Enhancing Sustainable Last-Mile Delivery: The Impact of Electric Vehicles and AI Optimization on Urban Logistics
The rapid growth of e-commerce has intensified the need for efficient and sustainable last-mile delivery solutions in urban environments. This paper explores the integration of electric vehicles (EVs) and artificial intelligence (AI) into a combined framework to enhance the environmental, operationa...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-04-01
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| Series: | World Electric Vehicle Journal |
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| Online Access: | https://www.mdpi.com/2032-6653/16/5/242 |
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| author | Joao C. Ferreira Marco Esperança |
| author_facet | Joao C. Ferreira Marco Esperança |
| author_sort | Joao C. Ferreira |
| collection | DOAJ |
| description | The rapid growth of e-commerce has intensified the need for efficient and sustainable last-mile delivery solutions in urban environments. This paper explores the integration of electric vehicles (EVs) and artificial intelligence (AI) into a combined framework to enhance the environmental, operational, and economic performance of urban logistics. Through a comprehensive literature review, we examine current trends, technological developments, and implementation challenges at the intersection of smart mobility, green logistics, and digital transformation. We propose an operational framework that leverages AI for route optimization, fleet coordination, and energy management in EV-based delivery networks. This framework is validated through a real-world case study conducted in Lisbon, Portugal, where a logistics provider implemented a city consolidation center model supported by AI-driven optimization tools. Using key performance indicators—including delivery time, energy consumption, fleet utilization, customer satisfaction, and CO₂ emissions—we measure the pre- and post-AI deployment impacts. The results demonstrate significant improvements across all metrics, including a 15–20% reduction in delivery time, a 10–25% gain in energy efficiency, and up to a 40% decrease in emissions. The findings confirm that the synergy between EVs and AI provides a robust and scalable model for achieving sustainable last-mile logistics, supporting broader urban mobility and climate objectives. |
| format | Article |
| id | doaj-art-2630d200f4d24457a4a491aa9b522d2d |
| institution | Kabale University |
| issn | 2032-6653 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | World Electric Vehicle Journal |
| spelling | doaj-art-2630d200f4d24457a4a491aa9b522d2d2025-08-20T03:47:57ZengMDPI AGWorld Electric Vehicle Journal2032-66532025-04-0116524210.3390/wevj16050242Enhancing Sustainable Last-Mile Delivery: The Impact of Electric Vehicles and AI Optimization on Urban LogisticsJoao C. Ferreira0Marco Esperança1Faculty of Logistics, Molde University College, NO-6410 Molde, NorwayISTAR, Instituto Universitário de Lisboa (ISCTE-IUL), 1649-026 Lisbon, PortugalThe rapid growth of e-commerce has intensified the need for efficient and sustainable last-mile delivery solutions in urban environments. This paper explores the integration of electric vehicles (EVs) and artificial intelligence (AI) into a combined framework to enhance the environmental, operational, and economic performance of urban logistics. Through a comprehensive literature review, we examine current trends, technological developments, and implementation challenges at the intersection of smart mobility, green logistics, and digital transformation. We propose an operational framework that leverages AI for route optimization, fleet coordination, and energy management in EV-based delivery networks. This framework is validated through a real-world case study conducted in Lisbon, Portugal, where a logistics provider implemented a city consolidation center model supported by AI-driven optimization tools. Using key performance indicators—including delivery time, energy consumption, fleet utilization, customer satisfaction, and CO₂ emissions—we measure the pre- and post-AI deployment impacts. The results demonstrate significant improvements across all metrics, including a 15–20% reduction in delivery time, a 10–25% gain in energy efficiency, and up to a 40% decrease in emissions. The findings confirm that the synergy between EVs and AI provides a robust and scalable model for achieving sustainable last-mile logistics, supporting broader urban mobility and climate objectives.https://www.mdpi.com/2032-6653/16/5/242sustainable last-mile deliveryelectric vehicles (EVs)urban logisticsartificial intelligence (AI) |
| spellingShingle | Joao C. Ferreira Marco Esperança Enhancing Sustainable Last-Mile Delivery: The Impact of Electric Vehicles and AI Optimization on Urban Logistics World Electric Vehicle Journal sustainable last-mile delivery electric vehicles (EVs) urban logistics artificial intelligence (AI) |
| title | Enhancing Sustainable Last-Mile Delivery: The Impact of Electric Vehicles and AI Optimization on Urban Logistics |
| title_full | Enhancing Sustainable Last-Mile Delivery: The Impact of Electric Vehicles and AI Optimization on Urban Logistics |
| title_fullStr | Enhancing Sustainable Last-Mile Delivery: The Impact of Electric Vehicles and AI Optimization on Urban Logistics |
| title_full_unstemmed | Enhancing Sustainable Last-Mile Delivery: The Impact of Electric Vehicles and AI Optimization on Urban Logistics |
| title_short | Enhancing Sustainable Last-Mile Delivery: The Impact of Electric Vehicles and AI Optimization on Urban Logistics |
| title_sort | enhancing sustainable last mile delivery the impact of electric vehicles and ai optimization on urban logistics |
| topic | sustainable last-mile delivery electric vehicles (EVs) urban logistics artificial intelligence (AI) |
| url | https://www.mdpi.com/2032-6653/16/5/242 |
| work_keys_str_mv | AT joaocferreira enhancingsustainablelastmiledeliverytheimpactofelectricvehiclesandaioptimizationonurbanlogistics AT marcoesperanca enhancingsustainablelastmiledeliverytheimpactofelectricvehiclesandaioptimizationonurbanlogistics |