7 citations · 16 across the 10 of their papers we have counts for
10 papers
PALCAS: A Priority-Aware Intelligent Lane Change Advisory System for Autonomous Vehicles using Federated Reinforcement Learning
Yassine Ibork, Nhat Ha Nguyen, Myounggyu Won +1
We present a priority-aware intelligent lane change advisory system based on multi-agent federated reinforcement learning, namely PALCAS, for autonomous vehicles (AVs). While exist…
Z-Merge: Multi-Agent Reinforcement Learning for On-Ramp Merging with Zone-Specific V2X Traffic Information
Yassine Ibork, Myounggyu Won, Lokesh Das
Ramp merging is a critical and challenging task for autonomous vehicles (AVs), particularly in mixed traffic environments with human-driven vehicles (HVs). Existing approaches typi…
RESTRAIN: Reinforcement Learning-Based Secure Framework for Trigger-Action IoT Environment
Md Morshed Alam, Lokesh Chandra Das, Sandip Roy +2
Internet of Things (IoT) platforms with trigger-action capability allow event conditions to trigger actions in IoT devices autonomously by creating a chain of interactions. Adversa…
Traffic Volume Prediction using Memory-Based Recurrent Neural Networks: A comparative analysis of LSTM and GRU
Lokesh Chandra Das
Predicting traffic volume in real-time can improve both traffic flow and road safety. A precise traffic volume forecast helps alert drivers to the flow of traffic along their prefe…
LCS-TF: Multi-Agent Deep Reinforcement Learning-Based Intelligent Lane-Change System for Improving Traffic Flow
Lokesh Chandra Das, Myounggyu Won
Discretionary lane-change is one of the critical challenges for autonomous vehicle (AV) design due to its significant impact on traffic efficiency. Existing intelligent lane-change…
RLPG: Reinforcement Learning Approach for Dynamic Intra-Platoon Gap Adaptation for Highway On-Ramp Merging
Sushma Reddy Yadavalli, Lokesh Chandra Das, Myounggyu Won
A platoon refers to a group of vehicles traveling together in very close proximity using automated driving technology. Owing to its immense capacity to improve fuel efficiency, dri…
WatchPed: Pedestrian Crossing Intention Prediction Using Embedded Sensors of Smartwatch
Jibran Ali Abbasi, Navid Mohammad Imran, Lokesh Chandra Das +1
The pedestrian crossing intention prediction problem is to estimate whether or not the target pedestrian will cross the street. State-of-the-art techniques heavily depend on visual…
LSTM-Based Adaptive Vehicle Position Control for Dynamic Wireless Charging
Lokesh Chandra Das, Dipankar Dasgupta, Myounggyu Won
Dynamic wireless charging (DWC) is an emerging technology that allows electric vehicles (EVs) to be wirelessly charged while in motion. It is gaining significant momentum as it can…
SAINT-ACC: Safety-Aware Intelligent Adaptive Cruise Control for Autonomous Vehicles Using Deep Reinforcement Learning
Lokesh Das, Myounggyu Won
We present a novel adaptive cruise control (ACC) system namely SAINT-ACC: {S}afety-{A}ware {Int}elligent {ACC} system (SAINT-ACC) that is designed to achieve simultaneous optimizat…
D-ACC: Dynamic Adaptive Cruise Control for Highways with Ramps Based on Deep Q-Learning
Lokesh Das, Myounggyu Won
An Adaptive Cruise Control (ACC) system allows vehicles to maintain a desired headway distance to a preceding vehicle automatically. It is increasingly adopted by commercial vehicl…