3 citations · 7 across the 11 of their papers we have counts for
11 papers
NaviDriveVLM: Decoupling High-Level Reasoning and Motion Planning for Autonomous Driving
Ximeng Tao, Pardis Taghavi, Dimitar Filev +2
Vision-language models (VLMs) have emerged as a promising direction for end-to-end autonomous driving (AD) by jointly modeling visual observations, driving context, and language-ba…
Toward Unified Multimodal Representation Learning for Autonomous Driving
Ximeng Tao, Dimitar Filev, Gaurav Pandey
Contrastive Language-Image Pre-training (CLIP) has shown impressive performance in aligning visual and textual representations. Recent studies have extended this paradigm to 3D vis…
Taming Spontaneous Stop-and-Go Traffic Waves: A Computational Mechanism Design Perspective
Di Shen, Qi Dai, Suzhou Huang +1
It is well known that stop-and-go waves can be generated spontaneously in traffic even without bottlenecks. Can such undesirable traffic patterns, induced by intrinsic human drivin…
Control of a commercially available vehicle by a tetraplegic human using a brain-computer interface
Xinyun Zou, Jorge Gamez, Meghna Menon +15
Brain-computer interfaces (BCIs) read neural signals directly from the brain to infer motor planning and execution. However, the implementation of this technology has been largely…
Hierarchical Game-Based Multi-Agent Decision-Making for Autonomous Vehicles
Mushuang Liu, Yan Wan, Frank Lewis +3
This paper develops a game-theoretic decision-making framework for autonomous driving in multi-agent scenarios. A novel hierarchical game-based decision framework is developed for…
A Survey of Reinforcement Learning-Based Motion Planning for Autonomous Driving: Lessons Learned from a Driving Task Perspective
Zhuoren Li, Guizhe Jin, Ran Yu +8
Reinforcement learning (RL), with its ability to explore and optimize policies in complex, dynamic decision-making tasks, has emerged as a promising approach to addressing motion p…
Learning Autonomy: Off-Road Navigation Enhanced by Human Input
Akhil Nagariya, Dimitar Filev, Srikanth Saripalli +1
In the area of autonomous driving, navigating off-road terrains presents a unique set of challenges, from unpredictable surfaces like grass and dirt to unexpected obstacles such as…
Minimum-Time Trajectory Optimization With Data-Based Models: A Linear Programming Approach
Nan Li, Ehsan Taheri, Ilya Kolmanovsky +1
In this paper, we develop a computationally-efficient approach to minimum-time trajectory optimization using input-output data-based models, to produce an end-to-end data-to-contro…
Game Projection and Robustness for Game-Theoretic Autonomous Driving
Mushuang Liu, H. Eric Tseng, Dimitar Filev +2
Game-theoretic approaches are envisioned to bring human-like reasoning skills and decision-making processes for autonomous vehicles (AVs). However, challenges including game comple…
A Comparison between Markov Chain and Koopman Operator Based Data-Driven Modeling of Dynamical Systems
Saeid Tafazzol, Nan Li, Ilya Kolmanovsky +1
Markov chain-based modeling and Koopman operator-based modeling are two popular frameworks for data-driven modeling of dynamical systems. They share notable similarities from a com…
Communication-Efficient Decentralized Multi-Agent Reinforcement Learning for Cooperative Adaptive Cruise Control
Dong Chen, Kaixiang Zhang, Yongqiang Wang +3
Connected and autonomous vehicles (CAVs) promise next-gen transportation systems with enhanced safety, energy efficiency, and sustainability. One typical control strategy for CAVs…