Guoyu, Zhang (Tongji University), Chen, Qian (Tongji University), Hang, Peng (Tongji University), Lu, Xiong (Tongji Unviersity), Sun, Jian (Tongji University)

Multi-Modality Fusion Perception Strategy Based on Adaptive Matching for Vehicle-Road Cooperation

Scheduled for presentation during the Invited Session "Cooperative Driving Technology for Connected Automated Vehicles" (WeAT10), Wednesday, September 25, 2024, 11:10−11:30, Salon 18

2024 IEEE 27th International Conference on Intelligent Transportation Systems (ITSC), September 24- 27, 2024, Edmonton, Canada

This information is tentative and subject to change. Compiled on October 7, 2024

Abstract

随着自动驾驶技术的不断发展，对交通场景的感知性能提出了新的要求，车路协同技术备受业界关注。面对日益复杂的交通场景和庞大的交互感知数据，如何在车路协同感知系统的检测精度和实时性需求之间取得平衡，成为亟待解决的问题。该文提出一种基于异构多模态感知数据的自适应选择方法和处理模型优化方法，对多端传感器数据进行评估和优化，并根据感知场景环境的复杂程度对特征提取模型的空间尺度进行优化，从而实现车路协同的准确实时感知。同时，针对不同环境复杂度的场景特性，引入多空间尺度调制模块，有效整合局部和非局部特征信息，增强了模型在车辆和道路协同感知场景中处理特征的能力。实验结果对比&#