A Copula-Based Joint Model of Commute Mode Choice and Number of Non-Work Stops during the Commute

At the time of publication A. Portoghese, E. Spissu, and I. Meloni were at University of Cagliari, and C.R. Bhat and N. Eluru were at the University of Texas at Austin.In this paper, in the spirit of a tour-based frame of analysis, we examine the commute mode choice and the number of non-work stops during the commute. Understanding the mode and activity stop dimensions of weekday commute travel is important since the highest level of weekday traffic congestion in urban areas occurs during the commute periods. The paper employs a copula-based joint multinomial logit – ordered modeling framework in which commute mode choice is modeled using a multinomial logit formulation and the number of commute stops is modeled using an ordered response formulation. The data used in this study are drawn from the “Time use” multipurpose survey conducted between 2002 and 2003 by the Turin Town Council and the Italian National Institute of Statistics (ISTAT) in the Greater Turin metropolitan area of Italy. The results highlight the importance of accommodating the inter-relationship between commute mode choice and commute stops behavior. The results also point to the stronger effect of household responsibilities and demographic characteristics in the Italian context compared to the US context.Civil, Architectural, and Environmental Engineerin

A model of the dynamic process of time allocation to discretionary activities

This paper proposes an activity-based methodology for representing the allocation of time to discretionary activities during their programming and scheduling, based on the premise that both phases are to be considered contextually and two aspects of the same decision process. The aim of this work is to extend the treatment of utility maximization associated with carrying out two activities to J activities, so as to be able to segregate the time spent traveling from the total amount of time dedicated to out-of-home activities. The global structure of the model takes the form of a nested Tobit, particularly suited for reproducing a sequence of coupled choices. The first choice concerns dividing up overall discretionary time between activities inside and outside the home, then the second choice, subordinate to the first, involves rebudgeting the time between in- and outof- home activities and trips. Thus the proposed model enables us to analyze the effects that each explicative variable exerts on trips segregated from activities outside the home and, last, during demand forecasting, the direct consequences of allocating discretionary time to trips following changes to an individual’s time budget. A database created from a large-scale time-use survey (ISTAT 1988–1991) has been used for calibrating the model coefficients

The Effect of Personal Cap-and-Trade Mileage Policies on Individual Activity-Travel Patterns: The Activity Locator Project

At the time of publication I. Meloni and E. Spissu were at the University of Cagliari; and C. Bhat was the University of Texas at Austin.The objective of this work is to contribute to the debate on sustainable policies aimed at reducing personal carbon emissions from the transport sector. The proposed research describes an experiment extending the cap-and-trade system, employed in manufacturing-based emission curb programs, to Voluntary Travel Behavioral Change (VTBC) program. In paricular, a VTBC program is proposed that relies on opportune changes in individual activity-travel patterns after observing actual behavior recorded using an innovative device. In this regard, the methodology developed includes: (1) the design of a new behavioral strategy called "Cap and Save" and (2) the implementation of a new device for daily individual activity travel patterns collection called "Activity Locator". The two aspects are closely interrelated, since behavioral strategies are usually difficult to evaluate; indeed, data regarding individual behavior before and after policy intervention are rarely collected. From July to October 2009, both the Activity Locator and the Cap and save were implemented during a two-week survey involving a group of students of the University of Cagliari (Italy). The students' activity-travel behavior over two survey weeks and their feedback on both the Activity Locator device and Cap and save strategy were then analyzed.Civil, Architectural, and Environmental Engineerin

A copula-based joint multinomial discrete–continuous model of vehicle type choice and miles of travel

Vehicle type choice, Vehicle usage, Vehicle miles of travel, Copula-based approach, Discrete–continuous choice modeling, Travel behavior, Greenhouse gas emissions, Transportation energy consumption,

The influence of activity-travel patterns on the success of VTBC

The objective of this work is to verify how the complexity of activity-travel patterns may influence the propensity to change travel behaviour in the context of a Voluntary Travel Behaviour Change (VTBC) programme. Data used in this work was drawn from a VTBC programme implemented in Cagliari, Italy between 2011 and 2012, for promoting the use of an underutilised Light Rail service (LR). A descriptive comparative analysis of activity–travel patterns recorded before and after the delivery of a personalised travel plan was reported. In addition to the descriptive analysis, a panel Probit model is proposed to further understand the influence of complex trip-chaining behaviours on the propensity to change travel behaviours. The results indicate that when individuals are presented with a convenient transport alternative that allows them to flexibly chain their activities, the propensity to use a sustainable mode of transport increases. Abbreviations: ABA: activity – based analysis; AW: after work tour; BW: before work tour; CMS: casteddu mobility styles; CW: complex working day; HWC: home to work commute tour; LR: light rail; NHB: non home based tour; NNW: non work tour; NW: non working day; P&R: park and rider; PP&R: prospective park and rider; PTP: personalised travel plan; SW: simple working day; VTBC: voluntary travel behaviour change; WB: work based tou

Lessons learned from a personalized travel planning (PTP) research program to reduce car dependence

Voluntary travel behavior change programs have been implemented worldwide since the late 1990s at a personal and community level. Most of the now completed programs were commissioned by local authorities to commercial firms, in an attempt to reduce private car use. In this context, the evaluation and review of the reliability of these policy measures have been at the core of most of the debates and studies in this field. In this paper, we describe the lessons learned from a research program funded by the Sardinian Government (Italy), aimed at testing a soft transport policy measure for reducing car dependence. In particular, the work reviews in detail the methodological approach and participants’ feedback on a personalized travel plan (PTP). After implementation of the soft measure, the PTP participants were divided into two groups depending on whether they had reduced car use or not, and separate analyses were conducted to highlight the factors underlying different behavior change decisions. General conclusions regarding the effectiveness of the PTP are beyond the scope of the present study