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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.This paper focuses on the main policy and regulatory issues faced in the development, application, andmanagement of autonomous driving maps in China, i.e., encryption of autonomous driving maps, limitationsdriving vehicles in China: formulating an autonomous driving map management mode, allowing pilot application

Keywords： autonomous driving map     autonomous driving regulation     autonomous driving policy    

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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 drivingThis study proposes an online evolutionary decision-making and motion planning framework for autonomousdriving based on a hybrid data- and model-driven method.decision-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 proposed

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

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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: long-term trajectory forecasting of surrounding vehicles is one of the indispensable preconditions for autonomousvehicles (AVs) to accomplish reasonable behavioral decisions and guarantee driving safety.integrated 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 dynamiceffectiveness 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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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:

The rapid advance of autonomous vehicles (AVs) has motivated new perspectives and potential challengesCurrently, driving assistance systems of Level 3 and below have been widely produced, and several applicationsdriving.By exploring the physical mechanisms behind high-level autonomous driving systems and analyzing the essenceof driving, we put forward a coordinated and balanced framework based on the brain–cerebellum&

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

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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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Toward Human-in-the-loop AI: Enhancing Deep Reinforcement Learning Via Real-time Human Guidance for AutonomousDriving Article

Jingda Wu, Zhiyu Huang, Zhongxu Hu, Chen Lv

Engineering 2023, Volume 21, Issue 2,   Pages 75-91 doi: 10.1016/j.eng.2022.05.017

Abstract: study, a real-time human-guidance-based (Hug)-deep reinforcement learning (DRL) method is developed for policytraining in an end-to-end autonomous driving case.Based on this human-in-the-loop guidance mechanism, an improved actor-critic architecture with modified policy

Keywords： Human-in-the-loop AI     Deep reinforcement learning     Human guidance     Autonomous driving    

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Semantic Consistency and Correctness Verification of Digital Traffic Rules

Lei Wan,Changjun Wang,Daxin Luo,Hang Liu,Sha Ma,Weichao Hu,

Engineering doi: 10.1016/j.eng.2023.04.016

Abstract: The consensus of the automotive industry and traffic management authorities is that autonomous vehiclesdigital methods, natural language traffic rules can be translated into machine language and used by autonomousrules utilizing metric temporal logic (MTL) can be easily incorporated into simulation platforms and autonomousdriving systems (ADS).

Keywords： Autonomous driving     Traffic rules     Digitization     Formalization     Verification    

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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: The gradual maturation of platoon control technology is enabling vehicle platoons to achieve basic driving

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

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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 fromBased upon these findings and considering regional disparity, several policy implications are proposed

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

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Analysis of the current situation of environmental policy of China and establishment of distributed environmentalpolicy framework

Chaoyang FU,Wangfeng LI

Frontiers of Environmental Science & Engineering 2015, Volume 9, Issue 2,   Pages 310-316 doi: 10.1007/s11783-014-0658-9

Abstract: studies are conducted focusing on the implementation effect of contemporary China’s typical environmental policytypes of environmental management tools are compared from the perspective of implementation costs and policywhich could afford a new method for changing the current relatively low efficiency of environmental policy, solving the problem of “government failure” in environmental policy implementation, and providing anew way to make environmental policy system more flexible and more efficient.

Keywords： environmental policy     distributed environment policy     distributed parameter model     lumped parameter model    

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An autonomous miniature wheeled robot based on visual feedback control

CHEN Haichu

Frontiers of Mechanical Engineering 2007, Volume 2, Issue 2,   Pages 197-200 doi: 10.1007/s11465-007-0033-7

Abstract: micro-motors, a novel omni-direction miniature wheeled robot is designed on the basis of the bi-corner drivingvisual navigation and control system allow the robot to navigate and track the target and to accomplish autonomous

Keywords： measuring     distance     autonomous locomotion     advantage     navigation    

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Embedding expert demonstrations into clustering buffer for effective deep reinforcement learning Research Article

Shihmin WANG, Binqi ZHAO, Zhengfeng ZHANG, Junping ZHANG, Jian PU

Frontiers of Information Technology & Electronic Engineering 2023, Volume 24, Issue 11,   Pages 1541-1556 doi: 10.1631/FITEE.2300084

Abstract: exploration methods that sample an action from different types of posterior distributions, we focus on the policySpecifically, we first employ in the policy to generate an action candidate set.Then we introduce a clustering buffer for modeling the internal hierarchy, which consists of on-policydata, off-policy data, and expert data to evaluate actions from the clusters in the action candidate

Keywords： Reinforcement learning     Sample efficiency     Sampling process     Clustering methods     Autonomous driving    

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Pre-training with asynchronous supervised learning for reinforcement learning based autonomous driving Research Articles

Yunpeng Wang, Kunxian Zheng, Daxin Tian, Xuting Duan, Jianshan Zhou,ypwang@buaa.edu.cn,zhengkunxian@buaa.edu.cn,dtian@buaa.edu.cn,duanxuting@buaa.edu.cn

Frontiers of Information Technology & Electronic Engineering 2021, Volume 22, Issue 5,   Pages 615-766 doi: 10.1631/FITEE.1900637

Abstract: Rule-based autonomous driving systems may suffer from increased complexity with large-scale inter-coupled(RL) has been applied in designing autonomous driving systems because of its outstanding performancedriving system.We propose an asynchronous (ASL) method for the RL-based end-to-end autonomous driving model to addressdriving model in the RL training stage.

Keywords： 自主驾驶；自动驾驶车辆；强化学习；监督学习    

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Toward autonomous mining: design and development of an unmanned electric shovel via point cloud-based

Frontiers of Mechanical Engineering 2022, Volume 17, Issue 3, doi: 10.1007/s11465-022-0686-2

Abstract: In the field of autonomous excavation, environmental perception and excavation trajectory planning areBased on optimal trajectory command, the UES performs autonomous excavation.

Keywords： autonomous excavation     unmanned electric shovel     point cloud     excavation trajectory planning    

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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 driving map used in intelligent vehicle test platform has no uniform standard, which leads to differentgranularity 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 situation

Keywords： Driving brain     Intelligent driving     Hardware platform framework    

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Title Author Date Type Operation

Thoughts and Suggestions on Autonomous Driving Map Policy

Liu Jingnan, Dong Yang, Zhan Jiao, Gao Kefu

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

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

Towards the Unified Principles for Level 5 Autonomous Vehicles

Jianqiang Wang, Heye Huang, Keqiang Li, Jun Li

Journal Article

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

Heiko G. Seif, Xiaolong Hu

Journal Article

Toward Human-in-the-loop AI: Enhancing Deep Reinforcement Learning Via Real-time Human Guidance for AutonomousDriving

Jingda Wu, Zhiyu Huang, Zhongxu Hu, Chen Lv

Journal Article

Semantic Consistency and Correctness Verification of Digital Traffic Rules

Lei Wan,Changjun Wang,Daxin Luo,Hang Liu,Sha Ma,Weichao Hu,

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

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

Journal Article

Analysis of the current situation of environmental policy of China and establishment of distributed environmentalpolicy framework

Chaoyang FU,Wangfeng LI

Journal Article

An autonomous miniature wheeled robot based on visual feedback control

CHEN Haichu

Journal Article

Embedding expert demonstrations into clustering buffer for effective deep reinforcement learning

Shihmin WANG, Binqi ZHAO, Zhengfeng ZHANG, Junping ZHANG, Jian PU

Journal Article

Pre-training with asynchronous supervised learning for reinforcement learning based autonomous driving

Yunpeng Wang, Kunxian Zheng, Daxin Tian, Xuting Duan, Jianshan Zhou,ypwang@buaa.edu.cn,zhengkunxian@buaa.edu.cn,dtian@buaa.edu.cn,duanxuting@buaa.edu.cn

Journal Article

Toward autonomous mining: design and development of an unmanned electric shovel via point cloud-based

Journal Article

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

Deyi Li,Hongbo Gao

Journal Article