Lieve Creemers

Changes in Travel Behavior in Response to Weather Conditions: Do Type of Weather and Trip Purpose Matter?

Weather can influence travel demand, traffic flow, and traffic safety. A hypothesis—the type of weather determined the likelihood of a change in travel behavior, and changes in travel behavior because of weather conditions depended on trip purpose—was assayed. A stated adaptation study was conducted in Flanders (the Dutch-speaking region of Belgium). A survey, completed by 586 respondents, was administered both on the Internet and as a traditional paper-and-pencil questionnaire. To ensure optimal correspondence between the survey sample composition and the Flemish population, observations in the sample were weighted. To test the main hypotheses, Pearson chi-square independence tests were performed. Results from both the descriptive analysis and the independence tests confirm that the type of weather matters and that changes in travel behavior in response to these weather conditions are highly dependent on trip purpose. This dependence of behavioral adjustments on trip purpose provides policy makers with a deeper understanding of how weather conditions affect traffic. Further generalizations of the findings are possible by shifting the scope toward revealed travel behavior. Triangulation of both stated and revealed travel behavior on the one hand and traffic intensities on the other hand is a key challenge for further research.

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

This 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 activity-scheduling attributes.

Investigating the Minimum Size of Study Area for an Activity-Based Travel Demand Forecasting Model

Nowadays, considerable attention has been paid to the activity-based approach for transportation planning and forecasting by both researchers and practitioners. However, one of the practical limitations of applying most of the currently available activity-based models is their computation time, especially when large amount of population and detailed geographical unit level are taken into account. In this research, we investigated the possibility of restraining the size of the study area in order to reduce the computation time when applying an activity-based model, as it is often the case that only a small territory rather than the whole region is the focus of a specific study. By introducing an accuracy level of the model, we proposed in this research an iteration approach to determine the minimum size of the study area required for a target territory. In the application, we investigated the required minimum size of the study area surrounding each of the 327 municipalities in Flanders, Belgium, with regard to two different transport modes, that is, car as driver and public transport. Afterwards, a validation analysis and a case study were conducted. All the experiments were carried out by using the FEATHERS, an activity-based microsimulation modeling framework currently implemented for the Flanders region of Belgium.

Effect of Traveler’s Nationality on Daily Travel Time Expenditure Using Zero-Inflated Negative Binomial Regression Models: Results from Belgian National Household Travel Survey

In this study, data stemming from the 2010 Belgian National Household Travel Survey were used to assess the effect of a traveler’s nationality on daily travel time expenditure. Negative binomial (zero-inflated) models were estimated to isolate the effect of nationality after other contributing factors such as sociodemographics, residential characteristics, transport options, and temporal characteristics were controlled for. The results indicate that even if one controls for a series of other influencing factors, nationality plays a significant role in differences in travel time expenditure. This finding is especially relevant in the development of policy packages that are targeted at social inequalities. From a methodological perspective, methodological options—two weighting schemes and two bootstrap solutions—were presented to provide sufficient support for the conclusions. To generalize the results in further studies, an oversampling of travelers of different nationalities is strongly recommended. Future research should focus more on the underlying psychological constructs of why ethnic and cultural differences persist even if one accounts for other determinants.

Travel Demand Forecasting Using Activity-Based Modeling Framework FEATHERS: An Extension

Activity‐based travel demand modeling is the approach with most relation and need for intelligent solutions as it directly aims at reproducing human decision making in daily life. Therefore, the way to implement the selected intelligent solution plays an important role in the successful application of the models. FEATHERS (the Forecasting 16 Evolutionary Activity‐Travel of Households and their Environmental RepercussionS) is an activity‐based microsimulation modeling framework used for transport demand forecasting. Currently, this framework is implemented for the Flanders region of Belgium and the most detailed travel demand data can be obtained at the Subzone level, which consists of 2,386 virtual units with an average area of 5.8 km2. For the sake of more detailed travel demand forecasting, we investigated in this study the extension of the FEATHERS framework from the Subzone zoning system to a more disaggregated zoning system, i.e., Building block (BB), which is the most detailed geographical level currently applicable in Belgium consisting of 10,521 units with an average area of 1.3 km2. In this paper, we elaborated the data processing procedure to implement the FEATHERS framework under the BB zoning system. The observed as well as the predicted travel demand in Flanders based on the two zoning systems was compared. The extended modeling system was further applied to investigate the potential impact of light rail initiatives on travel demand at a local network in Flanders.