Current pedestrian crossing signals operate on fixed timing without adjustment to pedestrian behavior, which can leave vulnerable road users (VRUs) such as the elderly, disabled, or distracted pedestrians stranded when the light changes. We introduce No Pedestrian Left Behind (NPLB), a real-time adaptive traffic signal system that monitors VRUs in crosswalks and automatically extends signal timing when needed. We evaluated five state-of-the-art object detection models on the BGVP dataset, with YOLOv12 achieving the highest mean Average Precision at 50% ([email protected]) of 0.756. NPLB integrates our fine-tuned YOLOv12 with ByteTrack multi-object tracking and an adaptive controller that extends pedestrian phases when remaining time falls below a critical threshold. Through 10,000 Monte Carlo simulations, we demonstrate that NPLB improves VRU safety by 71.4%, reducing stranding rates from 9.10% to 2.60%, while requiring signal extensions in only 12.1% of crossing cycles.

翻译：当前行人过街信号灯采用固定时序，无法根据行人行为进行调整，这可能导致老年人、残障人士或注意力分散的行人等弱势道路使用者在信号灯变换时被困于路中。我们提出"不让任何行人掉队"（NPLB）系统——一种实时自适应交通信号系统，能监测人行横道上的VRU，并在必要时自动延长信号灯时长。在BGVP数据集上对五种先进目标检测模型的评估显示，YOLOv12在平均精度（[email protected]）上以0.756的数值表现最优。NPLB将微调后的YOLOv12与ByteTrack多目标追踪模块及自适应控制器集成，当剩余通行时间低于临界阈值时自动延长行人相位。通过10,000次蒙特卡洛模拟，我们证明NPLB可将VRU安全性提升71.4%，使行人滞留率从9.10%降至2.60%，且仅需在12.1%的过街周期中启动信号延长。