Projeto de rede de transporte público urbano: uma abordagem baseada em otimização multiobjetivo da infraestrutura prioritária e eletrificação de frota de ônibus

Abstract

In the context of the climate emergency, where cities have a significant impact on greenhouse gas emissions, the transport sector is one of the main contributors to both emissions and the depletion of non-renewable resources. This thesis presents an analysis of the impact of integrating sustainability strategies into bus public transport systems to reduce carbon dioxide (CO2), particulate matter (PM), and nitrogen oxide (NOx) emissions. The modelling approach considered the perspectives of passengers, operators, and the community within the transport planning process, while simultaneously addressing environmental, economic, and social sustainability aspects. A multi-objective optimisation model was developed for the Urban Transport Network Design Problem, whose decision variables were the implementation of exclusive bus lanes and the electrification of bus fleets. The objective functions aimed to minimise the construction, acquisition, maintenance, and operation costs, as well as the construction and operational emissions of a bus public transport system. The European Environment Agency's model was used for the emission modelling formulation; it takes into account the technology and category of the vehicles and their operating speed, the latter being a linking parameter between the two decision variables. To solve the mathematical model, the metaheuristic NSGA-II (Non-dominated Sorting Genetic Algorithm II) was employed, which was applied to the city of Belo Horizonte, Minas Gerais, Brazil. The case study was defined based on a qualitative analysis of principles and an investigation of the availability of open data in Brazilian state capitals. The results indicated that the strategies proposed are capable of improving the quality of public transport systems by reducing CO2, PM and NOx emissions. The scenario analysis demonstrated that when the measures were applied jointly, using overnight and opportunity charging during the day, the costs, although high, yielded greater environmental and social benefits for passengers and the community, with reductions in operational emissions compared to the baseline scenario of approximately 39.1 to 57.8% for CO₂, 92.9 to 94.9% for PM, and 86.3 to 90.5% for NOx. As contributions, this thesis sought to overcome the gap between mathematical complexity and application complexity by using an emission model dependent on bus technology, category, and operating speed, and by applying it to a large-scale network.