A recent study aims to assess urban freight tours by integrating machine learning with the Life Cycle Sustainability Assessment (LCSA). The research captures supply chain operations using the Gradient Boosting Regression (GBR) model, real-time data from surveys, and Global Positioning System (GPS) tracking.
These predictions were analysed using LCSA to assess the sustainability impacts of Hydrogen Fuel Light Commercial Vehicles (HFLCVs) and Electric Light Commercial Vehicles (ELCVs) compared to traditional fuel-based vehicles. HFLCVs show remarkable reductions in ecosystem and health damage by 58% and 61%, indicating substantial environmental and health benefits.
Findings suggest that strategic investment in hydrogen-fuel and electric LCVs can significantly decrease operational costs and environmental impacts, making them crucial for advancing sustainable urban logistics. This research highlights the benefits and possibilities of using an integrated data-driven approach to achieve urban sustainability, thus creating an urgency to shift policies favouring green urban freight systems.
Advanced machine learning
This study significantly contributes to urban logistics and sustainability by integrating advanced machine learning with Life Cycle Sustainability Assessment (LCSA) to accurately predict urban freight tour demands. It highlights that while light commercial vehicles (LCVs) are cost-effective, they have a significant environmental footprint (48 kPt), making them the most important contributors to urban ecological degradation. Scenario analyses show that transitioning to cleaner technologies—like solar-electric, wind-electric, and hydrogen-fueled LCVs—can significantly reduce environmental harm, with hydrogen options cutting human health, ecosystem, and resource damage by over 60%. Economically, sustainable vehicles offer long-term benefits, and socially, there’s a need to improve health and safety standards for LCV operators. The study also acknowledges limitations such as potential bias in survey data and the reduced reliability of GPS methods in dense urban settings, which may affect the generalizability of findings.
Future research should develop an integrated simulation model combining economic, environmental, and social dimensions, including GIS-based infrastructure analysis and full vehicle lifecycle assessments. This should factor in local infrastructure, energy systems, and policy environments. Testing scalability through pilot projects, analyzing stakeholder impacts, and using econometric models to assess policy scenarios are also recommended to guide global transitions to sustainable urban freight systems.
Key policy measures and strategies
Key policy measures and strategies to support the adoption of sustainable light commercial vehicles (HFLCVs and ELCVs) in urban logistics:
- Financial Subsidies and Tax Incentives
To offset the high upfront costs of hydrogen and electric LCVs, governments can offer direct purchase subsidies, tax rebates (e.g., on sales, road, or corporate tax), and import duty exemptions on critical components. These measures reduce cost barriers and encourage businesses to adopt clean vehicle technologies. - Awareness Campaigns
Informational campaigns targeting fleet operators, businesses, and policymakers should emphasize the long-term cost savings and environmental benefits of HFLCVs and ELCVs. Case studies, lifecycle cost analyses, and educational events can shift perceptions and build support. - Low-Emission Zones (LEZs)
LEZs restrict access for high-emission vehicles in urban areas, improving air quality. Policies should include clear emission criteria, enforcement mechanisms, and supporting infrastructure like EV charging stations and hydrogen refuelling points to ensure compliance and operational continuity. - Urban Consolidation Centres (UCCs)
UCCs enable efficient last-mile deliveries by consolidating goods in central hubs. Using electric or hydrogen-powered vehicles from these centers reduces emissions and increases delivery efficiency. Policy support could include infrastructure funding and integration with smart logistics systems. - Route Optimization Technologies
Advanced routing software using GPS and real-time data can reduce congestion, fuel use, and emissions. Governments can promote adoption through grants or incentives, encouraging fleet operators to invest in smart routing tools for efficient logistics. - Pre-order and Delivery Consolidation Systems
Encouraging pre-ordering and coordinated delivery scheduling helps reduce empty trips and improves vehicle load efficiency. Incentives such as grants or tax breaks can support companies implementing these systems, especially when integrated with digital logistics platforms.