Hybrid optimisation for coordinating autonomous trucks and drones. This project aims to build analytics for controlling a fleet of autonomous trucks and drones working in tandem to deliver retail good

Description

Hybrid optimisation for coordinating autonomous trucks and drones. This project aims to build analytics for controlling a fleet of autonomous trucks and drones working in tandem to deliver retail goods and disaster relief. This project expects to develop new mathematical and artificial intelligence algorithms for routing and scheduling the vehicles and for directing the multi-modal transfer of goods between vehicles in real-time as traffic conditions change. Expected outcomes of this project include new theories and technologies that enable a central computer to remotely control the autonomous fleet for maximum efficiency. Benefits in transport and logistics include improved freight productivity through reducing costs and delivery times.. Scheme: Discovery Early Career Researcher Award. Field: 4903 - Numerical and Computational Mathematics. Lead: Dr Edward Lam