ABSTRACT
Since transportation needs meet limited space and budgets and further social and environmental considerations, effective understanding of transportation demand is required to better manage the urban mobility services while meeting travel needs at different spatial and temporal granularities. Transportation demand modeling depends on collecting and analyzing geospatial data, georeferenced sociodemographic data, economic data, and environmental data, all of which are becoming accessible in ever greater variety, veracity and volume with technologies, such as positioning sensors installed on smartphones, high-performance mobile computing platforms, smart cards, or car navigation systems. This chapter reviews old and state-of-the-art methods of travel data collection and analysis, and explains the application and crucial roles of these data in improving transportation demand modeling and simulation techniques.
