Zobrazeno 1 - 10
of 707
pro vyhledávání: '"Yin Guodong"'
A critical aspect of safe and efficient motion planning for autonomous vehicles (AVs) is to handle the complex and uncertain behavior of surrounding human-driven vehicles (HDVs). Despite intensive research on driver behavior prediction, existing appr
Externí odkaz:
http://arxiv.org/abs/2411.01475
High-speed cruising scenarios with mixed traffic greatly challenge the road safety of autonomous vehicles (AVs). Unlike existing works that only look at fundamental modules in isolation, this work enhances AV safety in mixed-traffic high-speed cruisi
Externí odkaz:
http://arxiv.org/abs/2404.14713
Preceding vehicles typically dominate the movement of following vehicles in traffic systems, thereby significantly influencing the efficacy of eco-driving control that concentrates on vehicle speed optimization. To potentially mitigate the negative e
Externí odkaz:
http://arxiv.org/abs/2306.09736
Autor:
Yin, Guodong, Zhou, Mufeng, Chen, Yiming, Tang, Wenjun, Yang, Zekun, Lee, Mingyen, Du, Xirui, Yue, Jinshan, Liu, Jiaxin, Yang, Huazhong, Liu, Yongpan, Li, Xueqing
Performing data-intensive tasks in the von Neumann architecture is challenging to achieve both high performance and power efficiency due to the memory wall bottleneck. Computing-in-memory (CiM) is a promising mitigation approach by enabling parallel
Externí odkaz:
http://arxiv.org/abs/2212.04320
Autor:
Chen, Yiming, Dai, Guohao, Zhou, Mufeng, Lee, Mingyen, Challapalle, Nagadastagiri, Yin, Guodong, Yang, Zekun, Liu, Yongpan, Yang, Huazhong, Narayanan, Vijaykrishnan, Li, Xueqing
Graph convolutional network (GCN), an emerging algorithm for graph computing, has achieved promising performance in graphstructure tasks. To achieve acceleration for data-intensive and sparse graph computing, ASICs such as GCNAX have been proposed fo
Externí odkaz:
http://arxiv.org/abs/2208.08600
Autor:
Chen, Yiming, Yin, Guodong, Tan, Zhanhong, Lee, Mingyen, Yang, Zekun, Liu, Yongpan, Yang, Huazhong, Ma, Kaisheng, Li, Xueqing
Publikováno v:
Design Automation Conference 2022
Computing-in-memory (CiM) is a promising technique to achieve high energy efficiency in data-intensive matrix-vector multiplication (MVM) by relieving the memory bottleneck. Unfortunately, due to the limited SRAM capacity, existing SRAM-based CiM nee
Externí odkaz:
http://arxiv.org/abs/2206.00379
Autor:
Zhang, Ronghui, Peng, Jingtao, Gou, Wanting, Ma, Yuhang, Chen, Junzhou, Hu, Hongyu, Li, Weihua, Yin, Guodong, Li, Zhiwu
Publikováno v:
In Expert Systems With Applications 5 December 2024 256
Publikováno v:
In Computers and Electrical Engineering December 2024 120 Part B
Autor:
Xue, Pengyu, Pi, Dawei, Wan, Chenxi, Yang, Chen, Xie, Boyuan, Wang, Hongliang, Wang, Xianhui, Yin, Guodong
Publikováno v:
In Engineering Applications of Artificial Intelligence October 2024 136 Part A
The cooperative control of the connected and automated vehicle (CAV) is recognized as an effective approach to alleviate traffic congestion and improve traffic safety, especially for on-ramp bottlenecks. However, in the mixed traffic, the uncertainty
Externí odkaz:
http://arxiv.org/abs/2111.00746