01662725

Component

https://doi.org/10.1177/0361198118773557

Routines and mandatory activities, such as work and school, shape the activity patterns of individuals and strongly influence travel demand. Knowledge about stability and variability of these routines could strengthen travel demand modelling and forecasting. A longitudinal perspective is required to investigate these aspects. In this study, the activity patterns of a sample of people is compared for one week in two successive years. It is analyzed whether the activity patterns of a given person vary from year to year, to what degree, and how this variability and stability can be measured. It is considered whether socio-demographic factors and life events determine stability in weekly activity patterns. The study is based on the representative panel survey, German Mobility Panel. The weekly activity patterns of the same respondents in different years is assessed, using two methods to measure stability and variability. The survey respondents are clustered into three groups according to the degree of variability in their activity patterns. A logistic regression model is also used to identify socio-economic and demographic covariates for similarity in weekly activity patterns. Results show that about one-third of the sample had the same or very similar weekly activity patterns in the two years examined. A person’s occupation status is a good predictor for the variability of activity patterns. Moreover, persons undergoing a change in occupation status are quite likely to show a greater variability in their activity patterns.

18-01379

English

pp 46-56

2018-12

Transportation Research Record: Journal of the Transportation Research Board

Digital/other

References (24) ; Tables (6)

Activity choices; Analysis; Travel demand; Travel patterns; Trend (Statistics)

German Mobility Panel

Germany

Planning and Forecasting; Transportation (General)

TRIS, TRB, ATRI

Jan 8 2018 10:21AM

• A Modeling Analysis of Impact from E-Hailing Service on Non-Work Travel Mode in Shanghai, China
• A Stated Preference Survey Approach to Understanding Mobility Choices in Light of Shared Mobility Services and Automated Vehicle Technologies in the U.S.
• Alternative Activity Pattern Generation for Stated Preference Surveys
• Coordinated Daily Activity Pattern Type in an Applied Activity-Based Travel Model System: Specifics of Modeling Large Households and Modality Preferences
• Effects of Traffic Congestion on Vehicle Miles Traveled
• Estimation of a Long-Distance Travel Demand Model using Trip Surveys, Location-Based Big Data, and Trip Planning Services
• Exploring the Self-Reported Long-Distance Travel Frequency of Millennials and Generation X in California
• How Should Travel Demand and Supply Models Be Jointly Calibrated?
• Incorporating Multiple Uncertainties into Projections of Chinese Private Car Sales and Stock
• Investigating Behavioral Differences in Heterogeneous Decision Rule Segments: An Empirical Analysis
• Learning Daily Activity Sequences of Population Groups using Random Forest Theory
• Machine Learning Travel Mode Choices: Comparing the Performance of an Extreme Gradient Boosting Model with a Multinomial Logit Model
• Measuring the Impact of Motivations on Travelers’ Strategic Decisions in Different Traffic Conditions: Data Collection, Analysis, and Modeling
• Modeling the Structural Relationships of Activity-Travel Participation of Working Women
• Relationships between Consecutive Long-Term and Mid-Term Mobility Decisions over the Life Course: A Bayesian Network Approach
• The Times They Are A-Changin’: What Do the Expanding Uses of Travel Time Portend for Policy, Planning, and Life?
• Time-Dependent Intermodal A* Algorithm: Methodology and Implementation on a Large-Scale Network
• Tolerance and Indifference Bands in Regret–Rejoice Choice Models: Extension to Market Segmentation in the Context of Mode Choice Behavior
• Travel Behavior Classification: An Approach with Social Network and Deep Learning
• Trip Characteristics Analysis of the Effects of a Travel Behavior Change Program