scholarly journals Comprehensive Econometric Microsimulator for Daily Activity-Travel Patterns

2004 ◽  
Vol 1894 (1) ◽  
pp. 57-66 ◽  
Author(s):  
Chandra R. Bhat ◽  
Jessica Y. Guo ◽  
Sivaramakrishnan Srinivasan ◽  
Aruna Sivakumar
Keyword(s):  
Daily Activity ◽  
Travel Patterns

Generation of Synthetic Daily Activity-Travel Patterns

1997 ◽  
Vol 1607 (1) ◽  
pp. 154-162 ◽  
Author(s):  
Ryuichi Kitamura ◽  
Cynthia Chen ◽  
Ram M. Pendyala
Keyword(s):  
Daily Activity ◽  
Travel Demand ◽  
Demand Forecasting ◽  
Multinomial Logit Model ◽  
Time Of Day ◽  
Travel Patterns ◽  
Activity Type ◽  
Individual Activity ◽  
Sequential Approach ◽  
Data Set

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.

The design of a strategy to encourage voluntary travel behaviour change: a cap and save programme

2012 ◽  
pp. 11-30
Author(s):  
Italo Meloni ◽  
Erika Spissu
Keyword(s):  
Daily Activity ◽  
Travel Behaviour ◽  
Travel Patterns ◽  
Accurate Analysis ◽  
Behavioural Changes ◽  
Behavioural Strategy ◽  
Wide Range ◽  
Before And After ◽  
Reduce Emissions ◽  
The Individual

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.

Simulation of Daily Activity Patterns Incorporating Interactions within Households

2005 ◽  
Vol 1926 (1) ◽  
pp. 135-141 ◽  
Author(s):  
Ondřej Přibyl ◽  
Konstadinos G. Goulias
Keyword(s):  
Decision Trees ◽  
Daily Activity ◽  
Travel Demand ◽  
Activity Patterns ◽  
Demand Analysis ◽  
New Method ◽  
Travel Patterns ◽  
The Past ◽  
Microsimulation Models ◽  
Daily Activity Patterns

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.

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
Keyword(s):  
Time Use ◽  
Daily Activity ◽  
Older Individuals ◽  
Travel Patterns

scholarly journals Exploring the correlations between spatiotemporal daily activity-travel patterns and stated interest and perception of risk with self-driving cars

2020 ◽  
Vol 1 ◽  
pp. 1-15
Author(s):  
Jingyi Xiao ◽  
Rongxiang Su ◽  
Elizabeth C. McBride ◽  
Konstadinos G. Goulias
Keyword(s):  
Public Transportation ◽  
Travel Behavior ◽  
Autonomous Vehicles ◽  
Daily Activity ◽  
Puget Sound ◽  
Travel Patterns ◽  
Multinomial Regression ◽  
Multinomial Regression Model ◽  
People’S Attitudes ◽  
Self Driving Cars

Abstract. The key to Autonomous Vehicles (AVs) successful penetration of markets lies in identifying specific needs that AVs satisfy for daily activity-travel participation of individuals. In this paper we explore whether and to what extent people’s exhibited spatiotemporal activity-travel patterns correlate with their stated perceptions about self-driving cars. We investigate the travel diaries of 3,411 survey respondents who live in the Puget Sound region of the U.S. in 2017 using sequence analysis. In parallel, we apply hierarchical clustering to identify people’s attitudes based on their stated interest and perception of risks about AVs. A multinomial regression model is built to examine the correlations between AV attitude clusters and daily activity-travel patterns. Statistically significant correlations are then identified. The model results suggest that people exhibiting different activity-travel behavior patterns also express distinct attitudes towards the uses of AVs. The model shows that people who travel to work during the day are more likely to be positive to AVs. In particular, the group traveling to work later than the regular 8-to-5 schedule shows stronger interest and less concerns to AVs, which can be partially explained by the diverse activities they do throughout the day, the variety of travel modes they use and presumably more schedule flexibility they need than the public transportation system offers.

Agent Simulation of Time Allocation on Daily Activity-Travel Patterns

CICTP 2017 ◽  
2018 ◽  
Author(s):  
Tianming Luo ◽  
Wei Wang ◽  
Min Yang ◽  
Zehao Xin
Keyword(s):  
Time Allocation ◽  
Daily Activity ◽  
Travel Patterns ◽  
Agent Simulation
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