实测验证了真实道路中协同变道预测的硬件架构设计与挑战。
Design Insights and Comparative Evaluation of a Hardware-Based Cooperative Perception Architecture for Lane Change Prediction
- 基于真实车辆硬件部署，构建协同变道预测系统
- 发现感知、通信与交通行为的实际瓶颈与可靠性问题
- 为同类系统落地提供可复用的实践经验
近年来，车道变更预测研究受到关注。现有大多数工作在仿真环境或预录数据集上进行，常依赖简化假设，如感知、通信和交通行为，这些假设在实际中未必成立。真实道路中的变道预测系统部署较少，且其面临的技术挑战、局限性及经验教训常未被充分记录。本研究通过在混合交通环境中进行真实硬件部署，探索协同变道预测，并分享实施与测试过程中浮现的设计洞见。重点揭示了系统运行中的瓶颈、可靠性问题与操作约束，这些因素直接影响系统行为。通过详实记录这些经验，本研究为后续类似系统的开发提供了实践指导。
原文摘要 · Abstract (English)
Research on lane change prediction has gained attention in the last few years. Most existing works in this area have been conducted in simulation environments or with pre-recorded datasets, these works often rely on simplified assumptions about sensing, communication, and traffic behavior that do not always hold in practice. Real-world deployments of lane-change prediction systems are relatively rare, and when they are reported, the practical challenges, limitations, and lessons learned are often under-documented. This study explores cooperative lane-change prediction through a real hardware deployment in mixed traffic and shares the insights that emerged during implementation and testing. We highlight the practical challenges we faced, including bottlenecks, reliability issues, and operational constraints that shaped the behavior of the system. By documenting these experiences, the study provides guidance for others working on similar pipelines.
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