Automating the school transport decision by using robotics

The city of Tampere is growing at a rapid pace and the region is projected to have XX% more residents of school-age in 2032 than today. However, the city school network does not currently effectively serve those likely growth locations in terms of new pupils and, as a result, the city is now embarking upon the design and development of the future school network. The work carried out the adaptation of Tampere population projection 2032 to a block-level student population forecast (growth or decline) and this was used as a starting point for study of the future. Subsequently, the work carried out school network optimisation studies with different design assumptions.The optimisations took into account those comprehensive schools which will remain part of the future school network while the optimisation was targeted as part of the rest of the school network. In the case of strong comprehensive schools, their capacity was optimised. As a result of the work, different thresholds were found to place schools in different locations and to increase systemic understanding of the impact of individual school placement decisions on the entire school network. The results of the work confirmed the assumption that the school network can be clearly reduced in quantitative terms, even though the recommendations on school travel distances are not exceeded. The results of the work helped the client to reflect on school placement issues and engage in discussions with parents and politicians. The problem is exacerbated by the fact that school closures are never politically popular, but insufficient financing is available to maintain the currrent infrastructure.