Ⅰ- SI title: Special Issue on Active Sensing, Safety Risk Assessment, and Advanced Control for Intelligent Chassis Systems
Journal: Chinese Journal of Mechanical Engineering (IF: 4.6, JCR Q1)
Information: Intelligent chassis systems are the basic platform for autonomous driving systems, cockpit systems, and power systems, and play a crucial role in the progress and innovation of automotive technology. With the intelligent chassis system, automobiles can realize autonomous navigation, automatic parking, remote vehicle monitoring, and other functions, providing users with a more convenient and safer travel experience.
With the integration of multiple sensors into the chassis system, the intelligent chassis system senses the external traffic environment (e.g., information such as surrounding vehicles' motion, the tire-road friction coefficient, etc.) and vehicle dynamic states (e.g., center-of-mass side deviation angle, etc.) with greater accuracy. Intelligent chassis systems can assess in real time the driving risks caused by vehicle-vehicle collisions and dynamic instability based on multi-source information. Furthermore, after accurately measuring the risk of driving, the vehicle needs to be precisely controlled to avoid accidents, and the design of the controller usually needs to satisfy the requirements of real-time and robustness.
Although the research related to intelligent chassis systems is rapidly growing, there are still problems such as low perception accuracy, difficulty in recognizing safety risks, and ineffective vehicle control. The combination of artificial intelligence and traditional model-based methods is the key to solving these problems. In this background, the purpose of this special session is to establish a platform for researchers and practitioners to share their latest findings, thereby contributing to the advancement of intelligent chassis systems, covering topics including but not limited to:
Multi-sensor fusion for macro-detection and micro-identification of roads
Multi-modal object detection in intelligent chassis systems
Fault diagnosis of intelligent chassis systems
State estimation and parameters identification for intelligent chassis systems
Cross-domain safety risk assessment of intelligent chassis systems
Personalized Human-Machine Interaction for Intelligent Chassis Systems
Multi-domain distributed cooperative control of intelligent chassis systems
Data-driven learning control of intelligent chassis systems
Submission Deadline: 31 December 2024
Ⅱ - SI title: Recent Advances in Safety and Reliability for Transportation Cyber-Physical Systems (T-CPS)
Journal: IEEE Transactions on Intelligent Transportation Systems (IF: 7.9, JCR Q1)
Information: Cyber-Physical Systems is an exciting growing research field with the benefits of efficiency and flexibility improvement, safety monitoring, and control enhancement, and have attracted the attention of many researchers. CPS has propelled transportation system innovation and formed a Transportation Cyber-Physical System (T-CPS). TCPS aims to merge the 3C technologies of Computing, Communication, and Control, integrate transportation information elements with transportation physical elements, and leverage the advantages of information technology in perception, transmission, and optimization control. This special issue will promote state-of-the-art research covering all aspects of safety control, dependability, and fault tolerance in T-CPS through contributions from scholars, contributing to the growth in the research and development of T-CPS. Particularly, authors are encouraged to submit their original research and review articles in theoretical, methodological, or practical focuses, such as simulation models, algorithms, experiments, and applications for big complex reliable transportation systems.
Case studies, test beds, prototypes, and practical systems for T-CPS
Dependability, Security, and privacy issues for T-CPS
Safe control systems design for T-CPS
Fault diagnostics for T-CPS
Alarm management and safety monitoring
Safety protection in T-CPS
Intrusion detection and attacker localization for cyber-physical systems
Model-based process risk assessment and prevention
Testing and verification of dependable T-CPS
Model-based control and estimation algorithms for T-CPS
Machine learning-based methods for safety and reliability of T-CPS
Submission Deadline: 1 October 2024
Ⅲ - SI title: Advancements in Safety-Critical Control for Autonomous Intelligent Systems
Journal: International Journal of Control, Automation, and Systems (IF: 2.5, JCR Q2)
Information: In recent years, the rapid advancements in artificial intelligence (AI), robotics, and automation technologies have led to the emergence of intelligent automation systems with unprecedented capabilities. These systems, including automated storage and retrieval systems, self-driving vehicles, and various types of autonomous robots, have the potential to revolutionize industries and everyday life. However, the autonomous operation of these systems introduces new challenges, particularly in ensuring their safety and reliability, which are crucial for their widespread adoption and acceptance.
The aim of this special issue is to address these challenges by focusing on "Advancements in Safety-Critical Control for Autonomous Intelligent Systems." The primary motivation behind this special issue is to provide a platform for researchers and practitioners to share insights, methodologies, and innovative solutions aimed at enhancing the safety and reliability of intelligent automation systems. By bringing together experts from the fields of control, robotics, and AI, this special issue seeks to advance the state-of-the-art in safety-critical control and contribute to the development of safer and more reliable autonomous systems.
The topics of interest within the scope of this Special Issue include (but are not limited to) the following:
Intelligent fault detection and fault-tolerant control of intelligent automation systems
Reliability and traceability of decision-making for intelligent automation systems
Risk assessment of artificial intelligence (AI)-based automation systems
Model-based safety and cybersecurity assessment of intelligent automation system
Ethical framework for designing automation systems
Interests and risks of learning-based control
Conflict detection and resolution of intelligent automation systems
Safety- and security-related issues
Functional safety and system security in automation systems
Human-robot collaboration-Risk assessment of intelligent automation
Design, development, validation, and applications of intelligent automation systems (e.g., unmanned ground vehicles (UGV), unmanned aerial vehicles (UAV), unmanned underwater vehicles (UUV))
Submission Deadline: 31 December 2024
Ⅳ - SI title: Enhancing Safety in Connected Automated Vehicles (CAVs) for Mixed Traffic Environments
Journal: IET Intelligent Transport Systems (IF: 2.3, JCR Q2)
Information: Intelligent transportation systems (ITS) leverage information and communication technologies to enhance the efficiency, safety, and sustainability of road transportation. Connected automated vehicles (CAVs) play a crucial role in ITS implementation as they enable communication with other vehicles and infrastructure, facilitating more efficient traffic management and safer driving experiences. The implementation of connected vehicles in intelligent transportation systems will revolutionize driving. However, due to the progressive deployment of such promising technologies, mixed traffic - in which connected and automated vehicles (CAVs) with different levels of automation and traditional human-driven vehicles coexist - will persist for a long time.
Taking into account that CAVs will need to navigate mixed-traffic environments, there is a pressing need to address a multitude of challenges, of which safety is at the forefront. Safety serves as the bedrock of ITS, and corresponding safety measures, such as collision avoidance systems, robust cybersecurity protocols, and rigorous validation testing, are integral for ensuring the reliability and trustworthiness of CAVs. Additionally, safety-relevant interactions between CAVs with different levels of automation and connectivity, between CAVs and human-driven vehicles, and between CAVs and other road users (e.g., vulnerable road users) are vital for ensuring that CAVs proactively prevent accidents, protect road users, and enhance overall road safety. This special issue is dedicated to exploring progress on the use of CAVs in mixed-traffic environments, with a primary focus on safety. The guest editors encourage submission of research that seeks to enhance the comprehension and applications of CAVs, toward advancing progress in the field.
Topics for this call for papers include but not restricted to:
Fault detection and diagnosis for CAVs under mixed traffic environments
Emergency response systems for CAVs under mixed traffic environments
Event detection based on V2V and V2I connectivity under mixed traffic environments
Real-time collision avoidance systems for CAVs under mixed traffic environments
User behaviour analysis for CAVs under mixed traffic environments
Safety-critical decision-making for CAVs under mixed traffic environments
Vehicle–pedestrian/vehicle/others interaction modelling for CAVs under mixed traffic environments
Hazard perception and avoidance systems for CAVs under mixed traffic environments
Testing, evaluation and verification for CAVs under mixed traffic environments
Submission Deadline: 31 October 2024