Formatting scientific data to enable designers to query socio-economic and environmental impacts of autonomous vehicles

Autonomous vehicles (AVs) are about to expand quickly within a few decades, with some fully autonomous AV shuttles already in use worldwide. However, significant uncertainties still surround their development. Beyond technical and economic concerns, the long-term impacts on people and society are often neglected by car manufacturers in favor of immediate technical and economic considerations. Anticipating these impacts comprehensively is crucial to ensure that decision-makers make informed choices that benefit society. This paper presents the Study-Method-Impact (SMI) model, which aims to help designer simulate the long-term socio-economic and environmental impacts of AVs. The SMI model centralizes and structures data from scientific literature, making it more accessible for designers. It also provides detailed results to complex queries. The paper compares the results of the SMI model with external synthesis reviews and concludes that it is a useful tool for providing accurate and comprehensive information to designers. The SMI model has the potential to inform decision making and policy surrounding autonomous vehicles. Further development and perspectives are also discussed to incorporate the model within industrial tools.