Topic Area D:
Activity and Transport Demand
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This topic area deals with understanding and modelling how people make choices regarding their activities and travel plans and how these interact with the transport system. It deals with theoretical constructs, behavioural assumptions, and methodologies for the analysis, representation, inference and modelling of the way travellers behave and the interrelationships of this behaviour with their activities and the transport system. This subject area includes all topics related to the analysis of travel demand and behaviour and their interactions with time use, and the environment.
D1: Data Collection and Processing Methods (Patrick Bonnel)*
As transport models heavily rely on good quality data, model selection should be jointly considered with data availability. Data needs refer both to travel behaviour, but also to their determinants (attitudes, motivations, preferences) and to the context. This track addresses issues associated to: travel surveys design and analysis; quality and quantity of data obtained with various data collection methods; benefits and challenges of cross-sectional, continuous and longitudinal surveys; using ‘big-data’ sets; new technology-based data collections – GPS, mobile, smart card; triangulation and combination of various data sources; data archiving (travel surveys, networks and contextual data).
D2: Travel Behaviour and Choice Modelling (Chandra Bhat)*
Disaggregate choice models are at the forefront of methodological innovations in understanding and predicting travel behaviour. This track highlights the need for developing models to better understand behaviour and applying them in policy-related situations, especially for assessing changes in relation to new interventions. This session track welcomes papers looking at: new applications of discrete choice models – including both stated and revealed preference data; new advances in modelling and experimental designs; models incorporating spatial dimension and uncertainty in choice modelling; hybrid models, latent class and latent construct models. .
D3: Applications of Travel Behaviour Analysis and Demand Modelling Approaches (Bhargab Maitra)*
The general theme of this session track is the application of various approaches, both traditional (econometric, statistical, etc.) and alternative (cluster analysis, neural network, fuzzy logic, etc.), for carrying out travel behavior analysis and demand modelling in real life scenarios. With the theoretical and methodological developments on one hand, it is now, on the other hand, equally important to apply the knowledge in real world transportation problems. This session track complements session D2 and focusses more on application of various methods in different contexts, case specific findings, use of the derived knowledge for improvement of transport system, addressing policy issues, etc.
D4: ICT Activities, Time Use and Travel Demand (Eran Ben-Elia)*
Theoretical and empirical research has shown that the information and communication technologies (ICT) lead to a reorganisation of activities (both in time and space) of the individuals and households, hence impacting on travel behaviour. Areas covered in this session track include: better understanding of the fragmentation of activities and thus the role of ICT in travel; complementarity between travel and ICT; time use models; emerging technologies and trends. The interest is not in the individual technologies per se, but in their ultimate implications for planning and management of transport systems.
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