Improving future travel demand projections: a pathway with an open science interdisciplinary approach

Abstract Transport accounts for 24% of global CO2 emissions from fossil fuels. Governments face challenges in developing feasible and equitable mitigation strategies to reduce energy consumption and manage the transition to low-carbon transport systems. To meet this challenge, policymakers need more realistic/sophisticated future projections of transport demand to better understand the speed and depth of the actions required to mitigate greenhouse gas (GHG) emissions and meet local and global emissions targets in the transport sector. In this position paper, we argue that more sophisticated models call for a greater interdisciplinary collaboration agenda across open data, data science, behaviour modelling, and policy analysis to provide robust insights to policymakers. The paper also points to some needed efforts and directions to help improve travel demand projection models and indicates how these efforts could benefit from the International Transport Energy Modeling (iTEM) Open Data project and open science interdisciplinary collaborations.