Intelligent Connected Shared Micro-Mobility Systems: System Trade-off Mitigation and Constraint Management Based on Multi-Objective Monotonicity Analysis

Abstract

Abstract

Shared micro-mobility systems are increasingly prevalent in urban transportation, yet their operation faces multiple conflicting objectives (e.g., efficiency, cost, user experience, environmental impact) and complex constraints (e.g., vehicle scheduling, charging management, traffic regulations). Existing design and optimization methods struggle to effectively balance these trade-offs and manage constraints, often resulting in suboptimal system performance. This study proposes a system design approach based on Multi-Objective Monotonicity Analysis (MOMA), aiming to proactively identify, mitigate, and avoid trade-off conflicts in intelligent connected shared micro-mobility systems at the early design stage. By constructing system design variables, objective functions, and constraints, operational data of shared micro-mobility systems are modeled and analyzed using computer-aided techniques, and design principles are distilled in combination with expert knowledge. The key finding is that the proposed approach can systematically identify critical factors leading to trade-off conflicts and generate a set of combinable design principles, thereby achieving “ideal design” in the early stage of system development and effectively improving system efficiency, user satisfaction, and sustainability. This study provides a new theoretical framework and practical guidance for the optimized design of intelligent connected shared micro-mobility systems, contributing to the resilience and sustainability of urban transportation and offering insights for the integrated design of other complex engineering systems.

Keywords: intelligent connected shared micro-mobility; system design; trade-off mitigation; constraint management; multi-objective optimization; monotonicity analysis