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Travel surveys collect data on the mobility of populations. Large-scale national household transport surveys are used to estimate key mobility figures on national or sub-national levels, like out of home rates, trips and transport mode rates, and to predict the demand of the population regarding the use of transportation modes.
Transport surveys face with a drop of response rates over the world. Even if weighting procedures allow to reduce the incidence of non-response, it is not always possible to postulate that people with some socio-demographic characteristics who do not respond to a survey have the same behaviour than people with the same socio-demographic characteristics who respond and survey non-response might produce bias.
Travel surveys have also some peculiarities, like the focus on trips’ collection for specific days only. They also need a higher number of respondents in comparison to “regular” social surveys, to reach an adequate precision to model and predict travel and transport demand on a regional level. Efforts are made to increase response rate for traditional transport surveys by improving the questionnaire, reducing respondent burden, increasing reminders… Even if results are generally positive, it is in most cases not sufficient. Moreover, implementation of travel surveys is relatively expensive.
New forms of mobility, like car - or bike - sharing that allow passive forms of data collection methods for this specific subgroup, mixed-modes surveys and incorporation of “Big data” are getting increased attention to lower transport survey costs. The potential of new interactive media and Big data seems to be high to improve transport surveys. But the question of data comparability remains. The danger when databases are merged is that a sample selection bias will be created and compromise the accuracy of explanatory models.
The aims of the session will be to discuss the potential of new technologies for mixed modes framework and the opportunity to combine transport survey results with other data sources. It will be possible to characterize bias generated by these methods and to give some perspectives for reduce them. Topics for this session may include (but are not restricted to):
• Survey mode effects in travel survey
• Passive data collection in travel surveys
• Integrating GPS data in trip and survey data
• Improving trip reporting in different modes
• Effects of proxy interviews
• Combining mobility data sources
• Improving household completion rates
• Methods to collect mobility data for specific sociodemographic groups (children)