Meteorological variation in daily travel behaviour: evidence from revealed preference data from the Netherlands

peer reviewedThis study investigates the meteorological variation in revealed preference travel data. The main objective of this study is to investigate the impact of weather conditions on daily activity participation (trip motives) and daily modal choices in the Netherlands. To this end, data from the Dutch National Travel Household Survey of 2008 were matched to hourly weather data provided by the Royal Dutch Meteorological Institute and were complemented with thermal indices to indicate the level of thermal comfort and additional variables to indicate the seasonality of the weather conditions. Two multinomial logit–generalised estimation equations (MNL-GEE) models were constructed, one to assess the impact of weather conditions on trip motives and one to assess the effect of weather conditions on modal choice. The modelling results indicate that, depending on the travel attribute of concern, other factors might play a role. Nonetheless, the thermal component, as well as the aesthetical component and the physical component of weather play a significant role. Moreover, the parameter estimates indicate significant differences in the impact of weather conditions when different time scales are considered (e.g. daily versus hourly based). The fact that snow does not play any role at all was unexpected. This finding can be explained by the relatively low occurrence of this weather type in the study area. It is important to consider the effects of weather in travel demand modelling frameworks because this will help to achieve higher accuracy and more realistic traffic forecasts. These will in turn allow policy makers to make better long-term and short-term decisions to achieve various political goals, such as progress towards a sustainable transportation system. Further research in this respect should emphasise the role of weather conditions and activityscheduling attributes

Defining Interestigness for Association Rules

Interestingness in Association Rules has been a major topic of research in the past decade. The reason is that the strength of association rules, i.e. its ability to discover ALL patterns given some thresholds on support and confidence, is also its weakness. Indeed, a typical association rules analysis on real data often results in hundreds or thousands of patterns creating a data mining problem of the second order. In other words, it is not straightforward to determine which of those rules are interesting for the end-user. This paper provides an overview of some existing measures of interestingness and we will comment on their properties. In general, interestingness measures can be divided into objective and subjective measures. Objective measures tend to express interestingness by means of statistical or mathematical criteria, whereas subjective measures of interestingness aim at capturing more practical criteria that should be taken into account, such as unexpectedness or actionability of rules. This paper only focusses on objective measures of interestingness

A Pattern Search Method for Discovering Conserved Motifs in Bioactive Peptide Families

status: publishe

Modelling Route Choice Decisions of Car Travellers Using Combined GPS and Diary Data

The aim of this research is to identify the relationship between activity patterns and route choice decisions. The focus is twofold: on the one hand, the relationship between the purpose of a trip and the road categories used for the relocation is investigated; on the other hand, the relationship between the purpose of a trip and the deviation from the shortest path is studied. The data for this study were collected in 2006 and 2007 in Flanders, the Dutch speaking and northern part of Belgium. To estimate the relationship between the primary road category travelled on and the corresponding activity-travel behaviour a multinomial logit model is developed. To estimate the relationship between the deviation from the shortest path and the corresponding activity-travel behaviour a Tobit model is developed. The results of the first model point out that route choice is a function of multiple factors, not just travel time or distance. Crucial for modelling route choices or in general for traffic assignment procedures is the conclusion that activity patterns have a clear influence on the road category primarily driven on. Particularly, it was shown that the likelihood of taking primarily through roads is highest for work trips and lowest for leisure trips. The second model shows a significant relationship between the deviation from the shortest path and the purpose of the trip. Furthermore, next to trip-related attributes (trip distance), also socio-demographic variables and geographical differences play an important role. These results certainly suggest that traffic assignment procedures should be developed that explicitly take into account an activity-based segmentation. In addition, it was shown that route choices were similar during peak and off-peak periods. This is an indication that car drivers are not necessarily utility maximizers, or that classical utility functions in the context of route choices are omitting important explanatory variables