Safety Benefits of Parcel Delivery Modes Using Geographically Weighted Negative Binominal Regression

The surge of e-commerce has disrupted household shopping habits, and new technologies are providing new opportunities for parcel deliveries. Emerging urban parcel delivery (UPD) modes, including Automated Vehicles (AV), delivery robots, and Unmanned Aircraft Vehicles (UAV), are revolutionizing traffic patterns, operations, and safety. They are anticipated to decrease surface UPD truck trips and stops, thus, leading to less exposure of UPD trucks on surface roads and reduced UPD crashes. Limited studies are available to analyze parcel delivery demand and associated safety effectiveness. This paper aims to evaluate the safety impacts of innovative last-mile delivery strategies in urban areas. The geographically weighted negative binominal regression (GWNBR) model was developed at zone levels based on the roadway, traffic, and demographic data collected in Hillsborough County, Florida. Future UPD scenarios were projected for coming years (2030, 2040, and 2050) with different replacement rates (10%, 30%, and 50%) of UPD truck stops by emerging UPD modes. The developed GWNBR model was used to predict UPD crashes for future scenarios. The results indicate that emerging UPD technologies cause a decrease in delivery truck stops and reduce UPD crashes by 3%, 11%, and 20% for 2030, 2040, and 2050, respectively.