Forthcoming and Online First Articles

International Journal of Vehicle Autonomous Systems

International Journal of Vehicle Autonomous Systems (IJVAS)

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International Journal of Vehicle Autonomous Systems (4 papers in press)

Regular Issues

  • Analysis of recent trends and developments in assisted and automated driving systems: a systematic review   Order a copy of this article
    by Shivaji Thorat, Ramesh Pawase 
    Abstract: Surface road transportation is an essential part of our daily life, enabling us to commute to work, school, hospital, and many places ubiquitously. This leads to an increased need of private transportation. Also, road safety is potentially impacted by driving under the influence and increased usage of mobiles during driving Distracted driving is becoming a major reason for increased road accidents today. Thus, there seems a need of advanced driver assistance systems (ADAS) and automated driving (AD) in vehicles to ensure human safety in risky road environments. It has several benefits such as increased road safety, traffic jam reduction, low fuel consumption, and minimal human intervention in safety-critical driving conditions. This review paper delivers an overview of recent technological trends and advancements that happened in ADAS/AD systems with its limitations (or challenges) and opportunities ahead.
    Keywords: advanced driver assistance systems; automated driving; autonomous vehicles; electrical and electronics architectures; road safety; sensor fusion and radars.
    DOI: 10.1504/IJVAS.2024.10063840
     
  • A decentralised asynchronous federated learning framework for autonomous driving   Order a copy of this article
    by Xiaoli Li, Ting Cai, Wei Xiong, Degang Xu 
    Abstract: Obtaining more information from other vehicles to accurately identify the road environment is an urgent issue for autonomous driving. However, collecting road environmental information directly from other vehicles may violate personal privacy. Federated learning can achieve multi-vehicle collaborative sensing of the road environment while protecting data privacy. We propose a decentralized asynchronous federated learning framework based on blockchain. Firstly, using blockchain to replace the central server of traditional federated learning architecture avoids the untrustworthy issues caused by the central architecture. Secondly, the blockchain module includes scoring contract units and incentive contract units to prevent malicious vehicle attacks, and designs fair incentive mechanisms to ensure the ecological health and sustainable development of federated learning. Thirdly, using the asynchronous federated learning algorithm, blockchain can immediately aggregate model updates from vehicles, greatly improving the overall training flexibility and real-time performance. Experimental results demonstrate the effectiveness of the proposed framework.
    Keywords: autonomous driving; blockchain; federated learning; asynchronous; decentralised.
    DOI: 10.1504/IJVAS.2024.10064091
     
  • Classification on unmanned underwater vehicles: a review   Order a copy of this article
    by Arpan Ghatak, Koena Mukherjee, Yogesh Singh 
    Abstract: This paper represents a concise survey on different Unmanned Underwater vehicle, commonly known as UUV. These unmanned vehicles are classified into two categories, one is Remotely Underwater Vehicle (ROV) and another is Autonomous Underwater Vehicle (AUV). In this Survey paper, the survey is concentrated into different types of ROVs and AUVs and functionality of these vehicles. The material classification and components used to construct any underwater vehicle and different fundamental aspects of AUV design is also briefly described. A brief progress work over the years on different types of unmanned underwater vehicle is done to understand the progression of these underwater robots.
    Keywords: unmanned underwater vehicles; DOF; biomimetic AUV; underwater glider; autonomous underwater vehicle.
    DOI: 10.1504/IJVAS.2024.10064856
     
  • A review on hardware in loop testing for various SAE levels of autonomous vehicle subsystems   Order a copy of this article
    by M. Siddharth, A. Rammohan 
    Abstract: The complexity of automobiles has increased tremendously in this decade to address environmental issues, customers' sophisticated demands, and safety. Electric Vehicles (EV) and Autonomous Vehicles (AV) have a lot of new cutting-edge technologies that have been incorporated into them. EVs and AVs rely on a combination of cameras, sensors and artificial intelligence algorithms for navigation and decision-making on the road. This development in EV and AV subsystems requires a platform to test and validate the developed systems effectively and safely. Hardware in the Loop (HIL) is one of the solutions used to validate the models or prototypes developed in the latest automotive systems. HIL can closely mimic the actual plant model and is used to evaluate the automotive control system before building it into a real-time system. HIL testing adaptation for the autonomous platforms from SAE level 0 vehicles to SAE level 4 vehicles, such as drivability development and regenerative brake by wire, and longitudinal and lateral automation, are elaborated in this review.
    Keywords: vehicle safety; hardware-in-the-loop; automotive control systems; testing and validation.
    DOI: 10.1504/IJVAS.2024.10064857