Zobrazeno 1 - 10
of 8 647
pro vyhledávání: '"Zheng, Lei"'
Ensuring safety and driving consistency is a significant challenge for autonomous vehicles operating in partially observed environments. This work introduces a consistent parallel trajectory optimization (CPTO) approach to enable safe and consistent
Externí odkaz:
http://arxiv.org/abs/2409.10310
Sequential recommendation aims to estimate how a user's interests evolve over time via uncovering valuable patterns from user behavior history. Many previous sequential models have solely relied on users' historical information to model the evolution
Externí odkaz:
http://arxiv.org/abs/2405.14359
Current recommendation systems are significantly affected by a serious issue of temporal data shift, which is the inconsistency between the distribution of historical data and that of online data. Most existing models focus on utilizing updated data,
Externí odkaz:
http://arxiv.org/abs/2404.15678
In this work, we present a reward-driven automated curriculum reinforcement learning approach for interaction-aware self-driving at unsignalized intersections, taking into account the uncertainties associated with surrounding vehicles (SVs). These un
Externí odkaz:
http://arxiv.org/abs/2403.13674
Abrupt maneuvers by surrounding vehicles (SVs) can typically lead to safety concerns and affect the task efficiency of the ego vehicle (EV), especially with model uncertainties stemming from environmental disturbances. This paper presents a real-time
Externí odkaz:
http://arxiv.org/abs/2403.04143
Enforcing safety while preventing overly conservative behaviors is essential for autonomous vehicles to achieve high task performance. In this paper, we propose a barrier-enhanced homotopic parallel trajectory optimization (BHPTO) approach with over-
Externí odkaz:
http://arxiv.org/abs/2402.10441
Autor:
Liu, Qiong, Nanthakumar, S. S., Li, Bin, Cheng, Teresa, Bittner, Florian, Ma, Chenxi, Ding, Fei, Zheng, Lei, Roth, Bernhard, Zhuang, Xiaoying
Many kinds of two-dimensional (2D) van der Waals (vdW) have been demonstrated to exhibit electromechanical coupling effects, which makes them promising candidates for next-generation devices, such as piezotronics and nanogenerators. Recently, flexoel
Externí odkaz:
http://arxiv.org/abs/2311.06120
Multi-modal behaviors exhibited by surrounding vehicles (SVs) can typically lead to traffic congestion and reduce the travel efficiency of autonomous vehicles (AVs) in dense traffic. This paper proposes a real-time parallel trajectory optimization me
Externí odkaz:
http://arxiv.org/abs/2309.05298
Publikováno v:
Proceedings of the IEEE Conference on Intelligent Transportation Systems (2023)
Unsignalized intersections are typically considered as one of the most representative and challenging scenarios for self-driving vehicles. To tackle autonomous driving problems in such scenarios, this paper proposes a curriculum proximal policy optim
Externí odkaz:
http://arxiv.org/abs/2308.16445
In dense traffic scenarios, ensuring safety while keeping high task performance for autonomous driving is a critical challenge. To address this problem, this paper proposes a computationally-efficient spatiotemporal receding horizon control (ST-RHC)
Externí odkaz:
http://arxiv.org/abs/2308.05929