Travel time expenditure in Flanders: towards a better understanding of travel behavior

In modern societies, mobility is considered to be vital for human development. In order to lead an efficient policy and achieve environmental goals, governments require reliable predictions of travel behavior. In this paper, the travel time expenditure in Flanders is investigated. The focus is put on the time spent on commuting. Two modeling approaches are used for the analysis of daily travel time expenditure, namely the Poisson regression approach and the classical linear regression approach. In this paper it is shown that socio-demographics, day-effects and transportation preferences are contributing significantly in the explanation of variability in daily commuting time and that multiplicative effects of the transportation preferences form good approximations of the travel time ratios.

[1]  A. Agresti,et al.  Categorical Data Analysis , 1991, International Encyclopedia of Statistical Science.

[2]  Piet Rietveld,et al.  Is Average Daily Travel Time Expenditure Constant? In Search of Explanations for an Increase in Average Travel Time , 2006 .

[3]  Ram M. Pendyala,et al.  Understanding Travel Time Expenditures Around the World: Exploring the Notion of a Travel Time Frontier , 2007 .

[4]  C. Bhat,et al.  Modeling Adults' Weekend Day-Time Use by Activity Purpose and Accompaniment Arrangement , 2007 .

[5]  A. M. Lockwood,et al.  Exploratory Analysis of Weekend Activity Patterns in the San Francisco Bay Area, California , 2005 .

[6]  Chandra R. Bhat,et al.  Discretionary activity time allocation of individuals between in-home and out-of-home and between weekdays and weekends , 1999 .

[7]  Zhaobin Liu,et al.  Predicting Directional Design Hourly Volume from Statutory Holiday Traffic , 2006 .

[8]  Jacob Cohen,et al.  Applied multiple regression/correlation analysis for the behavioral sciences , 1979 .

[9]  Chandra R. Bhat,et al.  An Exploratory Analysis of Weekend Activity Patterns in the San Francisco Bay Area , 2004 .

[10]  Mario Cools,et al.  Investigating Effect of Holidays on Daily Traffic Counts , 2007 .

[11]  Leo Breiman,et al.  Classification and Regression Trees , 1984 .

[12]  Kay W. Axhausen,et al.  Exploratory Analysis of Fixed Commitments in Individual Activity—Travel Patterns , 2002 .

[13]  Chandra R. Bhat,et al.  An Analysis of Weekend Work Activity Patterns in the San Francisco Bay Area , 2007 .

[14]  P. McCullagh,et al.  Generalized Linear Models , 1972, Predictive Analytics.