Special Session Ⅳ

Perception and Cooperative Control of Intelligent Transportation Equipment 智能载运装备感知与协同控制 Submission Deadline: July 30, 2026

Chair:	Co-chair:

Jiankun Peng Southeast University, China	Hailong Zhang North University of China, China

Keywords:
· Intelligent Transportation Equipment (智能载运装备) · Motion and Stability Control (运动与稳定性控制) · Intelligent Perception (智能感知) · Cooperative Control (协同控制) · Data-Driven (数据驱动)

Topics:
· Dynamics Modeling, State Estimation, and Motion Prediction of Intelligent Transportation Equipment(智能运载装备动力学建模、状态估计及运动预测) · Multisensor Fusion and Environmental Perception for Intelligent Transportation Equipment (智能载运装备的多传感器融合及环境感知) · Object Detection, Recognition, Tracking, and Scene Understanding in Traffic and Low-Altitude Environments (交通与低空环境中的目标检测、识别、跟踪及场景理解) · Detection of Small, Occluded, and Moving Targets in Complex Environments (复杂环境下小目标、遮挡目标及运动目标检测) · Data-driven chassis control (数据驱动底盘控制) · Trajectory Tracking, Path Following, and Vehicle Motion Control (车辆轨迹跟踪、路径跟随及运动控制) · Motion Planning, Obstacle Avoidance, and Path Update (运动规划、避障及路径更新) · Vehicle Platooning, Formation Control, and Cooperative Collision Avoidance (车辆编队、队形控制及协同避障) · Simulation, Testing, and Experimental Validation of Intelligent Transportation Equipment (智能载运装备系统的仿真、测试及实验验证)

Summary:
Intelligent transportation equipment has been widely applied in intelligent transportation, low-altitude operations, logistics, and special-purpose missions. Its reliable operation in complex and uncertain environments requires the deep integration of environmental perception, dynamics modeling, state estimation, motion prediction, intelligent control, and multi-platform cooperation. This special session focuses on the fundamental theories, key technologies, and engineering applications of intelligent transportation equipment, and encourages the integration of model-driven and data-driven methods to improve perception accuracy, state estimation reliability, motion stability, autonomous decision-making capability, cooperative collision avoidance, and overall system safety under variable operating conditions, environmental disturbances, communication constraints, and model uncertainties. The special session welcomes researchers and engineers from vehicle engineering, mechanical engineering, control science, artificial intelligence, computer vision, robotics, and transportation engineering. It aims to provide a platform for exchanging advances in fundamental theories, algorithms, simulation studies, and experimental research, and to promote the development of intelligent transportation equipment toward high-accuracy perception, stable control, cooperative operation, and reliable autonomy.

智能载运装备已广泛应用于智能交通、低空作业、物流运输和特种任务等场景。其在复杂、不确定环境下的可靠运行，需要环境感知、动力学建模、状态估计、运动预测、智能控制及多装备协同等技术的深度融合。本专题聚焦智能载运装备的基础理论、关键技术与工程应用，鼓励模型驱动与数据驱动方法的融合应用，以提升变工况、环境扰动、通信约束及模型不确定条件下的感知精度、状态估计可靠性、运动稳定性、自主决策能力、协同避碰能力与系统安全性。本专题面向车辆工程、机械工程、控制科学、人工智能、计算机视觉、机器人及交通运输等领域的科研人员与工程技术人员，旨在为基础理论、算法方法、仿真研究及实验成果提供交流平台，推动智能载运装备向高精度感知、稳定控制、协同运行和可靠自主方向发展。