Proximity is a State of Mind: Exploring Mental Maps in Daily Activity Travel Behaviour

aim of this paper is to explore the behavioural framework for the integration of the 'mental map' concept into the activity based modell ing of travel behaviour. The conceptual framework and the research methodology are described. Stated and revealed preference data gathering techniques are used simultaneously to gai n insight in the role of 'spatial cognition' in daily travel choice behaviour. This results in a qualitative descriptive reflection on spatial learning and activity travel planning. Keynote of this research is the fact that spatial c ognition - here defined as knowledge, experience and perception of large scale environmen ts and its transportation systems - influences the choice set of alternatives that are known and considered by individual travelers. This could affect location choice, mode choice as w ell as route choice.

[1]  D. Hensher.  Handbook of Transport Geography and Spatial Systems , 2004 .

[2]  Nigel Foreman,et al.  Spatial cognition in the child and adult , 1997 .

[3]  R. Downs,et al.  Maps in minds : reflections on cognitive mapping , 1978 .

[4]  Davy Janssens,et al.  Dynamic Activity-Travel Diary Data Collection Using a GPS-Enabled Personal Digital Assistant , 2006 .

[5]  S. Kosslyn.  Image and mind , 1982 .

[6]  Barbara Tversky,et al.  Cognitive Maps, Cognitive Collages, and Spatial Mental Models , 1993, COSIT.

[7]  David M. Mark,et al.  Cognitive models of geographical space , 1999, Int. J. Geogr. Inf. Sci..

[8]  C H Chang-Hyeon Joh,et al.  Measuring and predicting adaptation in multidimensional activity-travel patterns , 2004 .

[9]  Davy Janssens,et al.  Modeling Short-Term Dynamics in Activity-Travel Patterns: From Aurora to Feathers , 2008 .

[10]  Kevin Lynch,et al.  The Image of the City , 1960 .

[11]  Davy Janssens,et al.  Improving Performance of Multiagent Rule-Based Model for Activity Pattern Decisions with Bayesian Networks , 2004 .

[12]  Hjp Harry Timmermans,et al.  Representing mental maps and cognitive learning in micro-simulation models of activity-travel choice dynamics , 2005 .

[13]  T. Gärling,et al.  Cognitive Maps and Urban Travel , 2002 .

[14]  Ta Theo Arentze,et al.  Experiences with developing ALBATROSS: a learning-based transportation oriented simulation system , 1998 .

[15]  B. Kuipers.  The "Map in the Head" Metaphor , 1982 .

[16]  Hjp Harry Timmermans,et al.  Information gain, novelty seeking and travel: a model of dynamic activity-travel behavior under conditions of uncertainty , 2005 .

[17]  S. Mehndiratta,et al.  A Qualitative Survey Technique to Explore Decision Making Behaviour in New Contexts , 2003 .

[18]  Daniel R. Montello,et al.  Spatial Information Theory A Theoretical Basis for GIS , 1995, Lecture Notes in Computer Science.

[19]  Davy Janssens,et al.  Identifying behavioural principles underlying activity patterns by means of Bayesian networks , 2003 .

[20]  Davy Janssens,et al.  Improving the Performance of a Multi-Agent Rule-Based Model for Activity Pattern Decisions Using Bayesian Networks , 1997 .