Search Results for author: Shuo Feng

Found 16 papers, 3 papers with code

Accurately Predicting Probabilities of Safety-Critical Rare Events for Intelligent Systems

no code implementations20 Mar 2024 Ruoxuan Bai, Jingxuan Yang, Weiduo Gong, Yi Zhang, QIUJING LU, Shuo Feng

The complexity of predicting criticality arises from the extreme data imbalance caused by rare events in high dimensional variables associated with the rare events, a challenge we refer to as the curse of rarity.

Adaptive Testing Environment Generation for Connected and Automated Vehicles with Dense Reinforcement Learning

no code implementations29 Feb 2024 Jingxuan Yang, Ruoxuan Bai, Haoyuan Ji, Yi Zhang, Jianming Hu, Shuo Feng

A common approach involves designing testing scenarios based on prior knowledge of CAVs (e. g., surrogate models), conducting tests in these scenarios, and subsequently evaluating CAVs' safety performances.

regression reinforcement-learning

Few-Shot Scenario Testing for Autonomous Vehicles Based on Neighborhood Coverage and Similarity

no code implementations2 Feb 2024 Shu Li, Jingxuan Yang, Honglin He, Yi Zhang, Jianming Hu, Shuo Feng

To alleviate the considerable uncertainty inherent in a small testing scenario set and optimize scenario utilization, we frame the FST problem as an optimization problem and search for a small scenario set based on neighborhood coverage and similarity.

Autonomous Vehicles

Ancient Chinese Word Segmentation and Part-of-Speech Tagging Using Distant Supervision

1 code implementation3 Mar 2023 Shuo Feng, Piji Li

To address this problem, we take advantage of the memorization effects of deep neural networks and a small amount of annotated data to get a model with much knowledge and a little noise, and then we use this model to relabel the ancient Chinese sentences in parallel corpus.

Chinese Word Segmentation Memorization +3

Adaptive Safety Evaluation for Connected and Automated Vehicles with Sparse Control Variates

no code implementations1 Dec 2022 Jingxuan Yang, Haowei Sun, Honglin He, Yi Zhang, Shuo Feng, Henry X. Liu

One prevailing way is to design testing scenarios using prior knowledge of CAVs, test CAVs in these scenarios, and then evaluate their safety performances.

Adaptive Testing for Connected and Automated Vehicles with Sparse Control Variates in Overtaking Scenarios

no code implementations19 Jul 2022 Jingxuan Yang, Honglin He, Yi Zhang, Shuo Feng, Henry X. Liu

To validate the proposed method, the high-dimensional overtaking scenarios are investigated, and the results demonstrate that our approach can further accelerate the evaluation process by about 30 times.

regression

Exploring Contextual Relationships for Cervical Abnormal Cell Detection

1 code implementation11 Jul 2022 Yixiong Liang, Shuo Feng, Qing Liu, Hulin Kuang, Jianfeng Liu, Liyan Liao, Yun Du, Jianxin Wang

To mimic these behaviors, we propose to explore contextual relationships to boost the performance of cervical abnormal cell detection.

Cell Detection

Distilling Neuron Spike with High Temperature in Reinforcement Learning Agents

no code implementations5 Aug 2021 Ling Zhang, Jian Cao, Yuan Zhang, Bohan Zhou, Shuo Feng

This method uses distillation to effectively avoid the weakness of STBP, which can achieve SOTA performance in classification, and can obtain a smaller, faster convergence and lower power consumption SNN reinforcement learning model.

reinforcement-learning Reinforcement Learning (RL) +1

Optimal Cooperative Driving at Signal-Free Intersections with Polynomial-Time Complexity

no code implementations28 Apr 2021 Huaxin Pei, Yuxiao Zhang, Yi Zhang, Shuo Feng

Cooperative driving at signal-free intersections, which aims to improve driving safety and efficiency for connected and automated vehicles, has attracted increasing interest in recent years.

Distributed Cooperative Driving in Multi-Intersection Road Networks

no code implementations21 Apr 2021 Huaxin Pei, Yi Zhang, Qinghua Tao, Shuo Feng, Li Li

Cooperative driving at isolated intersections attracted great interest and had been well discussed in recent years.

A Learning-based Stochastic Driving Model for Autonomous Vehicle Testing

no code implementations4 Feb 2021 Lin Liu, Shuo Feng, Yiheng Feng, Xichan Zhu, Henry X. Liu

However, pre-determined BV trajectories can not react to the AV's maneuvers, and deterministic models are different from real human drivers due to the lack of stochastic components and errors.

Autonomous Vehicles

Distributionally Consistent Simulation of Naturalistic Driving Environment for Autonomous Vehicle Testing

1 code implementation8 Jan 2021 Xintao Yan, Shuo Feng, Haowei Sun, Henry X. Liu

Microscopic traffic simulation provides a controllable, repeatable, and efficient testing environment for autonomous vehicles (AVs).

Autonomous Vehicles

Testing Scenario Library Generation for Connected and Automated Vehicles, Part II: Case Studies

no code implementations9 May 2019 Shuo Feng, Yiheng Feng, Haowei Sun, Shao Bao, Yi Zhang, Henry X. Liu

In Part I of this study, a general methodology for TSLG is proposed, and theoretical properties are investigated regarding the accuracy and efficiency of CAV evaluation.

Cognitive Internet of Things: A New Paradigm beyond Connection

no code implementations11 Mar 2014 Qihui Wu, Guoru Ding, Yuhua Xu, Shuo Feng, Zhiyong Du, Jinlong Wang, Keping Long

Current research on Internet of Things (IoT) mainly focuses on how to enable general objects to see, hear, and smell the physical world for themselves, and make them connected to share the observations.

Decision Making

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