An exploratory analysis of joint-activity participation characteristics using the American time use survey

This paper presents a detailed exploratory analysis of joint activity participation characteristics using the American Time Use Survey (ATUS). As a very large nationwide survey that explicitly elicited information on both household and non-household companions for each activity episode, the ATUS is ideally suited for this analysis. Several intuitive and interesting results are obtained. Joint episodes are found to be of longer durations, significantly likely to take place at the residence of other people, and often confined to certain time periods of the weekday. In addition, important differences in these characteristics are also observed based on activity purpose, companion type, and the day of the week. These findings are intended to provide the basis for the justification of detailed collection of joint activity–travel participation information in household activity–travel surveys, and also as a stimulant for further empirical analysis and modeling of joint activity participation behavior.

Urban form,travel time,and cost relationships with tour complexity and mode choice

The primary purpose of this study was to investigate how relative associations between travel time, costs, and land use patterns where people live and work impact modal choice and trip chaining patterns in the Central Puget Sound (Seattle) region. By using a tour-based modeling framework and highly detailed land use and travel data, this study attempts to add detail on the specific land use changes necessary to address different types of travel, and to develop a comparative framework by which the relative impact of travel time and urban form changes can be assessed. A discrete choice modeling framework adjusted for demographic factors and assessed the relative effect of travel time, costs, and urban form on mode choice and trip chaining characteristics for the three tour types. The tour based modeling approach increased the ability to understand the relative contribution of urban form, time, and costs in explaining mode choice and tour complexity for home and work related travel. Urban form at residential and employment locations, and travel time and cost were significant predictors of travel choice. Travel time was the strongest predictor of mode choice while urban form the strongest predictor of the number of stops within a tour. Results show that reductions in highway travel time are associated with less transit use and walking. Land use patterns where respondents work predicted mode choice for mid day and journey to work travel.

Introduction: Habitual travel choice

In this introduction to the special issue on habitual travel choice, we provide a brief account of the role of habit in travel behaviour, discuss more generally what habitual choice is, and briefly review the issues addressed in the solicited papers. These issues include how habitual travel behaviour should be measured, how to model the learning process that makes travel choice habitual, and how to break and replace car-use habits.     

Subsidy and public transit performance: A factor analytic approach

The need to measure and evaluate transit system performance has led to the development of numerous performance indicators. However, depending upon the indicator, we oftentimes reach different conclusions regarding transit system performance. The research reported in this paper uses factor analytic methods to generate a set of underlying attributes (factors) that capture the performance of public transit systems in Indiana. Similar to what is reported in the literature, this study finds three attributes that best describe transit system performance: efficiency, effectiveness, and overall performance. Based upon systemsÕ factor scores, the study finds that systems scoring highly on one attribute generally perform well on the remaining attributes. Further, there is an inverse relationship between system performance and subsidies, a finding that supports performance based subsidy allocations.     

A frequency-based maritime container assignment model

This paper transfers the classic frequency-based transit assignment method of Spiess and Florian to containers demonstrating its promise as the basis for a global maritime container assignment model. In this model, containers are carried by shipping lines operating strings (or port rotations) with given service frequencies. An origin–destination matrix of full containers is assigned to these strings to minimize sailing time plus container dwell time at the origin port and any intermediate transhipment ports. This necessitated two significant model extensions. The first involves the repositioning of empty containers so that a net outflow of full containers from any port is balanced by a net inflow of empty containers, and vice versa. As with full containers, empty containers are repositioned to minimize the sum of sailing and dwell time, with a facility to discount the dwell time of empty containers in recognition of the absence of inventory. The second involves the inclusion of an upper limit to the maximum number of container moves per unit time at any port. The dual variable for this constraint provides a shadow price, or surcharge, for loading or unloading a container at a congested port. Insight into the interpretation of the dual variables is given by proposition and proof. Model behaviour is illustrated by a simple numerical example. The paper concludes by considering the next steps toward realising a container assignment model that can, amongst other things, support the assessment of supply chain vulnerability to maritime disruptions.     

Simulating the impacts of household travel on greenhouse gas emissions,urban air quality,and population exposure

This paper establishes a link between an activity-based model for the Greater Toronto Area (GTA), dynamic traffic assignment, emission modelling, and air quality simulation. This provides agent-based output that allows vehicle emissions to be tracked back to individuals and households who are producing them. In addition, roadway emissions are dispersed and the resulting ambient air concentrations are linked with individual time-activity patterns in order to assess population exposure to air pollution. This framework is applied to evaluate the effects of a range of policy interventions and 2031 scenarios on the generation of vehicle emissions and greenhouse gases in the GTA. Results show that the predicted increase of approximately 2.6 million people and 1.3 million jobs in the region by 2031 compared to 2001 levels poses a major challenge in achieving meaningful reductions in GHGs and air pollution.     

Design and evaluation of an integrated inventory and transportation system

This paper proposes the adoption of an integrated inventory and transportation system (IITS) to minimize the total costs of inventory and transportation. A non-linear programing is developed by analyzing transportation and inventory costs with one supplier and many retailers in the distribution environment. The paper compares the proposed model with the traditional approach in computing total costs with numerical data. The results indicate that the total costs can be optimized by adopting integrated programing rather than the traditional approach, along with achieving improved customer service levels. In particular, sensitivity analysis is applied to determine the performance of the IITS under various transportation costs, holding costs and shortage costs. It shows that the transportation cost per unit is most sensitive in the proposed model. In this situation, the IITS is more effective for cost saving when set-up cost, holding and shortage costs are high, but is less effective for situations involving high per-unit transportation costs.     

Evaluation of general aviation management at Denver Stapleton airport

The potential benefits of general aviation management at a major airport is examined in this paper. The three general aviation management techniques investigated are volume reduction, runway segregation and time restriction.

First, a methodology for analyzing these techniques is discussed. The various effects on each user group are quantified for economic comparison between each management technique attempted. A computer simulation model was used to measure the delay effects. Then, these techniques are applied to Denver Stapleton Airport to measure their effects in present and future scenarios.

The results show that the best general aviation management technique is volume restriction. The use of peak‐hour pricing mechanism provided better results than random rejection, particularly if only a small degree of diversion is desired. The construction of a new general aviation runway provided equivalent results to the best technique tested.     

Isolating high-priority metro and feeder bus transfers using smart card data

Fixed-rail metro (or ‘subway’) infrastructure is generally unable to provide access to all parts of the city grid. Consequently, feeder bus lines are an integral component of urban mass transit systems. While passengers prefer a seamless transfer between these two distinct transportation services, each service’s operations are subject to a different set of factors that contribute to metro-bus transfer delay. Previous attempts to understand transfer delay were limited by the availability of tools to measure the time and cost associated with passengers’ transfer experience. This paper uses data from smart card systems, an emerging technology that automatically collects passenger trip data, to understand transfer delay. The primary objective of this study is to use smart card data to derive a reproducible methodology that isolates high priority transfer points between the metro system and its feeder-bus systems. The paper outlines a methodology to identify transfer transactions in the smart card dataset, estimate bus headways without the aid of geographic location information, estimate three components of the total transfer time (walking time, waiting time, and delay time), and isolate high-priority transfer pairs. The paper uses smart card data from Nanjing, China as a case study. The results isolate eight high priority metro-bus transfer pairs in the Nanjing metro system and finally, offers several targeted measures to improve transfer efficiency.     

One city,three models: comparison of land‐use/transport policy simulation models for Dortmund

The paper reports on simulation experiments conducted by the International Study Group on Land‐Use/Transport Interaction (ISGLUTI) for the metropolitan region of Dortmund in the Federal Republic of Germany. Three land‐use/transport simulation models were applied to the Dortmund region: the DORTMUND model developed at the University of Dortmund, the LILT model being used at University College London and the MEPLAN package developed by Marcial Echenique & Partners in Cambridge. The three models are briefly characterized and their ex‐post forecasts are compared with the actual development of the region. The final section of the paper compares how the three models respond to a common set of assumptions and policies from the fields of land‐use control, traffic management and transport investment. The differences in model response give insights into the validity of the theoretical foundations and internal structure of the models.