Zobrazeno 1 - 10
of 105
pro vyhledávání: '"Poudel, Bibek"'
Effective communication, specifically through documentation, is the beating heart of collaboration among contributors in software development. Recent advancements in language models (LMs) have enabled the introduction of a new type of actor in that e
Externí odkaz:
http://arxiv.org/abs/2405.10243
Human-driven vehicles (HVs) exhibit complex and diverse behaviors. Accurately modeling such behavior is crucial for validating Robot Vehicles (RVs) in simulation and realizing the potential of mixed traffic control. However, existing approaches like
Externí odkaz:
http://arxiv.org/abs/2404.00796
This paper explores the intricacies of traffic behavior at unsignalized intersections through the lens of a novel dataset, combining manual video data labeling and advanced traffic simulation in SUMO. This research involved recording traffic at vario
Externí odkaz:
http://arxiv.org/abs/2312.14561
Human-driven vehicles (HVs) amplify naturally occurring perturbations in traffic, leading to congestion--a major contributor to increased fuel consumption, higher collision risks, and reduced road capacity utilization. While previous research demonst
Externí odkaz:
http://arxiv.org/abs/2311.12261
The surge in Reinforcement Learning (RL) applications in Intelligent Transportation Systems (ITS) has contributed to its growth as well as highlighted key challenges. However, defining objectives of RL agents in traffic control and management tasks,
Externí odkaz:
http://arxiv.org/abs/2306.08094
A prevalent limitation of optimizing over a single objective is that it can be misguided, becoming trapped in local optimum. This can be rectified by Quality-Diversity (QD) algorithms, where a population of high-quality and diverse solutions to a pro
Externí odkaz:
http://arxiv.org/abs/2304.07425
Traffic congestion is a persistent problem in our society. Previous methods for traffic control have proven futile in alleviating current congestion levels leading researchers to explore ideas with robot vehicles given the increased emergence of vehi
Externí odkaz:
http://arxiv.org/abs/2302.09167
With the growing use of machine learning algorithms and ubiquitous sensors, many `perception-to-control' systems are being developed and deployed. To ensure their trustworthiness, improving their robustness through adversarial training is one potenti
Externí odkaz:
http://arxiv.org/abs/2205.10933
Autor:
Poudel, Bibek, Li, Weizi
Traffic state prediction is necessary for many Intelligent Transportation Systems applications. Recent developments of the topic have focused on network-wide, multi-step prediction, where state of the art performance is achieved via deep learning mod
Externí odkaz:
http://arxiv.org/abs/2110.08712
Publikováno v:
In Journal of Manufacturing Processes 15 June 2024 119:964-974
