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Safety Risks of Self-driving Vehicle: Identification and Measurement

Dou Wenyue, Hu Ping, Wei Ping, Zheng Nanning

Strategic Study of CAE 2021, Volume 23, Issue 6,   Pages 167-177 doi: 10.15302/J-SSCAE-2021.06.016

Abstract:

Self-driving vehicle is a hot application of artificial intelligence,Further, we propose for the first time a six-element frame for the safety risks of self-driving vehicleTo cope with future safety risks of self-driving vehicle, enterprises should strengthen the researchThe government should strengthen the supervision over self-driving vehicle tests, improve regulationsConsumers should keep good driving habits and maintain rational regarding self-driving vehicle.

Keywords： self-driving vehicle     safety risk     risk identification     risk measurement    

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Fully Self-driving Future Hits the Brakes

Chris Palmer

Engineering 2023, Volume 26, Issue 7,   Pages 6-8 doi: 10.1016/j.eng.2023.05.002

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A Co-Point Mapping-Based Approach to Drivable Area Detection for Self-Driving Cars Article

Ziyi Liu,Siyu Yu,Nanning Zheng

Engineering 2018, Volume 4, Issue 4,   Pages 479-490 doi: 10.1016/j.eng.2018.07.010

Abstract:

The randomness and complexity of urban traffic scenes make it a difficult task for self-driving carsInspired by human driving behaviors, we propose a novel method of drivable area detection for self-drivingOur method positions candidate drivable areas through self-learning models based on the initial drivableAfter the initial drivable area is characterized by the features obtained through self-learning, a Bayesian

Keywords： Drivable area     Self-driving     Data fusion     Co-point mapping    

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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: single wheelset drive model and 2-DOFs torsional vibration model were established to investigate the self-excitedtorsional vibration of a locomotive driving system.The simulation results indicate that the self-excited torsional vibration occurs when the steady slipThe principle of energy conservation was used to analyze the mechanism of the self-excited vibration.The factors affecting on the amplitude of the self-excited vibration are studied.

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

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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: In this paper, we propose an integrated probabilistic architecture for long-term vehicle trajectory prediction, which consists of a driving inference model (DIM) and a trajectory prediction model (TPM).The proposed DIM incorporates the basic traffic rules and multivariate vehicle motion information.develop a Gaussian process (GP)-based TPM, considering both the short-term prediction results of the vehiclemodel and the driving motion characteristics.

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

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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:

The type, model, quantity, and location of sensors installed on the intelligent vehicle test platformThe driving map used in intelligent vehicle test platform has no uniform standard, which leads to differentgranularity of driving map information.Based on the software and hardware architecture of intelligent vehicle, the sensor information and drivingmap information are processed by using the formal language of driving cognition to form a driving situation

Keywords： Driving brain     Intelligent driving     Hardware platform framework    

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Fuzzy Control on Vehicle Motion Based on Subjective-objectiveJudgment of Driving Tenseness

Chen Xuemei and Gao Li

Strategic Study of CAE 2007, Volume 9, Issue 1,   Pages 53-57

Abstract: So，it is necessary to judge the emergency degree of environment and provide control algorithm of vehiclebased on relative distance， velocity and drivers’characteristics．Then the control algorithm of vehicleshow that the higher the emergency degree，the bigger the maximum deceleration is used to control the vehiclersquo;characteristics have obvious effect on the braking operation．The fuzzy logic is valid to control vehicle

Keywords： 　driver behavior；emergency；fuzzy logic；safety    

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Large-Scale Vehicle Platooning: Advances and Challenges in Scheduling and Planning Techniques Review

Jing Hou, Guang Chen, Jin Huang, Yingjun Qiao, Lu Xiong, Fuxi Wen, Alois Knoll, Changjun Jiang

Engineering 2023, Volume 28, Issue 9,   Pages 26-48 doi: 10.1016/j.eng.2023.01.012

Abstract:

Through vehicle-to-vehicle (V2V) communication, autonomizinga vehicle platoon can significantly reduce the distance between vehicles, thereby reducing air resistanceThe gradual maturation of platoon control technology is enabling vehicle platoons to achieve basic drivingfunctions, thereby permitting large-scale vehicle platoon scheduling and planning, which is essentialScheduling and planning are required in many aspects of vehicle platoon operation; here, we outline the

Keywords： Autonomous vehicle platoon     Autonomous driving     Connected and automated vehicles     Scheduling and planning    

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Autonomous Driving in the iCity—HD Maps as a Key Challenge of the Automotive Industry Perspective

Heiko G. Seif, Xiaolong Hu

Engineering 2016, Volume 2, Issue 2,   Pages 159-162 doi: 10.1016/J.ENG.2016.02.010

Abstract:

This article provides in-depth insights into the necessary technologies for automated driving in futureEspecially the challenges for the application of HD maps as core technology for automated driving are

Keywords： Autonomous driving     Traffic infrastructure     iCity     Car-to-X communication     Connected vehicle     HD maps    

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Towards the Unified Principles for Level 5 Autonomous Vehicles Article

Jianqiang Wang, Heye Huang, Keqiang Li, Jun Li

Engineering 2021, Volume 7, Issue 9,   Pages 1313-1325 doi: 10.1016/j.eng.2020.10.018

Abstract: By improving the automation level and vehicle intelligence, these systems
can be further advancedtowards fully autonomous driving.of driving, we put forward a coordinated and balanced framework based on the brain–cerebellum&the research paradigm of autonomous learning and prior knowledge to realize the characteristics of self-learning, self-adaptation, and self-transcendence for AVs.

Keywords： Autonomous vehicle     Principle of least action     Driving safety field     Autonomous learning     Basic paradigm    

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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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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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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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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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Title Author Date Type Operation

Safety Risks of Self-driving Vehicle: Identification and Measurement

Dou Wenyue, Hu Ping, Wei Ping, Zheng Nanning

Journal Article

Fully Self-driving Future Hits the Brakes

Chris Palmer

Journal Article

A Co-Point Mapping-Based Approach to Drivable Area Detection for Self-Driving Cars

Ziyi Liu,Siyu Yu,Nanning Zheng

Journal Article

Mechanism of self-excited torsional vibration of locomotive driving system

Jianxin LIU, Huaiyun ZHAO, Wanming ZHAI

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

Deyi Li,Hongbo Gao

Journal Article

Fuzzy Control on Vehicle Motion Based on Subjective-objectiveJudgment of Driving Tenseness

Chen Xuemei and Gao Li

Journal Article

Large-Scale Vehicle Platooning: Advances and Challenges in Scheduling and Planning Techniques

Jing Hou, Guang Chen, Jin Huang, Yingjun Qiao, Lu Xiong, Fuxi Wen, Alois Knoll, Changjun Jiang

Journal Article

Autonomous Driving in the iCity—HD Maps as a Key Challenge of the Automotive Industry

Heiko G. Seif, Xiaolong Hu

Journal Article

Towards the Unified Principles for Level 5 Autonomous Vehicles

Jianqiang Wang, Heye Huang, Keqiang Li, Jun Li

Journal Article

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

Journal Article

Thoughts and Suggestions on Autonomous Driving Map Policy

Liu Jingnan, Dong Yang, Zhan Jiao, Gao Kefu

Journal Article

Development and application prospects of piezoelectric precision driving technology

ZHAO Chunsheng, ZHANG Jiantao, ZHANG Jianhui, JIN Jiamei

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