Balancing Energy Resilience and Mobility: A Multi-Objective Strategy for Deploying Shared Autonomous Electric Vehicles in Urban Disruptions

As cities face increasing climate-induced disruptions, Shared Autonomous Electric Vehicles (SAEVs) emerge as a dual-purpose solution for sustaining passenger mobility and supplying emergency energy. This study introduces an integrated assessment framework that combines GIS-based spatial analysis, multi-objective optimization, and ε-constrained programming to evaluate SAEV fleet performance during power outages. Using Montreal as a testbed, we simulate the operations of a mid-sized SAEV fleet under varying power disruption scenarios. Our analysis reveals a critical operational trade-off: the fleet can meet up to 2% of daily mobility demand or supply 28% of energy needs in affected zones, but not simultaneously. Key insights from sensitivity analyses show that improving charging infrastructure yields greater operational gains than enlarging battery capacity. At the same time, revenue from energy provision rises significantly with enhanced fleet size and charger power. These findings underscore the importance of coordinated infrastructure planning and incentive design to enable SAEVs to support transport continuity and urban energy resilience effectively.