Abstract
This paper aims is to provide an overview of how new data collection methods and the various advances in urban travel demand modelling are improving the understanding of mobility. These new modelling applications and data allow for a study of both new disruptive transport services and changes in travel behaviours in the “Mobility as a Service” (MaaS) context that needs to be overcome in the future.
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Puignau Arrigain, S.A., Pons-Prats, J., Saurí Marchán, S. (2020). New Data and Methods for Modelling Future Urban Travel Demand: A State of the Art Review. In: Diez, P., Neittaanmäki, P., Periaux, J., Tuovinen, T., Pons-Prats, J. (eds) Computation and Big Data for Transport. Computational Methods in Applied Sciences, vol 54. Springer, Cham. https://doi.org/10.1007/978-3-030-37752-6_4
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