Environmental Assessment of Intelligent Logistics Automation

Abstract

Currently, with the development of intelligent logistics automation, lower operating costs and higher service reliability are increasingly associated with it. However, its net environmental impact remains uncertain because improvements in physical efficiency can be affected by computing energy consumption, equipment turnover, battery production, and demand rebound. Therefore, this paper constructs a lifecycle-oriented framework for evaluating automated transportation, warehousing, packaging, and digital infrastructure. This framework integrates findings from research in logistics, mobility, edge computing, and organization, and combines transparent index equations with reproducible example scenarios. Analysis shows that adaptive route planning, regional resource coordination, energy-saving control, and circular material management can reduce the intensity of environmental impact to some extent, but the results largely depend on system boundaries, power structure, utilization, service commitment, and equipment lifespan. Therefore, cross-domain evidence is considered as methodological guidance rather than direct logistics evidence. The final framework integrates environmental benefits, cost, service quality, and resilience as common constraints.