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pro vyhledávání: '"H, Erić"'
Autonomous driving depends on perception systems to understand the environment and to inform downstream decision-making. While advanced perception systems utilizing black-box Deep Neural Networks (DNNs) demonstrate human-like comprehension, their unp
Externí odkaz:
http://arxiv.org/abs/2403.15577
A continuous motion planning method for connected automated vehicles is considered for generating feasible trajectories in real-time using three consecutive clothoids. The proposed method reduces path planning to a small set of nonlinear algebraic eq
Externí odkaz:
http://arxiv.org/abs/2312.10880
Autor:
Wu, Jianhua, Gao, Bingzhao, Gao, Jincheng, Yu, Jianhao, Chu, Hongqing, Yu, Qiankun, Gong, Xun, Chang, Yi, Tseng, H. Eric, Chen, Hong, Chen, Jie
With the development of artificial intelligence and breakthroughs in deep learning, large-scale Foundation Models (FMs), such as GPT, Sora, etc., have achieved remarkable results in many fields including natural language processing and computer visio
Externí odkaz:
http://arxiv.org/abs/2405.02288
Meta reinforcement learning (Meta RL) has been amply explored to quickly learn an unseen task by transferring previously learned knowledge from similar tasks. However, most state-of-the-art algorithms require the meta-training tasks to have a dense c
Externí odkaz:
http://arxiv.org/abs/2311.06673
We propose a Stochastic MPC (SMPC) formulation for path planning with autonomous vehicles in scenarios involving multiple agents with multi-modal predictions. The multi-modal predictions capture the uncertainty of urban driving in distinct modes/mane
Externí odkaz:
http://arxiv.org/abs/2310.20561
Autonomous vehicles need to accomplish their tasks while interacting with human drivers in traffic. It is thus crucial to equip autonomous vehicles with artificial reasoning to better comprehend the intentions of the surrounding traffic, thereby faci
Externí odkaz:
http://arxiv.org/abs/2310.20148
This paper studies game-theoretic decision-making for autonomous vehicles (AVs). A receding horizon multi-player game is formulated to model the AV decision-making problem. Two classes of games, including Nash game and Stackelber games, are developed
Externí odkaz:
http://arxiv.org/abs/2310.20009
Understanding the intention of vehicles in the surrounding traffic is crucial for an autonomous vehicle to successfully accomplish its driving tasks in complex traffic scenarios such as highway forced merging. In this paper, we consider a behavioral
Externí odkaz:
http://arxiv.org/abs/2309.14497
This paper introduces the Generalized Action Governor, which is a supervisory scheme for augmenting a nominal closed-loop system with the capability of strictly handling constraints. After presenting its theory for general systems and introducing tai
Externí odkaz:
http://arxiv.org/abs/2211.12628
Autor:
Liu, Jinsun, Shao, Yifei, Lymburner, Lucas, Qin, Hansen, Kaushik, Vishrut, Trang, Lena, Wang, Ruiyang, Ivanovic, Vladimir, Tseng, H. Eric, Vasudevan, Ram
Performing real-time receding horizon motion planning for autonomous vehicles while providing safety guarantees remains difficult. This is because existing methods to accurately predict ego vehicle behavior under a chosen controller use online numeri
Externí odkaz:
http://arxiv.org/abs/2211.11997