The project consists in pursuing and supervising the development of an integrated platform for the creation, editing, optimisation and simulation of public transport networks and alternative modes called Transition. This platform will support network planning by promoting scenario comparison and automated optimisation through artificial intelligence and the application of innovative evolutionary algorithms. The simplicity of its interface, the robustness and rigour of the methods used, and the computational performance will make it possible to carry out analyses and plan networks more quickly and with greater flexibility. In addition, users and partners will participate in the collaborative development of the platform, which will be fully open source.
Transition will include a network creation and editing module, an import and export module for existing networks, an analysis and visualisation module (path calculator, animated maps, accessibility maps, among others), a simulation module (demand loading and load profile from survey and smart card data), an optimisation module (evolutionary algorithms and artificial intelligence) and a scenario comparison module. A modal choice model using deep learning will provide better predictions. Finally, the simulations may include areas where fleets of collective taxis with drivers or autonomous taxis (micro-transit and transport on demand) are integrated into public transport networks with the aim of increasing accessibility while reducing operating costs.