Driving Sustainability: A Multi-dimensional Impact Analysis on Integrating Autonomous Electric Vehicles Into Urban Mobility Ecosystems

Abstract

Autonomous electric vehicles (AEVs) represent a transformative convergence of electrification and automation, offering a critical pathway to decarbonize urban transport. However, unplanned adoption risks the AEV paradox, where technological efficiency is offset by systemic inefficiencies such as induced demand and increased congestion. This thesis develops an integrated framework by synthesizing system dynamics, a ReCiPe-based life-cycle calculator, and scenario analysis to quantify these large-scale integration trade-offs. Using Singapore as a case study, results demonstrate that synchronized AEV adoption can reduce life-cycle greenhouse gas emissions by 71.5%, resource depletion by 79.5%, and ecosystem damage by 83.3%. Notably, the research reveals that monetized health benefits reach 91.2% of the total cost of ownership, effectively internalizing externalities to provide a robust economic and public health mandate for the transition. However, these dividends are not guaranteed; findings indicate that without proactive governance to protect public transit and manage demand, sustainability gains are significantly diminished. To address these challenges, the thesis operationalizes its findings into a three-phase integrated policy toolkit and a Proactivity-Integration Matrix. These frameworks empower policymakers to move from reactive regulation to proactive stewardship. By aligning AEV deployment with transit integration and distance-based pricing, cities can transform technological inevitability into a deliberate instrument of sustainable, equitable urban design. Ultimately, this work proves that AEVs are not merely a technological upgrade, but a fundamental pivot point for urban design where economic vitality and socio-ecological health are integrated.