| Abstract |
Here, we present PLAN SMART, a dynamic tourism planning model that seeks to reduce travel expenses while adapting dynamically to real-time route disruptions. With a graph-based simulation of 63 nodes, where each node corresponds to a city, we represent transportation costs via weighted edges representing multi-modal travel costs. In contrast to static path-planning methods, PLAN SMART incorporates dynamic edge-blocking and real-time recalculation to enable travelers to effectively respond to unexpected disruptions. To ensure our model, we compare actual vs. predicted costs of travel in a scenario where travelers purchase tickets according to the recommendations by the system. Upon unexpected changes, the model automatically recalculates optimal routes, allowing for effortless itinerary modification. Our analysis is done across two iterations: one with one traveler going through the system alone, and the other with two travelers traveling simultaneously, tracking their costs. Simulation results prove that PLAN SMART repeatedly minimizes cost variance and optimizes travel efficiency over baseline models. Utilizing adaptive pathfinding and real-time decision-making, our system presents a scalable and low-cost solution to dynamic travel planning that is best implemented for smart city transport systems and real-time tourist information. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025. |
