output
20152018
most citedModeling car-following behavior on urban expressways in Shanghai: A naturalistic driving study

25 citations

6 papers

cs.RO2018★ 25 cited

Modeling car-following behavior on urban expressways in Shanghai: A naturalistic driving study

Meixin Zhu, Xuesong Wang, Andrew P. Tarko +1

Five car-following models were calibrated, validated and cross-compared. The intelligent driver model performed best among the evaluated models. Considerable behavioral differences…

cs.AI2018★ 11 cited

Automated vehicle's behavior decision making using deep reinforcement learning and high-fidelity simulation environment

Yingjun Ye, Xiaohui Zhang, Jian Sun

Automated vehicles are deemed to be the key element for the intelligent transportation system in the future. Many studies have been made to improve the Automated vehicles' ability…

quant-ph2016

Entanglement concentration for concatenated Greenberger-Horne-Zeiglinger state with feasible linear optics

Yu-Bo Sheng, Chang-Cheng Qu, Lan Zhou

The concatenated Greenberger-Horne-Zeiglinger (C-GHZ) state which is a new type of logic-qubit entanglement has attracted a lot of attentions recently. We present a feasible entang…

quant-ph2015

Feasible logic Bell-state analysis with linear optics

Lan Zhou, Yu-Bo Sheng

We describe a feasible logic Bell-state analysis protocol by employing the logic entanglement to be the robust concatenated Greenberger-Horne-Zeilinger (C-GHZ) state. This protocol…

quant-ph2015★ 1 cited

Purification of Logic-Qubit Entanglement

Lan Zhou, Yu-Bo Sheng

Recently, the theoretical work of Fröwis and W. Dür (Phys. Rev. Lett. \textbf{106}, 110402 (2011)) and the experiment of Lu \emph{et al.} (Nat. Photon. \textbf{8}, 364 (2014)) both…

quant-ph2015

Blind quantum machine learning

Yu-Bo Sheng, Lan Zhou

Blind quantum machine learning (BQML) enables a classical client with little quantum technology to delegate a remote quantum machine learning to the quantum server in such a approa…