Jointly modelling individual’s daily activity-travel time use andmode share by a nested multivariate Tobit model system

• Understanding mechanisms underlie the individual’s daily time allocations is very important to understand the variability ofindividual’s time-space constraints and to forecast his/her daily activity participation. At most of previous studies, activity timeallocation was viewed as allocating a continuous quantity (daily time budget) into multiple discrete alternatives (i.e. variousactivities and trips to engage with). However, few researches considered the influence of travel time that needs to be spent onreaching the activity location. Moreover, travel time itself is influenced by individuals’ mode choice. This can lead to an over- orunder-estimation of particular activity time location. In order to explicitly include the individual’s travel time and mode choiceconsiderations in activity time allocation modelling, in this study, a nested multivariate Tobit model is proposed. This proposedmodel can handle: 1. Corner solution problem (i.e. the present of substantial amount of zero observations); 2. Time allocationtrade-offs among different types of activities (which tends to be ignored in previous studies); 3. Travel is treated as a deriveddemand of activity participation (i.e. travel time and mode share are automatically censored, and are not estimated, ifcorresponding activity duration is censored). The model is applied on a combined dataset of Swedish national travel survey(NTS) and SMHI (Swedish Meteorological and Hydrological Institute) weather record. Individuals’ work and non-work activitydurations, travel time and mode shares are jointly modelled as dependent variables. The influences of time-locationcharacteristics, individual and household socio demographics and weather characteristics on each dependent variable areexamined. The estimation results show a strong work and non-work activity time trade-offs due to the individual’s time-spaceconstraints. Evidences on a potential positive utility of travel time added on non-work activity time allocation in the Swedish case,are also found. Meanwhile, the results also show a consistent mode choice preference for a given individual. The estimatednested multivariate Tobit model provides a superior prediction, in terms of the deviation of the predicted value against the actualvalue conditional on the correct prediction regarding censored and non-censored, compared to mutually independent Tobitmodels. However, the nested multivariate Tobit model does not necessarily have a better prediction for model componentsregarding non-work related activities.

Subject headings

TEKNIK OCH TEKNOLOGIER  -- Samhällsbyggnadsteknik -- Transportteknik och logistik (hsv//swe)

ENGINEERING AND TECHNOLOGY  -- Civil Engineering -- Transport Systems and Logistics (hsv//eng)

Keyword

multiple discrete-continuous model

sample selection model

activity-travel time allocation

Transportvetenskap

Transport Science

Transportvetenskap

Transport Science

Transportvetenskap

Transport Science

Publication and Content Type

ref (subject category)

kon (subject category)