Improving Highly Automated Traffic Management Models Using Alternative Graph Structures Simultaneously - Gábor Pauer; Árpád Török (Applied Sciences)
This research focuses on improving the modelling of highly automated centralized traffic management. Authors use a binary integer modelling for traffic flow optimization. One of the main results of the research is the integration of alternative graph structures simultaneously in the investigated traffic optimization model. This allows to take into account different categories of vehicles, especially large vehicles, and specific traffic directions. The study highlights the need for seamless interoperability between graph structures and demonstrates its feasibility through the investigation of advanced safety indicators. In addition, methods are developed and presented that will allow the future integration of non-automated traffic elements and conventional traffic engineering solutions. During our research, we reviewed the automated traffic management models, focusing on the advantages of both continuous and discrete models. Continuous models provide realism but are computationally intensive, while discrete models are simpler but less realistic. Considering this, our paper proposes solutions that offer a trade-off between these approaches, allowing a balance between computational complexity, accuracy, and realism in vehicle modelling.