Stochastic Modeling for Integrating Bike-Sharing Services with Public Transport in Urban Mobility Systems

Rapid urbanization and increasing transportation demands require innovative and sustainable mobility solutions. Integrating bike-sharing systems with public transportation networks like bus rapid transit offers a promising approach to reducing congestion and environmental impact. This paper introduces a stochastic Petri net model to support the planning and optimization of such integrated mobility systems. The proposed model estimates critical performance metrics, including bicycle availability, parking lot occupancy, and utilization rates, accounting for stochastic elements like demand variability and network congestion. Comprehensive case studies demonstrate the model’s ability to identify bottlenecks, evaluate resource allocation, and provide actionable insights for system improvement. The results validate the effectiveness of this approach in addressing operational challenges and enhancing user satisfaction. By offering a practical and adaptable modeling framework, this study advances urban mobility planning and provides a robust tool for sustainable transportation development.