Modeling Week Activity Schedules for Travel Demand Models

Activity schedules are an important input for travel demand models. This paper presents a model to generate activity schedules for one week. The approach, called actiTopp, is based on the concept of utility-based regression models and stepwise modeling. In contrast to most of the existing models, actiTopp covers the time period of one week. Few models have covered one week; thus, the activity generation approach of this simulation period is rare. Analysis of weekly activity behavior shows stability between different days (e.g., working durations). Hence, the model explicitly takes these aspects into account, for example, by defining time budgets to spread durations within the week. For model estimation, the study used data from the German Mobility Panel (MOP). This annual survey collects representative data on the travel behavior of the German population. The data from 2004–2013 provide more than 17,500 activity schedules for one week, with more than 450,000 activities. Selected results are shown for the model application to 2014 MOP data, which the study used for validation purposes. The mean value of activities per person and week show a difference of 0.3 activity. To evaluate the model, the study used Kolmogorov-Smirnov tests with a significance level of α = 0.001. For the activity type distribution of the 2014 sample, the analysis could not reject the null hypothesis of equality of the distribution of the model and the survey data at this significance level.

[1]  W.W. Recker,et al.  A MODEL OF COMPLEX TRAVEL BEHAVIOR: PART I. THEORETICAL DEVELOPMENT , 1985 .

[2]  Moshe Ben-Akiva,et al.  Activity Based Travel Demand Model Systems , 1998 .

[3]  John L. Bowman,et al.  The Day Activity Schedule Approach to Travel Demand Analysis , 1998 .

[4]  K. Axhausen,et al.  Observing the rhythms of daily life , 2000 .

[5]  Harry Timmermans,et al.  ALBATROSS: Multiagent, Rule-Based Model of Activity Pattern Decisions , 2000 .

[6]  M. Ben-Akiva,et al.  Activity-based disaggregate travel demand model system with activity schedules , 2001 .

[7]  W. W,et al.  A MODEL OF COMPLEX TRAVEL BEHAVIOR: PART II-AN OPERATIONAL MODEL , 2002 .

[8]  K. Axhausen,et al.  Habitual travel behaviour: Evidence from a six-week travel diary , 2003 .

[9]  Chandra R. Bhat,et al.  Comprehensive Econometric Microsimulator for Daily Activity-Travel Patterns , 2004 .

[10]  Mark Bradley,et al.  Activity-Based Travel Forecasting Models in the United States: Progress since 1995 and Prospects for the Future , 2005 .

[11]  Dirk Zumkeller,et al.  Dynamics of Change: Fifteen-Year German Mobility Panel , 2009 .

[12]  Joshua Auld,et al.  Framework for the development of the Agent-based Dynamic Activity Planning and Travel Scheduling (ADAPTS) model , 2009 .

[13]  Peter Vovsha,et al.  CT-RAMP Family of Activity-Based Models , 2010 .

[14]  Chandra R. Bhat,et al.  Activity-based Travel Demand Analysis , 2011 .

[15]  Abolfazl Mohammadian,et al.  Activity planning processes in the Agent-based Dynamic Activity Planning and Travel Scheduling (ADAPTS) model , 2012 .

[16]  Kay W. Axhausen,et al.  MATSim Agent Heterogeneity and a One-Week Scenario , 2012 .

[17]  Kay W. Axhausen,et al.  Simulating Urban Transport for a Week Time Horizon Using MATSim , 2012 .

[18]  Peter Vortisch,et al.  mobiTopp - A Modular Agent-based Travel Demand Modelling Framework , 2013, ANT/SEIT.

[19]  Fabian Märki,et al.  An agent-based model for continuous activity planning of multi-week scenarios , 2014 .

[20]  Peter Vortisch,et al.  The 6 th International Conference on Ambient Systems , Networks and Technologies ( ANT 2015 ) Modelling the Weekly Electricity Demand Caused by Electric Cars , 2015 .

[21]  Peter Vortisch,et al.  Multiple-day Agent-based Modeling Approach of Station-based and Free-floating Carsharing , 2015 .

[22]  Yi Zhu,et al.  SimMobility: A Multi-scale Integrated Agent-Based Simulation Platform , 2016 .

[23]  Peter Vortisch,et al.  Modeling Variability and Stability of Travel Behavior in a Longitudinal View Using the Agent Based Model mobiTopp , 2016 .