Important Dates

Submission deadline: Mar. 14, 2020 (no extension)

Notification deadline: Apr. 18, 2020

Camera-ready version deadline: May 2, 2020

Paper Requirements

Submitted papers shall not exceed six pages (two additional pages allowed with a fee) as a PDF file in IEEE two column format. All presented papers will be published by the IEEE and the conference proceedings will be submitted to the IEEE Xplore digital library, as long they follow the same review process of IEEE IV 2020, so that each paper will undergo a peer-reviewing process by at least two members of the International Program Committee.

Workshop Topics

The recent development of the Internet of Things (IoT) brings forward numerous novel technologies whose application scenarios are not only limited to the user level (e.g., individual consumer or private company), but can also be applied to the system level (e.g., commercial or industrial sector). For example, the IoT plays a significant role in the current Intelligent Transportation System (ITS), which is a system consists of vehicular communications, cloud computing, intelligent control, massive data management, and many other elements. By leveraging the IoT, different entities (e.g., vehicles, drivers, riders, infrastructures, traffic management centers, etc) in the existing transportation system get connected with each other, thus making the entire system smarter.

A rising and ubiquitous trend in this IoT context is represented by “digital twin”, where a real-time update of big data from the physical world’s entities is required to update the corresponding digital replicas in the cyber world. As an extension concept to digital twin, “parallel driving” also considers the mental world besides the physical world and the cyber world, which models the cognitive behaviors of human drivers, with the ability of enabling learning and interaction between the physical and cyber drivers. Both the computing architecture and the communication networks/protocols within the framework of digital twin or parallel driving are built to achieve higher efficiency, fidelity, and reliability.

However, along these developments come a few challenges for authorities, industry, as well as scientific communities. In terms of system design and control, current IoT applications in ITS need to be refined or even redesigned to better function under uncertainties in demand, and to better cooperate with existing conventional vehicles and infrastructures. From the performance assessment perspective, models and simulation tools based on artificial intelligence and big data have been widely developed to verify the performance of IoT applications, in particular taking into account the increasing trends in vehicle connectivity and automation. However, the validity of these models needs to be re-examined with field implementations.

This workshop focuses on sharing the state-of-the-art design, models, algorithms, simulation, and field implementation of a wide range of IoT applications in ITS (such as digital twin and parallel driving), and identifies challenges as well as research needs, aiming to encourage cross-disciplinary cooperation.

Parallel Driving/Transportation

Parallel driving/transportation is proposed under a cloud-based cyber-physical-social systems, which can include parallel testing, parallel learning, and many other modules.

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Digital Twin

A digital twin is a digital replica of a living or non-living physical entity, whose technology can be adopted to build a vehicle-to-cloud framework.

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Vehicular Cyber-Physical Systems (VCPS)

VCPS realizes mobile cloud computing services where vehicles themselves or mobile devices (e.g., smartphones and tablets of drivers or passengers in vehicles) play a role of both cloud server and cloud client.

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Artificial Intelligence and Big Data

AI and big data empowers the transportation systems to handle more challenging tasks in a more efficient manner.

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Remote Driving

Remote driving enables human operators to take over control of autonomous vehicles at any time, and also reduces the risk of rescue missions.

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Vehicle-to-Cloud Communication

Along with the development of vehicle-to-cloud communication, more advanced IoT applications can be implemented in transportation systems.

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Modeling and Simulation for Network Computing and Communication

Before the implementation of the IoT applications in real world, modeling and simulation can be conducted to study their effectiveness.

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Field Implementations of Internet of Vehicles

Field implementation of IoT applications can be conducted on real-world vehicles and make them internet of vehicles.

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Speaker 1 TBD

Speech abstract and speaker info TBD.

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Speaker 2 TBD

Speech abstract and speaker info TBD.

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Speaker 3 TBD

Speech abstract and speaker info TBD.

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Workshop Agenda

Following talks will be given within the 4-hour workshop session on Tuesday June 23, 2020

1:00-1:30. Prof. XX, Title TBD.
A rising and ubiquitous trend in this IoT context is represented by “digital twin”, where a real-time update of big data from the physical world’s entities is required to update the corresponding digital replicas in the cyber world. As an extension concept to digital twin, “parallel driving” also considers the mental world besides the physical world and the cyber world, which models the cognitive behaviors of human drivers, with the ability of enabling learning and interaction between the physical and cyber drivers. Both the computing architecture and the communication networks/protocols within the framework of digital twin or parallel driving are built to achieve higher efficiency, fidelity, and reliability.

1:30-2:00. Prof. XX, Title TBD.
A rising and ubiquitous trend in this IoT context is represented by “digital twin”, where a real-time update of big data from the physical world’s entities is required to update the corresponding digital replicas in the cyber world. As an extension concept to digital twin, “parallel driving” also considers the mental world besides the physical world and the cyber world, which models the cognitive behaviors of human drivers, with the ability of enabling learning and interaction between the physical and cyber drivers. Both the computing architecture and the communication networks/protocols within the framework of digital twin or parallel driving are built to achieve higher efficiency, fidelity, and reliability.

The workshop agenda will be finalized upon the review process is completed.

Workshop Organizers

Ziran Wang, Research Scientist
Toyota Motor North America, InfoTech Labs, USA
Guoyuan Wu, Associate Research Engineer
University of California, Riverside, USA
Lingxi Li, Associate Professor
Indiana University-Purdue University Indianapolis, USA
Dongpu Cao, Associate Professor
University of Waterloo, Canada
Li Li, Associate Professor
Tsinghua University, China