Exploration of Time Use Utility Derived by Older Individuals from Daily Activity–Travel Patterns

2010 ◽  
Vol 2156 (1) ◽  
pp. 111-119 ◽  
Author(s):  
Sarah Elia Ziems ◽  
Karthik C. Konduri ◽  
Bhargava Sana ◽  
Ram M. Pendyala
1997 ◽  
Vol 1607 (1) ◽  
pp. 154-162 ◽  
Author(s):  
Ryuichi Kitamura ◽  
Cynthia Chen ◽  
Ram M. Pendyala

Microsimulation approaches to travel demand forecasting are gaining increased attention because of their ability to replicate the multitude of factors underlying individual travel behavior. The implementation of microsimulation approaches usually entails the generation of synthetic households and their associated activity-travel patterns to achieve forecasts with desired levels of accuracy. A sequential approach to generating synthetic daily individual activity-travel patterns was developed. The sequential approach decomposes the entire daily activity-travel pattern into various components, namely, activity type, activity duration, activity location, work location, and mode choice and transition. The sequential modeling approach offers practicality, provides a sound behavioral basis, and accurately represents an individual’s activity-travel patterns. In the proposed system each component may be estimated as a multinomial logit model. Models are specified to reflect potential associations between individual activity-travel choices and such factors as time of day, socioeconomic characteristics, and history dependence. As an example results for activity type choice models estimated and validated with the 1990 Southern California Association of Governments travel diary data set are provided. The validation results indicate that the predicted pattern of activity choices conforms with observed choices by time of day. Thus, realistic daily activity-travel patterns, which are requisites for microsimulation approaches, can be generated for synthetic households in a practical manner.


Author(s):  
Italo Meloni ◽  
Erika Spissu

The objective of this work is to explore the contribution of daily activity-travel patterns to carbon emissions, and to define the steps for the implementation of an effective behavioural strategy to encourage voluntary travel behavioural changes. This work proposes an extensive review of the most relevant strategies implemented to achieve sustainable objectives. In particular, the focus is on those strategies aimed at changing human behaviour, debated both in transportation (Structural strategies) and in sociological and psychological (Cognitive-Motivational strategies) fields. Further, international experiences of Voluntary Travel Behavioural Changes programs, as opposed to compulsory measures (i.e. taxation, restrictions etc.), are investigated. Finally, the work describes the results of a pilot survey held in Cagliari (Italy) to test a behavioural strategy called "Cap and Save". The basic idea of the Cap and Save is that voluntary travel behavioural changes are more likely when the individuals are able to recognize a personal profit. The Cap and Save program combines a number of key aspects from behavioural strategies reviewed in the literature (i.e. Tradable Exploitation Rights, Personal Journey Planning etc.): first, individuals are free to modify their behaviour; second, a cognitive-motivational process is set forth to increase awareness of sustainable behaviours. Third, each individual receives an annual emissions limit (cap) and a monetary incentive (save) to reduce emissions; fourth, a set of personalized alternatives is tailored for the individual in order to reduce weekly mileage. Finally, the Cap and Save program relies on an accurate analysis of activity-travel behaviour before and after policy intervention. The initial test of the Cap and Save programme was conducted during a two-week survey (July-October 2009), which involved a group of students from the University of Cagliari (Italy). The first week, the students were invited to record their actual daily activity-travel patterns. The second week, they were asked to repeat the survey, this time they were challenged to maintain a weekly cap of kilometres travelled thereby saving the corresponding resources (i.e. environmental and monetary). Each student was provided with a set of personalized alternatives, which (if followed) would result in a 20% reduction of kilometres travelled. The comparison of before and after strategy implementation highlights the implications of Cap and Save on a wide range of individual daily activities and, specifically, on personal car usage.


Urban Studies ◽  
2017 ◽  
Vol 55 (10) ◽  
pp. 2226-2244 ◽  
Author(s):  
Ugo Lachapelle ◽  
Georges A Tanguay ◽  
Léa Neumark-Gaudet

Existing research has concluded that shares of telecommuting are low but stable, increase with distance from the workplace and that telecommuting may reduce commuting-related travel. Its effect on work and non-work travel are subject to rebound effects and, thus, still debated. Additionally, telecommuting does not necessarily occur entirely at home. The paper studies telecommuting’s potential as a sustainable mobility tool in Canada to reduce overall travel time and peak hour travel, and to increase non-motorised travel. Do types of telecommuting arrangements have varying relationships with these studied travel patterns? Using time use data from the 2005 Canadian General Social Survey, studied outcomes are regressed on telecommuting arrangements (all day home working, part-day home working and a combination of other locations and home and/or workplace) and other personal characteristics. Depending on telecommuting arrangements and travel outcomes, results vary. Working from home is associated with decreases in overall travel time by 14 minutes and increases in odds of non-motorised travel by 77%. Other forms of telecommuting yield different results. Telecommuters may be more likely to avoid peak hours when they do take trips. Types of telecommuting arrangements have different impacts on sustainable travel outcomes that should be considered depending on policy priorities.


Author(s):  
Ondřej Přibyl ◽  
Konstadinos G. Goulias

Activity-based approaches to travel demand analysis have gained attention in the past few years and rapidly created the need to develop alternative microsimulation models for comparisons. In this paper, one such example simulates an individual's daily activity–travel patterns and incorporates the interactions among members of households. This model uses several tools to simulate the activity patterns, including a new method to extract activity patterns from data and decision trees to take into account personal and household characteristics. The model outputs are the individuals’ daily activity patterns on a detailed temporal scale. These patterns respect individuals’ constraints, which are implicitly embedded in the simulated activity and travel schedules via the intrahousehold interactions. This model was evaluated with data from 1,500 persons in Centre County, Pennsylvania, collected during fall 2002 and spring 2003.


Author(s):  
Chandra R. Bhat ◽  
Jessica Y. Guo ◽  
Sivaramakrishnan Srinivasan ◽  
Aruna Sivakumar

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