Transport Choice Modeling for the Evaluation of New Transport Policies

Ander Pijoan, Oihane Kamara-Esteban, Ainhoa Alonso-Vicario and Cruz E. Borges
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Ander Pijoan: DeustoTech-Fundación Deusto, Avda. Universidades, 24, 48007 Bilbao, Spain
Oihane Kamara-Esteban: DeustoTech-Fundación Deusto, Avda. Universidades, 24, 48007 Bilbao, Spain
Ainhoa Alonso-Vicario: DeustoTech-Fundación Deusto, Avda. Universidades, 24, 48007 Bilbao, Spain
Cruz E. Borges: DeustoTech-Fundación Deusto, Avda. Universidades, 24, 48007 Bilbao, Spain

Sustainability, 2018, vol. 10, issue 4, 1-22

Abstract: Quantifying the impact of the application of sustainable transport policies is essential in order to mitigate effects of greenhouse gas emissions produced by the transport sector. One of the most common approaches used for this purpose is that of traffic modelling and simulation, which consists of emulating the operation of an entire road network. This article presents the results of fitting 8 well known data science methods for transport choice modelling, the area in which more research is needed. The models have been trained with information from Biscay province in Spain in order to match as many of its commuters as possible. Results show that the best models correctly forecast more than 51% of the trips recorded. Finally, the results have been validated with a second data set from the Silesian Voivodeship in Poland, showing that all models indeed maintain their forecasting ability.

Keywords: green travelling policies; transport modelling; transport choice modelling; traffic management; genetic programming (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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