Quantification of truck accessibility in urban last-mile deliveries using GPS probe data
提出了城市货运移动能源生产率（UF-MEP）指标，利用GPS数据评估末端配送系统性能，并在费城大区域验证了其与配送频率、运营成本和能源强度的关系。
This study presents the Urban Freight Mobility Energy Productivity (UF-MEP), a novel metric that evaluates the performance of last-mile urban freight delivery systems. Incorporating factors like delivery frequency, operational costs, and energy intensity, UF-MEP uses a data-centric approach for estimations. We introduce a pipeline that derives truck activity from GPS data, enabling the calculation of accessible delivery opportunities and UF-MEP. The work emphasizes the importance of comprehensive data collection in less populated areas and the critical role of GPS and link speed data in isochrone generation. Applied to Philadelphia’s large-scale network, our methodology demonstrates decreasing UF-MEP with rising residential and industrial delivery frequencies, while an increase is seen with commercial deliveries. Operational costs and energy intensity negatively impact UF-MEP. Our study suggests the highest potential for UF-MEP improvement lies in enhancing energy efficiency for medium and heavy-duty vehicles. • A novel multi-dimensional performance metric for urban freight delivery systems. • A scalable data pipeline for calculating the metric in large-scale networks. • Deal with data quality issues, e.g., variable transmission frequency and data loss. • Investigate metrics’ differences using GPS probe and link speed data. • Conduct numerical experiments in the greater Philadelphia region.