This study proposes the application of a backcasting approach to a mobility model with the aim of defining an optimal decarbonization roadmap. The selected decision variable is the introduction of a fleet of shared autonomous vehicles. The mobility model developed is composed of six interconnected sub-models. After presenting each of these models in detail, a method is introduced to analyze the direct and indirect effects of the measure, and a necessary condition for the occurrence of an undesirable effect is identified. Simulations in both forecasting and backcasting frameworks are then conducted, demonstrating the relevance of backcasting: it enables a 10% reduction in operator costs compared to forecasting results, while maintaining the same level of emissions.
@article{arxiv.2509.17928,
title = {Developing a Dynamic Mobility Model for Backcasting Applications: A Case Study with Shared Autonomous Vehicles},
author = {Théotime Héraud and Vinith Lakshmanan and Antonio Sciarretta},
journal= {arXiv preprint arXiv:2509.17928},
year = {2025}
}