Quantifying the Capability of Autonomous Robot-Assisted Distribution in Last-Mile: Insight from Rural to Urban Configurations

The surge in online transactions and e-commerce has promoted the demand for timely parcel delivery, increasing the burden on traditional manual delivery. This presents an opportunity for deploying autonomous robot-assisted delivery to improve operation efficiency where robots can navigate autonomously through road networks and deliver packages to customers. This research evaluates the performance of robots in executing last-mile deliveries from rural to urban regions characterised by varying demand density and road congestion. We establish a mixed integer programming model to present the robot-assisted delivery scenario and investigate the impact of key operating parameters on delivery performance. To reduce the computational complexity, we introduced a service set and variable reduction technique. Finally, we validate our model on data sets from rural to urban areas and benchmark the results with various classic delivery modes. Results demonstrate that robot-assisted delivery outperforms the existing delivery modes regarding delivery efficiency in urban regions with an average improvement rate of 76.51%, by shortening vehicle travel and parcel sorting time.