Perception, Modeling, State Estimation, and Dynamic Control of Intelligent Transportation Equipment
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Vehicular Sensing".
Deadline for manuscript submissions: 31 May 2026
Special Issue Editor
Interests: vehicle dynamics and control; design and advanced control of electrified chassis; decision planning; control of intelligent vehicles
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
In recent years, intelligent transportation equipment has rapidly emerged in many key fields such as aerospace, rail transit, and intelligent vehicles, becoming an important driving force for promoting modern technology and industrial development. Its core lies in precise perception, efficient modeling, reliable state estimation, and precise dynamic control. These technical elements are intertwined and work together to determine the performance, safety, and level of intelligence of intelligent transportation equipment.
Sensors play a crucial role in the perception process of intelligent transportation equipment. High precision and high reliability of sensor technology are key factors for achieving equipment intelligence. For example, LiDAR sensors can perceive real-time three-dimensional information of the surrounding environment of the carrying equipment, providing key data for path planning and obstacle recognition; inertial sensors and acceleration sensors can accurately measure the motion state of equipment, providing basic data support for state estimation and dynamic control. Meanwhile, multi-sensor fusion technology can integrate the data advantages of different types of sensors, improve perception accuracy and reliability, and provide more comprehensive and accurate information for intelligent decision-making of intelligent transportation equipment.
This Special Issue focuses on cutting-edge topics in the field of intelligent transportation equipment, aiming to provide a high-quality academic exchange platform for global researchers, gathering the latest research achievements and innovative practices in this field. We warmly welcome original research papers on the topics opf application of intelligent sensor technology in transportation equipment, accurate modeling methods for transportation equipment in complex environments, model-based and data-driven state estimation strategies, and advanced dynamic control algorithms.
This Special Issue will explore in depth how to improve the perception accuracy of environmental information by carrier equipment, achieve accurate modeling of its dynamic behaviors, and accurately estimate its state parameters under complex working conditions, thereby providing theoretical basis and technical support for designing efficient and robust dynamic control systems. Through these studies, we expect to promote significant progress in key performance indicators such as intelligence, automation, and safety of intelligent transportation equipment, contributing to the construction of a more intelligent, efficient, and reliable transportation equipment system.
Whether it is pioneering research on new types of transportation equipment or technological breakthroughs in the intelligent transformation of traditional transportation equipment, this Special Issue will focus on their innovative ideas and experimental verification results in perception, modeling, state estimation, and dynamic control. We believe that the publication of this Special Issue will inject new vitality into the continuous development of the field of intelligent transportation equipment, promote in-depth cooperation and exchanges between academia and industry, and jointly embrace the opportunities and challenges of the era of intelligent transportation equipment.
We look forward to your submissions.
Dr. Te Chen
Guest Editor
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Keywords
- intelligent transportation equipment
- autonomous vehicle
- sensor information fusion
- perception and decision-making
- complex dynamics modeling
- parameter identification
- state estimation
- advanced dynamics control
- nonlinear and robust control
- trajectory planning and tracking
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