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of 27
pro vyhledávání: '"Mehdipour, Noushin"'
Autor:
Karnchanachari, Napat, Geromichalos, Dimitris, Tan, Kok Seang, Li, Nanxiang, Eriksen, Christopher, Yaghoubi, Shakiba, Mehdipour, Noushin, Bernasconi, Gianmarco, Fong, Whye Kit, Guo, Yiluan, Caesar, Holger
Machine Learning (ML) has replaced traditional handcrafted methods for perception and prediction in autonomous vehicles. Yet for the equally important planning task, the adoption of ML-based techniques is slow. We present nuPlan, the world's first re
Externí odkaz:
http://arxiv.org/abs/2403.04133
Autor:
Mehdipour, Noushin
The increased adoption and deployment of cyber-physical systems in critical infrastructure in recent years have led to challenging questions about safety and reliability. These systems usually operate in uncertain environments and are required to sat
Externí odkaz:
https://hdl.handle.net/2144/41871
Autor:
Helou, Bassam, Dusi, Aditya, Collin, Anne, Mehdipour, Noushin, Chen, Zhiliang, Lizarazo, Cristhian, Belta, Calin, Wongpiromsarn, Tichakorn, Tebbens, Radboud Duintjer, Beijbom, Oscar
Autonomous vehicles must balance a complex set of objectives. There is no consensus on how they should do so, nor on a model for specifying a desired driving behavior. We created a dataset to help address some of these questions in a limited operatin
Externí odkaz:
http://arxiv.org/abs/2107.13507
Autor:
Xiao, Wei, Mehdipour, Noushin, Collin, Anne, Bin-Nun, Amitai Y., Frazzoli, Emilio, Tebbens, Radboud Duintjer, Belta, Calin
We develop optimal control strategies for autonomous vehicles (AVs) that are required to meet complex specifications imposed as rules of the road (ROTR) and locally specific cultural expectations of reasonable driving behavior. We formulate these spe
Externí odkaz:
http://arxiv.org/abs/2107.07460
We propose a framework for solving control synthesis problems for multi-agent networked systems required to satisfy spatio-temporal specifications. We use Spatio-Temporal Reach and Escape Logic (STREL) as a specification language. For this logic, we
Externí odkaz:
http://arxiv.org/abs/2104.02737
Autor:
Xiao, Wei, Mehdipour, Noushin, Collin, Anne, Bin-Nun, Amitai, Frazzoli, Emilio, Tebbens, Radboud Duintjer, Belta, Calin
We develop optimal control strategies for Autonomous Vehicles (AVs) that are required to meet complex specifications imposed by traffic laws and cultural expectations of reasonable driving behavior. We formulate these specifications as rules, and spe
Externí odkaz:
http://arxiv.org/abs/2101.05709
We extend Signal Temporal Logic (STL) to enable the specification of importance and priorities. The extension, called Weighted STL (wSTL), has the same qualitative (Boolean) semantics as STL, but additionally defines weights associated with Boolean a
Externí odkaz:
http://arxiv.org/abs/2010.00752
We propose a framework based on Recurrent Neural Networks (RNNs) to determine an optimal control strategy for a discrete-time system that is required to satisfy specifications given as Signal Temporal Logic (STL) formulae. RNNs can store information
Externí odkaz:
http://arxiv.org/abs/2009.11468
Akademický článek
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We propose a new robustness score for continuous-time Signal Temporal Logic (STL) specifications. Instead of considering only the most severe point along the evolution of the signal, we use average scores to extract more information from the signal,
Externí odkaz:
http://arxiv.org/abs/1909.00898