8 citations · 9 across the 4 of their papers we have counts for
5 papers
A Novel Traffic Simulation Framework for Testing Autonomous Vehicles Using SUMO and CARLA
Pei Li, Arpan Kusari, David J. LeBlanc
Traffic simulation is an efficient and cost-effective way to test Autonomous Vehicles (AVs) in a complex and dynamic environment. Numerous studies have been conducted for AV evalua…
Enhancing SUMO simulator for simulation based testing and validation of autonomous vehicles
Arpan Kusari, Pei Li, Hanzhi Yang +4
Current autonomous vehicle (AV) simulators are built to provide large-scale testing required to prove capabilities under varied conditions in controlled, repeatable fashion. Howeve…
Assessing and Accelerating Coverage in Deep Reinforcement Learning
Arpan Kusari
Current deep reinforcement learning (DRL) algorithms utilize randomness in simulation environments to assume complete coverage in the state space. However, particularly in high dim…
CWAE-IRL: Formulating a supervised approach to Inverse Reinforcement Learning problem
Arpan Kusari
Inverse reinforcement learning (IRL) is used to infer the reward function from the actions of an expert running a Markov Decision Process (MDP). A novel approach using variational…
Predicting optimal value functions by interpolating reward functions in scalarized multi-objective reinforcement learning
Arpan Kusari, Jonathan P. How
A common approach for defining a reward function for Multi-objective Reinforcement Learning (MORL) problems is the weighted sum of the multiple objectives. The weights are then tre…