86 citations · 167 across the 14 of their papers we have counts for
14 papers
Lane-Change in Dense Traffic with Model Predictive Control and Neural Networks
Sangjae Bae, David Isele, Alireza Nakhaei +5
This paper presents an online smooth-path lane-change control framework. We focus on dense traffic where inter-vehicle space gaps are narrow, and cooperation with surrounding drive…
Interaction-Aware Trajectory Planning for Autonomous Vehicles with Analytic Integration of Neural Networks into Model Predictive Control
Piyush Gupta, David Isele, Donggun Lee +1
Autonomous vehicles (AVs) must share the driving space with other drivers and often employ conservative motion planning strategies to ensure safety. These conservative strategies c…
SLAS: Speed and Lane Advisory System for Highway Navigation
Faizan M. Tariq, David Isele, John S. Baras +1
This paper proposes a hierarchical autonomous vehicle navigation architecture, composed of a high-level speed and lane advisory system (SLAS) coupled with low-level trajectory gene…
Active Uncertainty Reduction for Safe and Efficient Interaction Planning: A Shielding-Aware Dual Control Approach
Haimin Hu, David Isele, Sangjae Bae +1
The ability to accurately predict others' behavior is central to the safety and efficiency of interactive robotics. Unfortunately, robots often lack access to key information on wh…
Predicting Parameters for Modeling Traffic Participants
Ahmadreza Moradipari, Sangjae Bae, Mahnoosh Alizadeh +2
Accurately modeling the behavior of traffic participants is essential for safely and efficiently navigating an autonomous vehicle through heavy traffic. We propose a method, based…
Game Theoretic Decision Making by Actively Learning Human Intentions Applied on Autonomous Driving
Siyu Dai, Sangjae Bae, David Isele
The ability to estimate human intentions and interact with human drivers intelligently is crucial for autonomous vehicles to successfully achieve their objectives. In this paper, w…