AIMC Topic: Safety

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Understanding perceived ride safety and trust formation in robotaxi services under day and night conditions.

Scientific reports
This study investigates how passengers perceive ride safety and develop trust in Robotaxi services in the absence of human drivers, with a focus on differences between daytime and nighttime scenarios. Drawing on the Elaboration Likelihood Model (ELM)...

Predicting geriatric environmental safety perception assessment using LightGBM and SHAP framework.

Scientific reports
Global population aging highlights the need to understand how the elderly perceive safety in urban public spaces. This study used image semantic segmentation to identify key visual elements from panoramic images. A dataset was created by combining ma...

Enhancing the YOLOv8 model for realtime object detection to ensure online platform safety.

Scientific reports
In today's digital environment, effectively detecting and censoring harmful and offensive objects such as weapons, addictive substances, and violent content on online platforms is increasingly important for user safety. This study introduces an Enhan...

Learning salient representation of crashes and near-crashes using supervised contrastive variational autoencoder.

Accident; analysis and prevention
Models capable of learning representations that are salient in safety-critical events (SCEs; including crashes and near-crashes) are crucial for road safety. This study proposes a novel deep learning model, the supervised contrastive variational auto...

Predicting occupant response curves in vehicle crashes via Attention-enhanced multimodal temporal Network.

Accident; analysis and prevention
Accurately predicting safety responses, especially occupant crash response curves across multiple body regions, plays a crucial role in advancing vehicle crash safety by enabling design optimization and reducing the reliance on costly physical testin...

Cyclist crash severity modeling: A hybrid approach of XGBoost-SHAP and random parameters logit with heterogeneity in means and variances.

Journal of safety research
INTRODUCTION: Across the globe, policymakers are focusing on boosting sustainable transport options, notably cycling, to foster eco-friendly urban environments. However, the persistent safety challenges cyclists face continues to hinder these efforts...

Cyclist safety in the digital age: A review of advanced warning technologies.

Accident; analysis and prevention
Improving the safety of cyclists, who are considered vulnerable road users, is essential. Implementing a warning system that alerts cyclists to nearby hazards is an effective method to improve their safety. Nevertheless, the literature needs a compre...

Modeling crash avoidance behaviors in vehicle-pedestrian near-miss scenarios: Curvilinear time-to-collision and Mamba-driven deep reinforcement learning.

Accident; analysis and prevention
Interactions between vehicle-pedestrian at intersections often lead to safety-critical situations. This study aims to model the crash avoidance behaviors of vehicles during interactions with pedestrians in near-miss scenarios, contributing to the dev...

Simulation of human-vehicle interaction at right-turn unsignalized intersections: A game-theoretic deep maximum entropy inverse reinforcement learning method.

Accident; analysis and prevention
The safety of pedestrians in urban transportation systems has emerged as a significant research topic. As a vulnerable group within this transportation framework, pedestrians encounter heightened safety risks in complex urban road environments. Prote...

Spatial heterogeneity effect of built environment on traffic safety using geographically weighted atrous convolutions neural network.

Accident; analysis and prevention
The built environment exerts a significant influence on the frequency and severity of traffic accidents. Spatially uniform assumptions on the impacts of built environment factors commonly employed in existing research may lead to inconsistent and con...