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Journal of Autonomous Vehicles and Systems is a peer-reviewed journal published by ASME, covering Robotic Path Planning Algorithms, Autonomous Vehicle Technology and Safety, Robotics and Sensor-Based Localization. Over its lifetime it has published 84 papers, which have received 255 citations.
| Publisher | ASME |
|---|---|
| Reference style | Numbered (ASME) Numbered — [1], [2] in the text [1] Smith, A., Jones, B., and Lee, C., 2023, "A Representative Article Title," Journal of Autonomous Vehicles and Systems, 12(3), pp. 45–58.
Formats any DOI in Journal of Autonomous Vehicles and Systems style. No sign-up. |
| Publishes research in | Robotic Path Planning Algorithms Autonomous Vehicle Technology and Safety Robotics and Sensor-Based Localization Traffic control and management Vehicle Dynamics and Control Systems |
| ISSN | 2690-702X |
| Citation impact (2-yr) | 0.8 |
| h-index | 8 |
| i10-index | 7 |
| Top institutions publishing here | United States Army |
| You get | A submission-ready PDF and the editable LaTeX source — ready to submit. |
Citations each year’s papers have accumulated so far — the most recent years are still building up.
Abstract Research and technology in autonomous vehicles is beginning to become well recognized among computer scientists and engineers. Autonomous vehicles contain a combination of global positioning system (GPS), light detection and ranging (LIDAR), cameras, radio detection and ranging (RADAR), and ultrasonic sensors (which are hardly ever included). These autonomous vehicles use no less than two…
Abstract Computer simulation can be a useful tool when designing robots expected to operate independently in unstructured environments. In this context, one needs to simulate the dynamics of the robot’s mechanical system, the environment in which the robot operates, and the sensors which facilitate the robot’s perception of the environment. Herein, we focus on the…
Abstract Safe trajectory planning for high-performance automated vehicles in an environment with both static and moving obstacles is a challenging problem. Part of the challenge is developing a formulation that can be solved in real-time while including the following set of specifications: minimum time-to-goal, a dynamic vehicle model, minimum control effort, both static and moving…
Abstract Hazard analysis is the core of numerous approaches to safety engineering, including the functional safety standard ISO-26262 (FuSa) and Safety of the Intended Function (SOTIF) ISO/PAS 21448. We focus on addressing the immense challenge associated with the scope of training and testing for rare hazard for autonomous drivers, leading to the need to train…
Abstract This paper proposes a learning reference governor (LRG) approach to enforce state and control constraints in systems for which an accurate model is unavailable. This approach enables the reference governor to gradually improve command tracking performance through learning while enforcing the constraints during learning and after learning is completed. The learning can be performed…
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