-variables problems in the RP design matrixvis-à- vis the SP design matrix. All specifications tested are Multinomial Logit (MNL) models.The approach is tested with freight shippers' choice of carrier in three major North American cities. It is shown that the proposed sequential approach to using SP and RP data has the same or better predictive power as the model calibrated solely on the RP data (which is the best possible model for that data, in terms of goodness-of-fit figures of merit), when measured in terms of Pearson's Chi-squared ratio and the percent correctly predicted statistic. The sequential approach is also shown to produce predictions with lower error than produced by the more usual method of pooling the RP and SP data.     

Behavioural intentions as predictors of very specific behaviour

This paper proposes an alternative approach to understanding travel behaviour —the study of behavioural intentions. The communality of this and the revealed behaviour approach are outlined and the use of controlled experimental methods illustrated in an analysis of empirical data on behavioural intentions of citizens with respect to changes in the levels of transport service, and the introduction of an area licensing scheme for travel in a central city area in Australia.This research was completed while Jordan Louviere was at Cambridge Systematics Inc., Boston, Massachusetts, U.S.A.