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[转载]IEEE物联网期刊丨“网联自动驾驶”专刊征稿(影响因子5.86)

已有 1458 次阅读 2019-5-21 11:03 |系统分类:博客资讯|文章来源:转载

 IEEE物联网期刊丨“网联自动驾驶”专刊征稿(影响因子5.86

 

随着物联网在交通系统中日益普及,为了打造交通系统中更安全、更快、更智能的车辆,车载通信网络和自动驾驶技术是构建未来一代、功能强大的智能交通系统的基石技术。基于物联网的交通系统可以为自动化网联汽车提供大规模设备连接和传感器连接。通过使用物联网技术,网联自动驾驶车辆的数量将显著提高。随着网联自动驾驶汽车数量的增长,亟待提出新的技术方法并重新思考下一代汽车网络的设计,尤其是自动化网联汽车。因此,有必要研究新的理论、架构和技术,利用物联网提供的能力,形成更高效、更智能的交通系统。本期特刊旨在为学术界和工业界的研究人员、开发人员和从业人员提供一个平台,传播最新的成果,并推动物联网在自动化网联汽车技术方面的应用。

 

【征集主题包括但不限于】

  • 应用于连接自动驾驶汽车的创新物联网技术

  • V2X通信

  • 基于物联网的网联汽车解决方案

  • 车辆的物联网基础设施

  • 基于物联网的传感和识别

  • 自动化网联汽车的测试和验证

  • 基于物联网的导航和定位系统

  • 人工智能和基于物联网的自动化网联汽车的深度学习方法

  • 基于社会物理信息系统(CPSS)的平行驾驶

 

【重要时间节点】

  • 投稿截止日期:2019年7月15日

  • 第一次审稿截止日期:2019年10月1日

  • 审稿截止日期:2019年11月15日

  • 第二次审稿截止/通知:2019年12月15日

  • 最终稿件截止日期:2020年1月1日

  • 出版日期:2020年

 

【投稿须知】

所有IEEE Internet of Things Journal 的原稿或修订本必须通过IEEE稿件中心(http://mc.tcentral.com/iot)以电子方式提交。作者指南和提交信息可以在http://iot.ieee.org/journal找到。IEEE Internet of Things Journal鼓励作者在投稿过程中推荐潜在的审稿人,这可能有助于加快审稿速度(请只推荐那些不存在利益冲突的审稿人)。提交稿件时注意必须按适当的关键字分类。

 

【客座编辑】

曹东璞博士,滑铁卢大学,

dongpu.cao@uwaterloo.ca

李力博士,清华大学,

li-li@mail.tsinghua.edu.cn

Clara Marina博士,保时捷,

clara.martinez@porsche-engineering.de

陈龙博士,中山大学,

chenl46@mail.sysu.edu.cn

邢阳博士,克兰菲尔德大学,

y.xing@cranfield.ac.uk

庄卫华教授,滑铁卢大学,

wzhuang@uwaterloo.ca

 

IEEE Internet of Things Journal (Impact Factor 5.86

Special Issue on

 Internet of Things for Connected Automated Driving


Internet-of-things (IoT) is becoming increasingly prevalent in the transportation systems. The traffic system depends on safer, faster, and more intelligent vehicles. The vehicular communication networks (vehicle-to-everything, V2X) and the automated driving technique are two of the cornerstone technologies enabling the construction of future-generation highly functional and intelligent transportation system. The IoT-based transportation system can provide enormous connections of devices and sensors for the networked automated vehicles. The capacity of connected automated vehicles is expected to be dramatically enhanced by employing the IoT techniques. This calls for novel approaches and rethinking of the design of next-generation vehicular networks, particularly for the automated vehicles. Therefore, it is essential to pursue research on new theories, architectures, and techniques to exploit the capability that is delivered by IoT for forming more efficient and intelligent transportation system. This special issue aims to create a platform for researchers, developers and practitioners from both academia and industry to disseminate the state-of-the-art results and to advance the applications of IoT for connected automated driving technology.


Topics of interests include (but are not limited to) the following:

➢Innovative IoT techniques to connect automated vehicles 

➢ V2X communication

➢ IoT-based solutions for connected vehicles 

➢ Vehicular IoT Infrastructure 

➢ IoT-based sensing and recognition 

➢ Testing and verification of connected automated vehicles 

➢ IoT-based navigation and localization systems 

➢ AI and deep learning approaches for IoT-enabled connected automated vehicles 

➢ Cyber-physical-social systems based parallel driving


Important Dates 

Submissions Deadline: July 15, 2019 

Second Reviews Due/Notification: Dec 15, 2019 

First Reviews Due: October 1, 2019 

Final Manuscript Due: Jan 1, 2020 

Revision Due: November 15, 2019 

Publication Date: 2020


Submissions 

All original manuscripts or revisions to the IEEE IoT Journal must be submitted electronically through IEEE Manuscript Central, http://mc.manuscriptcentral.com/iot. Author guidelines and submission information can be found at http://iot.ieee.org/journal. The IEEE IoT Journal encourages authors to suggest potential reviewers as part of the submission process, which might help to expedite the review of the manuscript. Please suggest only those without conflict of interest. Each submission must be classified by appropriate keywords. 


Guest Editors

Dr. Dongpu Cao, University of Waterloo, Canada, 

dongpu.cao@uwaterloo.ca

Dr. Li Li, Tsinghua University, China, 

li-li@mail.tsinghua.edu.cn

Dr. Clara Marina, Porsche Engineering, Germany, 

clara.martinez@porsche-engineering.de

Dr. Long Chen, Sun Yet-sen University, China, 

chenl46@mail.sysu.edu.cn 

Dr. Yang Xing, Cranfield University, UK, 

y.xing@cranfield.ac.uk

Dr. Weihua Zhuang, University of Waterloo, Canada, 

wzhuang@uwaterloo.ca

   

 本文来源自智车科技公众号



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