Els Hannes

Destination Choice in Daily Activity Travel: Mental Map’s Repertoire

To improve the behavioral realism of activity-based travel demand models, a deeper understanding of an individuals travel decision process is needed. This research project aims at revealing the variety of critical spatial factors in an individuals mental map that influence daily activity travel (AT) behavior. A qualitative travel survey and in-depth interviews are used to identify spatial factors that appear in respondents’ destination choice decisions when discussing their daily activity space. Recorded interviews are processed with specialized software for qualitative data analysis (ATLAS.ti). First, representative if-then(-else) heuristics used by respondents are identified and classified. In addition, occurring spatial elements are indicated. To conclude, a new “script” approach used to grasp the behavioral mechanisms present in daily AT decisions is suggested. Further research along this line will increase comprehension of the impact of travel demand measures and improve their assessment in activity-based travel demand models.

Mental maps and travel behaviour: meanings and models

In this paper, the “mental map” concept is positioned with regard to individual travel behaviour to start with. Based on Ogden and Richards’ triangle of meaning (The meaning of meaning: a study of the influence of language upon thought and of the science of symbolism. International library of psychology, philosophy and scientific method. Routledge and Kegan Paul, London, 1966) distinct thoughts, referents and symbols originating from different scientific disciplines are identified and explained in order to clear up the notion’s fuzziness. Next, the use of this concept in two major areas of research relevant to travel demand modelling is indicated and discussed in detail: spatial cognition and decision-making. The relevance of these constructs to understand and model individual travel behaviour is explained and current research efforts to implement these concepts in travel demand models are addressed. Furthermore, these mental map notions are specified in two types of computational models, i.e. a Bayesian Inference Network (BIN) and a Fuzzy Cognitive Map (FCM). Both models are explained, and a numerical and a real-life example are provided. Both approaches yield a detailed quantitative representation of the mental map of decision-making problems in travel behaviour.

Tracking household routines using scheduling hypothesis embedded in skeletons

This study addresses complex daily activity-travel routines of households with young children and their proper representation in a computational process model of travel demand using family skeletons expressed as family sequence patterns. Building on qualitative interview research findings, an a priori classification of family types is defined according to the distribution of care and work responsibilities in the household on a typical weekday. Enriched census data are examined to calculate the share of each family type in the region of Flanders in Belgium. Next, individual activity-travel sequence patterns are drawn for children and adults. Finally, these individual sequences are combined to family sequence patterns, yielding a concise representation of skeletal information in activity-travel patterns of household members and their interrelationships. This process is tested and the method offers a promising approach to both household activity-travel analysis and travel demand modelling.