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      IEEE ITSC|Distributed Hybrid Conference on September 23

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      本文來源:智車科技

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      The 25th IEEE International Conference on Intelligent Transportation Systems (IEEE ITSC 2022) is the annual flagship conference sponsored by the IEEE Intelligent Transportation Systems Society, with the theme of "Blockchain-based ITS: The Human Use of Cyber-Physical-Social Transportation Systems". This Distributed Hybrid Conference (DHC) starts from September 19 and lasts to October 7. During this period, a total of 145 Distributed Hybrid Conferences will be held in an orderly manner.

      On September 23, ITSC 2022 arranged in a distributed hybrid way and held FIVE Special Sessions and ONE Workshop of almost all frontier research and hot topics in the field of intelligent transportation, in terms of Perception, Decision-Making and Control Technologies for Intelligent Vehicles in Complex Driving Conditions, Vehicles in Complex Driving Conditions, 2nd Special Session on Cooperative Driving in Mixed Traffic I, 2nd Special Session on Cooperative Driving in Mixed Traffic II, BlockChain & Knowledge Automation, AI Empowered Modeling Solutions for CAV Impacts: From Individual Vehicle Control to Networked System Management, Emerging Data-driven Technologies and Machine Intellection for Traffic Prediction & Estimation.

      11 session chairs and 32 session presenters gathered to share their recent work and perspectives, related to advanced blockchain-based intelligent transportation systems.

      Agendas of September 23 is announced as follows:

      Special Session 19:Perception, Decision-Making and Control Technologies for Intelligent Vehicles in Complex Driving Conditions

      Session Chair:Hongyan Guo (Jilin University)

      Schedule: 8:00-9:30 (Beijing time), September 23, 2022.

      Abstract:

      As an important part of intelligent transportation system (ITS), complex traffic driving environment is a factor that cannot be ignored with high traffic accidents, which brings serious threats to driving safety. Different from normal driving conditions, the complex traffic environment will affect the accuracy of vehicle perception, the effectiveness of decision-making and the stability of control, thus posing a severe test to intelligent driving. Multi-vehicle interaction and vehicle-road coordination provide important opportunities for driving safety in complex environments. As the core components of intelligent driving, including vehicle formation control, human-vehicle perception, and pedestrian prediction, it will undoubtedly become an important research field in the future. At present, many problems of intelligent driving in complex traffic environment are still open and far from solved in the face of uncertain interference, communication constraints, and complex computing burden.

      Key words: Intelligent Driving, Driving Safety, ITS, Vehicle Formation Control, Human-vehicle Perception, Pedestrian Prediction


      Special Session 20: 2nd Special Session on Cooperative Driving in Mixed Traffic I

      Session Chair:Jia Hu Tongji University (moderator), Guodong Yin (Southeast University), Yi Zhang (Tsinghua University), Ziran Wang (Purdue University), Siyuan Gong (Chang’an University)

      Schedule: 9:30-11:00 (Beijing time), September 23, 2022.

      Abstract:

      With the advancement of vehicle-to-everything (V2X) communications, the concept of cooperative driving has been attracting increasing attention from both academia and industry. Connected vehicles, either driven by human drivers or automated controllers, are able to coordinate with each other or infrastructures through V2X communications in certain traffic scenarios to improve the overall performance. Cooperative Adaptive Cruise Control (CACC), cooperative ramp merging, connected eco-driving at signalized intersections, automated coordination at non-signalized intersections, among other cooperative driving applications of connected vehicles, have the potential to benefit the transportation system in terms of safety, mobility, resilience, and/or environmental sustainability.

      However, the market penetration rate of connected vehicles is expected to evolve gradually. There will certainly be a transition period where only a portion of the vehicles traveling in the traffic environment are connected (and potentially automated), while others have no V2X capabilities – either automated vehicles equipped with on-board sensors or legacy vehicles driven by human drivers. How to perform cooperative driving maneuvers in mixed traffic environments to allow the coordination among all these vehicle types remains an open research question.

      This will be the second special session of the series, focusing on cooperative driving in mixed traffic. It focuses on sharing the state-of-the-art design, modeling, algorithms, simulation, and field implementation of cooperative driving in mixed traffic, and identifies challenges as well as research needs, aiming to encourage cross-disciplinary cooperation.

      Key words: Connected Vehicles, Cooperative Driving, Mixed Traffic, Vehicle-to-everything (V2X)


      Special Session 21: 2nd Special Session on Cooperative Driving in Mixed Traffic II

      Session Chair:Siyuan Gong (Chang'an University)

      Schedule: 11:00-12:30 (Beijing time), September 23, 2022.

      Abstract:

      With the advancement of vehicle-to-everything (V2X) communications, the concept of cooperative driving has been attracting increasing attention from both academia and industry. Connected vehicles, either driven by human drivers or automated controllers, are able to coordinate with each other or infrastructures through V2X communications in certain traffic scenarios to improve the overall performance. Cooperative Adaptive Cruise Control (CACC), cooperative ramp merging, connected eco-driving at signalized intersections, automated coordination at non-signalized intersections, among other cooperative driving applications of connected vehicles, have the potential to benefit the transportation system in terms of safety, mobility, resilience, and/or environmental sustainability.

      However, the market penetration rate of connected vehicles is expected to evolve gradually. There will certainly be a transition period where only a portion of the vehicles traveling in the traffic environment are connected (and potentially automated), while others have no V2X capabilities – either automated vehicles equipped with on-board sensors or legacy vehicles driven by human drivers. How to perform cooperative driving maneuvers in mixed traffic environments to allow the coordination among all these vehicle types remains an open research question.

      This will be the second special session of the series, focusing on cooperative driving in mixed traffic. It focuses on sharing the state-of-the-art design, modeling, algorithms, simulation, and field implementation of cooperative driving in mixed traffic, and identifies challenges as well as research needs, aiming to encourage cross-disciplinary cooperation.

      Key Words: Connected Vehicles, Cooperative Driving, Mixed Traffic, Vehicle-to-everything (V2X)


      Workshop: BlockChain & Knowledge Automation

      Session Chair:Xiao Xue (College of Intelligence and Computing, Tianjin University), Juanjuan Li (Institute of Automation, Chinese Academy of Sciences)

      Schedule: 15:30-17:30 (Beijing time), September 23, 2022.

      Abstract:

      Blockchain and knowledge automation have emerged as a dynamic and fast-growing research area. As a novel decentralized architecture and distributed computing paradigm, blockchain has great potentials of revolutionizing increasingly centralized Cyber-Physical-Social Systems (CPSS), and reshaping traditional knowledge automation workflows. The key advantage of blockchain technology lies in the fact that it can enable the establishment of secured, trusted and decentralized autonomous ecosystems for various scenarios, thus it has been successfully applied in many fields. Blockchain is crucial to knowledge automation, which is a direction for further development of Artificial Intelligence technology and a normal general framework for dealing with management and control of CPSS. The goal of knowledge automation is dealing with issues of Uncertainty, Diversity and Complexity with capacity of Agility, Focus and Convergence.

      The Blockchain and Knowledge Automation (BKA) Workshop aims to report and discuss the latest research progresses and investigate the future research directions of blockchain and knowledge automation, to stimulate innovation in this emerging area.

      Key Words: Blockchain, Knowledge Automation, BKA, Cyber-Physical-Social Systems, CPSS.


      Special Session 17: AI Empowered Modeling Solutions for CAV Impacts: From Individual Vehicle Control to Networked System Management

      Session Chair:Wei Ma (The Hong Kong Polytechnic University)

      Schedule: 18:30-19:45 (Beijing time), September 23, 2022.

      Abstract:

      Connected and Automated Vehicles (CAVs) are destined to revolutionize the entire transportation system from individual driving to network traffic control and management. Traditional modeling and analysis approaches, including traffic flow theory, network modeling, traffic control, and optimization technologies, serve as a systematic and fundamental tool to assess the impacts of CAVs on all aspects of the intelligent transportation systems, and it paves the road for the deployment of CAVs in the future. For example, traffic flow theory and control has been used to study mixed traffic flow with CAVs on highways, at intersections, and on networks; various simulation studies and traffic equilibrium analyses have investigated societal impacts of CAVs; and dynamic traffic simulation has been applied to evaluate Transportation Network Companies (TNCs)’s market expansion plans with CAVs. On the other hand, scholars have witnessed great advances in traffic modeling solutions with the involvement of Artificial Intelligent (AI) technologies in recent years. It enables researchers and practitioners to address highly complicated transportation modeling problems that involve nonconvexity, nonlinearity, high dimensionality and uncertainty, and prohibitive computation difficulties. For example, reinforcement learning has been widely used for CAV trajectory control and traffic signal control, and deep learning is adopted in “prediction+optimization” schemes for smart mobility tasks like resource scheduling and vehicle routing.

      Key Words: Connected and Automated Vehicles, CAVs, Mixed Traffic Flow, Trajectory Control


      Special Session 18: Emerging Data-driven Technologies and Machine Intellection for Traffic Prediction & Estimation

      Session Chair:Yicheng Zhang (Institute for Infocomm Research, A*STAR)

      Schedule: 20:00-21:30 (Beijing time), September 23, 2022.

      Abstract:

      Traffic forecasting and pattern recognition are critical tasks when working with highly dynamic systems such as urban transportation and air traffic. Accurate traffic forecasting enables route planning, vehicle dispatching, and congestion mitigation. This topic is difficult to solve because of the complex and dynamic spatio-temporal relationships that exist between different sections of the road network. This research topic has expanded significantly over the last few decades as a result of the arrival of big data via various advanced sensors or probe vehicle data, satellite-based aviation data, and the development and growth of new AI models.

      This special session will raise awareness of emerging technologies in the domain of traffic prediction and estimation in the big data era. Methods enabled by data-driven technology and machine learning-based approaches are envisioned as the next generation of traffic prediction and estimation solutions.

      Key Words: Traffic Forecasting and Estimation, Pattern Recognition, Data-driven Technology


      Please continue to pay attention to IEEE ITSC 2022

      IEEE ITSC official website:https://www.ieee-itsc2022.org/#/

      [Conference Introduction]

      Blockchain-based ITS: The Human Use of Cyber-Physical-Social Transportation Systems

      The 25th IEEE International Conference on Intelligent Transportation Systems (IEEE ITSC 2022) is the annual flagship conference sponsored by the IEEE Intelligent Transportation Systems Society. From 1997 to 2021, it has been held 24 times, covering 24 cities in 12 countries in Asia, Europe, North America, South America and Oceania. The main conference of the 25th IEEE ITSC 2022 will be held in Macau, China. IEEE ITSC 2022 welcomes articles and presentations in the areas of intelligent transportation systems and automated driving, conveying new advances and developments in theory, modeling, simulation, testing, case studies, as well as large-scale deployment. The conference particularly invites and encourages prospective authors to share their recent research work, findings, perspectives, and developments related to advanced blockchain-based intelligent transportation systems.

      - End -

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