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Research on Development Strategy of Unmanned Driving Technology

Yang Yanming, Gao Zenggui, Zhang Zilong, Shen Yue, Wang Linjun

Strategic Study of CAE 2018, Volume 20, Issue 6,   Pages 101-104 doi: 10.15302/J-SSCAE-2018.06.016

Abstract:

Unmanned driving technology is considered as a highly disruptive technologycomparative analysis and literature research, this paper analyses the development trend and stage of unmanned drivingtechnology, and evaluates its potential values and social impacts.It also proposes to promote the development of unmanned driving technology by strengthening the researchon automobile wire control technology, energy power technology and driving cognitive technology.

Keywords： disruptive technology     unmanned driving technology     automotive wire control technology     energy powertechnology     driving cognitive technology    

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Development and application prospects of piezoelectric precision driving technology

ZHAO Chunsheng, ZHANG Jiantao, ZHANG Jianhui, JIN Jiamei

Frontiers of Mechanical Engineering 2008, Volume 3, Issue 2,   Pages 119-132 doi: 10.1007/s11465-008-0034-1

Abstract: driving technology.Electromagnetic driving technology is based on traditional technology, has a low thrust-weight ratio,Non-electromagnetic driving technology is a new choice.As a category of non-electromagnetic driving technology, piezoelectric driving technology becomes animportant branch of modern precision driving technology.

Keywords： Electromagnetic     ultra-precision processing     technology     piezoelectric     cumbrous    

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Trends and driving forces of low-carbon energy technology innovation in China’s industrial sectors from

Xi ZHANG, Yong GENG, Yen Wah TONG, Harn Wei KUA, Huijuan DONG, Hengyu PAN

Frontiers in Energy 2021, Volume 15, Issue 2,   Pages 473-486 doi: 10.1007/s11708-021-0738-z

Abstract: Low-carbon energy technology (LC) innovation contributes to both environmental protection and economicof the innovation of LC in China’s industrial sectors, including the alternative energy production technology(AEPT) and the energy conversation technology (ECT).

Keywords： low-carbon energy technology (LC)     logarithmic mean Divisia index (LMDI)     industrial sector     regional disparity    

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Capacity analysis for cognitive heterogeneous networks with ideal/non-ideal sensing

Tao HUANG, Ying-lei TENG, Meng-ting LIU, Jiang LIU

Frontiers of Information Technology & Electronic Engineering 2015, Volume 16, Issue 1,   Pages 1-11 doi: 10.1631/FITEE.1400129

Abstract: Due to irregular deployment of small base stations (SBSs), the interference in cognitive heterogeneous

Keywords： Cognitive heterogeneous networks     Markov chain     Stochastic geometry     Homogeneous Poisson point process (    

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Indigenous and Integrated Innovation Driving the Boom in China's High-Speed Rail Technologies

Ministry of Science and Technology of the PRC

Engineering 2015, Volume 1, Issue 1,   Pages 9-10 doi: 10.15302/J-ENG-2015023

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Spatiotemporal evolution and driving factors for GHG emissions of aluminum industry in China

Frontiers in Energy 2023, Volume 17, Issue 2,   Pages 294-305 doi: 10.1007/s11708-022-0819-7

Abstract: Decomposition analysis is also performed to uncover the driving factors of GHG emission generated from

Keywords： aluminum     material flow analysis     GHG (greenhouse gas) emissions     LMDI (logarithmic mean divisa index)    

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A Hardware Platform Framework for an Intelligent Vehicle Based on a Driving Brain Article

Deyi Li,Hongbo Gao

Engineering 2018, Volume 4, Issue 4,   Pages 464-470 doi: 10.1016/j.eng.2018.07.015

Abstract: granularity of driving map information.The sensor information processing module is directly associated with the driving map information anddecision-making module, which leads to the interface of intelligent driving system software module hasmap information are processed by using the formal language of driving cognition to form a driving situationoutput to a decision-making module, and the output result of the decision-making module is shown as a cognitive

Keywords： Driving brain     Intelligent driving     Hardware platform framework    

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Mechanism of self-excited torsional vibration of locomotive driving system

Jianxin LIU, Huaiyun ZHAO, Wanming ZHAI

Frontiers of Mechanical Engineering 2010, Volume 5, Issue 4,   Pages 465-469 doi: 10.1007/s11465-010-0115-9

Abstract: vibration model were established to investigate the self-excited torsional vibration of a locomotive driving

Keywords： locomotive     driving system     self-excited torsional vibration     mechanism     influence factor    

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Thoughts and Suggestions on Autonomous Driving Map Policy

Liu Jingnan, Dong Yang, Zhan Jiao, Gao Kefu

Strategic Study of CAE 2019, Volume 21, Issue 3,   Pages 92-97 doi: 10.15302/J-SSCAE-2019.03.004

Abstract:

As a key infrastructure to realize autonomous driving, autonomous drivingmap is crucial to the commercial development of the autonomous driving field in China.Meanwhile, combining the development trends of domestic and international autonomous driving fields,vehicles in China: formulating an autonomous driving map management mode, allowing pilot applicationand orderly opening of autonomous driving maps, appropriately opening up corporate authorization and

Keywords： autonomous driving map     autonomous driving regulation     autonomous driving policy    

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A Probabilistic Architecture of Long-Term Vehicle Trajectory Prediction for Autonomous Driving Article

Jinxin Liu, Yugong Luo, Zhihua Zhong, Keqiang Li, Heye Huang, Hui Xiong

Engineering 2022, Volume 19, Issue 12,   Pages 228-239 doi: 10.1016/j.eng.2021.12.020

Abstract: preconditions for autonomous vehicles (AVs) to accomplish reasonable behavioral decisions and guarantee drivingintegrated probabilistic architecture for long-term vehicle trajectory prediction, which consists of a drivingThe DIM is designed and employed to accurately infer the potential driving intention based on a dynamicprocess (GP)-based TPM, considering both the short-term prediction results of the vehicle model and the drivingeffectiveness of our novel approach is demonstrated by conducting experiments on a public naturalistic driving

Keywords： Autonomous driving     Dynamic Bayesian network     Driving intention recognition     Gaussian process     Vehicle    

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A driving pulse edge modulation technique and its complex programming logic devices implementation

Xiao CHEN,Dong-chang QU,Yong GUO,Guo-zhu CHEN

Frontiers of Information Technology & Electronic Engineering 2015, Volume 16, Issue 12,   Pages 1088-1098 doi: 10.1631/FITEE.1500111

Abstract: This paper describes a new technique of driving pulse edge modulation for insulated gate bipolar transistorsdensity and width of the pulse trains, without regulating the hardware circuit, the slope of the gate drivingThis technique is used in the driving circuit based on complex programmable logic devices (CPLDs), and

Keywords： Driving pulse edge modulation     Switching voltage spike     Complex programmable logic device (CPLD)     Active    

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Reverse driving character of 2-DOF closed chain haptic device

GUO Wei-dong, GUO Xin, ZHANG Yu-ru

Frontiers of Mechanical Engineering 2006, Volume 1, Issue 3,   Pages 356-359 doi: 10.1007/s11465-006-0029-8

Abstract: Reverse driving character plays an important role in evaluating the performance of a haptic device, and
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Driving mechanism and boundary control of urban sprawl

Dongmei JIANG,Xiaoshun LI,Futian QU,Mingyan LI,Shaoliang ZHANG,Yunlong GONG,Xiaoping SHI,Xin CHEN

Frontiers of Environmental Science & Engineering 2015, Volume 9, Issue 2,   Pages 298-309 doi: 10.1007/s11783-014-0639-z

Abstract: Since the reform and opening-up, China’s economy has achieved remarkable development and so does the urbanization. However, there is an unavoidable contradiction between urban sprawl and the protection of arable land and the environment. By redefining the urban sprawl boundary, this paper is to provide a solution for the conflict above on the China’s urbanization context. The ideal boundary, moderate boundary and limit boundary are defined for urban sprawl in space. Taking Nanjing city as a case, the three urban sprawl boundaries are estimated in this paper based on the calculation of agricultural land resources value in Nanjing. The results show that 1) the integrated value of agricultural (cultivated) land resources in Nanjing is 1.55 × 10 CNY·hm , the economic value accounts for only 8.74% of the integrated value, while 91.26% of the integrated value has not revealed itself due to the existing institutional arrangements, policy distortions, and imperfect land market; 2) it is difficult to define the ideal and moderate boundaries due to the relatively low price of North Nanjing. In South Nanjing the land price is expensive and the ideal, moderate and limit boundaries are expanded to Jiangning, Qixia, and Yuhuatai; 3) the city scale of South Nanjing should be limited within 5.82 × 10 hm , which is roughly the same as the designated size of 5.81 × 10 hm in the urban planning. It is suggested that the rational scope of urban expansion should be controlled within the moderate boundary.

Keywords： urban sprawl     rational expansion     driving forces     boundary control     Nanjing    

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Evolutionary Decision-Making and Planning for Autonomous Driving Based on Safe and Rational Exploration

Kang Yuan,Yanjun Huang,Shuo Yang,Zewei Zhou,Yulei Wang,Dongpu Cao,Hong Chen,

Engineering doi: 10.1016/j.eng.2023.03.018

Abstract: Decision-making and motion planning are extremely important in autonomous driving to ensure safe drivingstudy proposes an online evolutionary decision-making and motion planning framework for autonomous drivingdecision-making module based on deep reinforcement learning (DRL) is developed to pursue a rational drivingFinally, two principles of safety and rationality for the self-evolution of autonomous driving are proposedthe proposed online-evolution framework is able to generate safer, more rational, and more efficient driving

Keywords： Autonomous driving     Decision-making     Motion planning     Deep reinforcement learning     Model predictive control    

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Achieving Cognitive Mass Personalization via the Self-X Cognitive Manufacturing Network: An Industrial

Xinyu Li, Pai Zheng, Jinsong Bao, Liang Gao, Xun Xu

Engineering 2023, Volume 22, Issue 3,   Pages 14-19 doi: 10.1016/j.eng.2021.08.018

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Title Author Date Type Operation

Research on Development Strategy of Unmanned Driving Technology

Yang Yanming, Gao Zenggui, Zhang Zilong, Shen Yue, Wang Linjun

Journal Article

Development and application prospects of piezoelectric precision driving technology

ZHAO Chunsheng, ZHANG Jiantao, ZHANG Jianhui, JIN Jiamei

Journal Article

Trends and driving forces of low-carbon energy technology innovation in China’s industrial sectors from

Xi ZHANG, Yong GENG, Yen Wah TONG, Harn Wei KUA, Huijuan DONG, Hengyu PAN

Journal Article

Capacity analysis for cognitive heterogeneous networks with ideal/non-ideal sensing

Tao HUANG, Ying-lei TENG, Meng-ting LIU, Jiang LIU

Journal Article

Indigenous and Integrated Innovation Driving the Boom in China's High-Speed Rail Technologies

Ministry of Science and Technology of the PRC

Journal Article

Spatiotemporal evolution and driving factors for GHG emissions of aluminum industry in China

Journal Article

A Hardware Platform Framework for an Intelligent Vehicle Based on a Driving Brain

Deyi Li,Hongbo Gao

Journal Article

Mechanism of self-excited torsional vibration of locomotive driving system

Jianxin LIU, Huaiyun ZHAO, Wanming ZHAI

Journal Article

Thoughts and Suggestions on Autonomous Driving Map Policy

Liu Jingnan, Dong Yang, Zhan Jiao, Gao Kefu

Journal Article

A Probabilistic Architecture of Long-Term Vehicle Trajectory Prediction for Autonomous Driving

Jinxin Liu, Yugong Luo, Zhihua Zhong, Keqiang Li, Heye Huang, Hui Xiong

Journal Article

A driving pulse edge modulation technique and its complex programming logic devices implementation

Xiao CHEN,Dong-chang QU,Yong GUO,Guo-zhu CHEN

Journal Article

Reverse driving character of 2-DOF closed chain haptic device

GUO Wei-dong, GUO Xin, ZHANG Yu-ru

Journal Article

Driving mechanism and boundary control of urban sprawl

Dongmei JIANG,Xiaoshun LI,Futian QU,Mingyan LI,Shaoliang ZHANG,Yunlong GONG,Xiaoping SHI,Xin CHEN

Journal Article

Evolutionary Decision-Making and Planning for Autonomous Driving Based on Safe and Rational Exploration

Kang Yuan,Yanjun Huang,Shuo Yang,Zewei Zhou,Yulei Wang,Dongpu Cao,Hong Chen,

Journal Article

Achieving Cognitive Mass Personalization via the Self-X Cognitive Manufacturing Network: An Industrial

Xinyu Li, Pai Zheng, Jinsong Bao, Liang Gao, Xun Xu

Journal Article