Renni Anggraini

Car allocation decisions in car-deficient households: the case of non-work tours

This study examines the household interactions in the context of the car allocation choice decision in car-deficient households as part of an activity-scheduling process, focusing on non-work tours. A chi-square automatic interaction detector-based algorithm is applied to derive a decision tree using a large activity diary dataset recently collected in the Netherlands. The results show a satisfactory improvement in the goodness-of-fit of the decision tree model compared to the null model. Gender still plays a role. A descriptive analysis indicates that men, more often than women, get the car for non-work tours for which a car allocation decision needs to be made. Tour-level attributes also influence the household car allocation decision for non-work tours. Overall, men exert more influence on the car allocation decision for non-work tours, as indicated by the number of influential variables that relate to males. The developed models will be incorporated in a refinement of the ALBATROSS model – an existing computational process model of activity-travel choice.

Factors affecting trip generation of motorcyclist for the purpose of non-mandatory activities

The inadequate facilities and limited access to public transport reflect many people using private vehicles, in particular, motorcycle. The motorcycle is most widely used in Indonesia, recently, including Aceh Province. As a result, the number of motorcycle ownership is increasing significantly. The increasing number of motorcycles leads to complex traffic problems. Several factors tend to affect the trip generation of the motorcyclist, i.e., the social demographics of individuals and families, accessibility, etc. This study aims to analyze the characteristics of motorcyclists for non-mandatory activities, i.e. activities other than to work and school. It also aims to determine the dominant factors that affect their trips through trip generation models. The required data consist of primary data and secondary data. Primary data consists of a home interview survey that collects individual’s daily trips. It is conducted by distributing the questionnaires to 400 families residing in Lhokseumawe City. Modeling the trip generation of the motorcyclist is done by multiple linear regression analysis. Parameters calibration uses OLS (Ordinary Least Square) method. The results showed that the dominant variables that affect the trip generation of motorcyclist for non-mandatory activities are license ownership, housewife, school-age children, middle-income household, and lower education level. It can be concluded that some factors affecting trip generation to non-work activities were female motorcyclists from the middle-income household with lower education level. As their status is mostly as the housewife, escorting children to non-school activities seems to the mother’s task, instead of the father. It is clear that, most female ride motorcycle for doing household tasks. However, it should be noted that the use of the motorcycle in long-term does not suit for sustainable transportation.The inadequate facilities and limited access to public transport reflect many people using private vehicles, in particular, motorcycle. The motorcycle is most widely used in Indonesia, recently, including Aceh Province. As a result, the number of motorcycle ownership is increasing significantly. The increasing number of motorcycles leads to complex traffic problems. Several factors tend to affect the trip generation of the motorcyclist, i.e., the social demographics of individuals and families, accessibility, etc. This study aims to analyze the characteristics of motorcyclists for non-mandatory activities, i.e. activities other than to work and school. It also aims to determine the dominant factors that affect their trips through trip generation models. The required data consist of primary data and secondary data. Primary data consists of a home interview survey that collects individual’s daily trips. It is conducted by distributing the questionnaires to 400 families residing in Lhokseumawe City. Modeling...