[AISWorld] CFP: IEEE SMC 2020 - Special Session in Connected and Autonomous Transportation Systems

[Patrick Hung]

Call For Papers
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Special Session in Connected and Autonomous Transportation Systems
to be held in the 2020 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC)
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Date: October 11, 2020 - October 14, 2020
Location: Toronto, Canada
http://smc2020.org/

Deadline for submission: April 30, 2020

The futuristic idea of autonomous vehicles are each day closer to our daily lives, and their benefits are about to change our quality of life. Technological advancements in the automobile and transportation sector have gained significant interest from governments, industry leaders, and citizens. Together Semi-Autonomous Vehicles (SAV) and Connected and Autonomous Vehicles (CAV) are making a revolution in these sectors. SAV/CAV offers benefits for private and public transportation by offering them better and more effective transportation services, such as the dramatic reduction of car crashes and driver fatigue. It includes vehicles as private and service (e.g., Uber) cars, buses for public transportation (which includes school buses) and trucks (e.g., garbage collector and agricultural trucks). The wide variety of SAV/CAV makes this topic of research particularly interesting, and its benefits are potentially available for different sections of society. What separates SAV from CAV definitions is their level of automation. According to the Society of Automotive Engineers International (SAE), the level of automation of vehicles ranges from level 0 to 5. Level 0 concerns vehicles that are entirely human-operated, while level 5 vehicles are fully automated. For example, in level 1 of automation, the vehicle may assist the driver with tasks like steering or acceleration. SAV is to be considered at least level 2 of vehicle automation. It enables the driver to remain fully engaged with the driving task, but with gradual transfer of control from human to machine. Level 2 automation features include adaptive cruise control and automatic emergency braking. In the industry, most of CAV classify as level 4 of automation, while the companies have carefully explored level 3. It may depend on sharing controlling aspects of the driving task, between machine and human, under some circumstances. It can be dangerous for both the driver and passengers due to the spare time between controlling exchange and human-decision making. Level 4 of autonomous capability means cars can self-drive in most conditions without human intervention. However, there are many open design challenges to achieve it, that include technical, ethical, and regulatory matters. A completely automated vehicle (level 5) can perform all driving functions under all conditions. In this situation, humans are just passengers. In general, SAV/CAV can be characterized by the following properties: (a) Ubiquitous computing (ubicomp): assessing information or being assessed interactively and autonomously everywhere and anywhere via various sensors over different standards, such as the Controller Area Network (CAN), which is a multi-node bus protocol for short messages transmission of trigger signals and measurement values to support distributed control systems; (b) Human-computer interaction (HCI): the essential interfaces of SAV/CAV that offer an interaction between the human and in-vehicle system in a context of Vehicle-to-Vehicle (V2V), Vehicle-to-Infrastructure (V2I) and IoT-to-Vehicle (I2V); and (c) Applications platform: allowing users to download the third-party application software in their in-vehicle system or even on the Internet of Things (IoT) for customizing the SAV/CAV, for example, an in-vehicle Infotainment for information and entertainment applications. These benefits, however, are conditioned to the overcoming of a series of Human-Vehicle Interaction (HVI) challenges. HVI concerns how a human performs tasks inside vehicles, and it has evolved dramatically over recent years. HVI interfaces evolved from buttons to composite panels, including speech recognition functionalities, computer vision resources, visual displays, Augmented Reality (AR), until Artificial Intelligence (AI) and robotics. Scenarios include self-driving assistance, entertainment, including privacy and security solutions. This special session should also further research on new best practices and directions for connected and autonomous transportation systems. Topics of interest include, but are not limited to:

* Architectures for autonomous self-driving
* Design implications for HVI
* Devices for in-vehicle systems
* Industry standards and solution stacks in SAV/CAV
* Interoperable and interactive middleware for in-vehicle systems
* Internet of Things (IoT) for SAV/CAV
* Social-technical models for SAV/CAV
* Security, privacy, and trust in SAV/CAV
* Testing and training platforms for SAV/CAV
* Theoretical frameworks for SAV/CAV
* In-vehicle companion robots
* Case Studies

Extended versions of accepted papers will be invited for submission by specific journal special issues. Further details will be announced soon.


Patrick C. K. Hung, Jing Ren, and Hossam A.Gabbar, Ontario Tech University, Canada
Shih-Chia Huang, National Taipei University of Technology, Taiwan



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