Joint Optimization of E-Scooter and Public Transit Operations

Journal article, 2026

First and last mile connections play a critical role in urban transportation systems. To address this challenge, various short-distance travel modes have emerged. Among them, e-scooters have gained increasing popularity as a key form of shared micromobility (SMM), offering advantages such as environmental friendliness, flexibility, and energy efficiency. As a result, effectively integrating e-scooters into existing urban transit networks has become a pressing priority. Thus, this research develops a synergistic transit-SMM framework establishing multimodal travel chains that enhance holistic transportation system performance. A bilevel optimization framework captures the intrinsic interaction between upper-level resource allocation and lower-level commuter demand: from the perspective of managers, the upper-level model minimizes operational costs-Through optimized bus/e-scooter deployment, battery allocation, and charging infrastructure-subject to comprehensive travel demand fulfillment; from the perspective of commuters, the lower-level model simulates traveler behavior via integer programming under predetermined multimodal deployments to minimize combined travel and congestion costs. Considering computational complexity, a simulated annealing (SA) algorithm is employed to solve the bilevel model, with performance benchmarked against Gurobi. The model's effectiveness and algorithmic efficiency are evaluated through experiments across various scales in Skövde, Sweden. The computational analysis reveals that the SA algorithm achieves a 60%-70% reduction in solution time compared to Gurobi-based optimization, while maintaining solution quality within 1% of the optimal objective values obtained by the solver. Furthermore, demand scenario analysis indicates a significant rise in the e-scooter mode selection rate, escalating from 0.18% to 29.14% throughout the investigated demand range, underscoring its strategic importance in enhancing urban mobility systems. Finally, we provide practical insights for optimizing urban mobility and promoting sustainable transport systems.