#pedestrian-safety News & Analysis

3 articles tagged with #pedestrian-safety. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.

3 articles

AINeutralarXiv – CS AI · Jun 96/10

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Decoding Pedestrian Crossing Intention from Egocentric Vision via Vision Language Models

Researchers developed a method using vision language models to predict pedestrian crossing intentions from egocentric video footage, achieving state-of-the-art results through fine-tuning and incorporating contextual cues like eye gaze and ego motion. The approach frames pedestrian intent prediction as a visual question answering task and demonstrates 14.5% accuracy improvement over specialized baselines, with implications for autonomous vehicle safety systems.

AIBullisharXiv – CS AI · Jun 26/10

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DeepIPCv3: Event-Aware Multi-Modal Sensor Fusion for Sudden Pedestrian Crossing Avoidance

DeepIPCv3 is a novel autonomous driving framework that combines LiDAR and Dynamic Vision Sensor (DVS) data using transformer-based cross-modal attention to improve pedestrian collision avoidance. The system addresses critical safety gaps in frame-based perception by leveraging microsecond-level event streams, achieving state-of-the-art performance in sudden crossing scenarios.

AIBullisharXiv – CS AI · May 286/10

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Modeling Vehicle-Type-Specific Pedestrian Crash Avoidance Behavior in Safety-Critical Interactions Using Smooth-Mamba Deep Reinforcement Learning

Researchers developed SMamba-DDPG, a deep reinforcement learning framework that models how pedestrians behave differently when interacting with autonomous vehicles versus human-driven vehicles. The study found that pedestrians react faster to AVs and adopt lower crossing speeds, with AV interactions showing lower conflict rates than HDV scenarios.