1 citations · 1 across the 4 of their papers we have counts for
4 papers
An End-to-End Collaborative Learning Approach for Connected Autonomous Vehicles in Occluded Scenarios
Leandro Parada, Hanlin Tian, Jose Escribano +1
Collaborative navigation becomes essential in situations of occluded scenarios in autonomous driving where independent driving policies are likely to lead to collisions. One promis…
Safe and Efficient Manoeuvring for Emergency Vehicles in Autonomous Traffic using Multi-Agent Proximal Policy Optimisation
Leandro Parada, Eduardo Candela, Luis Marques +1
Manoeuvring in the presence of emergency vehicles is still a major issue for vehicle autonomy systems. Most studies that address this topic are based on rule-based methods, which c…
A Decentralised Multi-Agent Reinforcement Learning Approach for the Same-Day Delivery Problem
Elvin Ngu, Leandro Parada, Jose Javier Escribano Macias +1
Same-Day Delivery services are becoming increasingly popular in recent years. These have been usually modelled by previous studies as a certain class of Dynamic Vehicle Routing Pro…
Transferring Multi-Agent Reinforcement Learning Policies for Autonomous Driving using Sim-to-Real
Eduardo Candela, Leandro Parada, Luis Marques +3
Autonomous Driving requires high levels of coordination and collaboration between agents. Achieving effective coordination in multi-agent systems is a difficult task that remains l…