A review of household dynamic vehicle ownership models: holdings models versus transactions models

Among disaggregate vehicle ownership models, which model the number and/or type of vehicles owned at the household level, one can distinguish holdings models, which deal with the (optimal) household fleet at a single point in time, and transactions models. The latter type of model explains changes to the household fleet, such as replacement and disposal. The paper describes previous attempts at such dynamic models and sketches how a vehicle transactions model could look (as an example we discuss an application to The Netherlands). This includes discussions of transaction probabilities, two-stage budgeting, introducing vehicle quality in the utility functions, and the envisaged model structure and data it could use.     

Exploration of route choice behavior with advanced traveler information using neural network concepts

A model of driver's route choice behavior under advanced traveler information system (ATIS) is developed based on data collected from learning experiments using interactive computer simulation. The experiment subjected drivers to 32 simulated days in which they were to choose between the freeway or a side road. A neural network model is used as a convenient modeling technique in this initial phase of the analysis. The results indicated that most subjects made route choices based mainly on their recent experiences. It was also demonstrated that route choice behaviors are related to the personal characteristics as well as the characteristics of the respective routes. Travel experiences have less effect on the choice of the side road compared to the freeway and the results indicate that the prediction accuracy of the model, the acceptance rate of advice, and the quality of advice are closely correlated. The model developed here was for advice consistently provided at a level of 75 percent accuracy. The paper concludes with a discussion of experimental limitations and suggestions for future research.     

Steady sailing performance of a hybrid-sail assisted bulk carrier

The steady sailing performance of a sail-assisted bulk carrier is investigated utilising towing-tank derived hydrodynamic derivatives and wind tunnel measured aerodynamic properties of the sails and the ship. The aerodynamic characteristics investigated include the ship hull at the fully-loaded draught, the sail–sail interaction effects for two sets of four identical hybrid-sails, and the sail–hull interaction effects for the same two sets of identical sails in the presence of the selected bulk carrier hull-form. This is in addition to lift–drag measurements of single isolated sails of each shape. The form of the two sets of soft sails was rectangular and triangular. This paper is concerned with assessing the benefits of a sail-assisted ship operation, and hence a steady-state rather than complete time-domain integrations of the governing equations are reported. The results of the completed analysis suggest that the benefits of the derived sail generated driving force are greater than the overhead of equipping the ship with a selected system of hybrid-sails. Sail-assisted ships could represent an important contribution to an improving global environment by reducing the demands for a driving force through the propeller.     

A causal analysis of car ownership and transit use

The causal structure underlying household mobility is examined in this study using a sample obtained from the Dutch National Mobility Panel survey. The results indicate that car ownership is strongly associated with mode use, but that it has no influence on weekly person trip generation by household members. Characteristics of mode use are examined through a causal analysis of changes in car ownership, number of drivers, number of car trips, and number of transit trips. It is shown that observed changes in mode use cannot be adequately explained by assuming that a change in transit use influences car use. The finding suggests that the increase in car use, which is a consequence of increasing car ownership, may not be suppressed by improving public transit.     

A model of daily time allocation to discretionary out-of-home activities and trips

This paper presents a model of discrete activity choice and continuous resource allocation which is based on the premise of random utility maximization and which can be conveniently estimated using existing statistical software packages. The model derivation involves virtually no approximations and adheres strictly to the utility maximization concept. The empirical analysis applies the model to the participation choice and resource (time) allocation to nonwork, out-of-home activities by workers. The statistical results show that activity choice and time allocation are governed by the same mechanism as the utilitarian assumptions indicate and support the theoretical framework employed in the model development.     

On the formulation of time-space prisms to model constraints on personal activity-travel engagement

The notion of time-space prisms has often been used in the context of describing activity-travel patterns of individuals. This paper presents a methodology for estimating the temporal vertices of time-space prisms using the stochastic frontier modeling technique. Observed trip starting and ending times are used as dependent variables and socio-economic characteristics and commute characteristics serve as independent variables. The models are found to offer plausible results indicating that temporal vertices of time-space prisms, though unobservable, can be estimated based on temporal characteristics of observed activity-travel patterns. Comparisons of stochastic frontier models of prism vertices and the distributions of prism vertices are presented using two activity data sets collected in the United States – San Francisco and Miami. Differences and similarities in temporal vertex locations are highlighted in the paper.     

An evaluation of activity-based travel analysis

This paper is a review and assessment of the contributions made by activity-based approaches to the understanding and forecasting of travel behavior. In their brief history of approximately a decade, activity-based analyses have received extensive interest. This work has led to an accumulation of empirical evidence and new insights and has made substantial contributions toward the better understanding of travel behavior. However, practical applications of the approach in transportation planning and policy development have been scarce. Based on an analysis of the inherent characteristics of the activity-based approach, a review of recent (after the 1981 Oxford conference) developments, and a synthesis of the findings from past empirical studies, this study attempts to evaluate the contribution made by activity-based analyses and determine the reasons for the limited practical application. Recommendations are made for the future development of activity-based analysis as a science of travel behavior and as a tool in the practice of transportation planning and policy development.     

Analysis of personal action space using a model system with multiple choice structures

The concept of heterogeneity in choice structure is applied in this study to examine individuals’ action space, which is defined in terms of the reported frequencies of visits. A disaggregate model system that predicts the frequency of visits is condensed using a nested logit model with multiple choice structures.