AIMC Topic: Built Environment
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Crash prediction based on traffic platoon characteristics using floating car trajectory data and the machine learning approach.
Accident; analysis and prevention
Oct 4, 2019
Predicting crash propensity helps study safety on urban expressways in order to implement countermeasures and make improvements. It also helps identify and prevent crashes before they happen. However, collecting real-time wide-coverage traffic inform...
Expressway crash risk prediction using back propagation neural network: A brief investigation on safety resilience.
Accident; analysis and prevention
Jan 17, 2019
This study presents the work in predicting crash risk on expressways with consideration of both the impact of safety critical events and traffic conditions. The traffic resilience theory is introduced to learn safety problems from the standpoint of 1...
Real-time crash prediction models: State-of-the-art, design pathways and ubiquitous requirements.
Accident; analysis and prevention
Jan 8, 2019
Proactive traffic safety management systems can monitor traffic conditions in real-time, identify the formation of unsafe traffic dynamics, and implement suitable interventions to bring unsafe conditions back to normal traffic situations. Recent adva...
A spatiotemporal deep learning approach for citywide short-term crash risk prediction with multi-source data.
Accident; analysis and prevention
Nov 1, 2018
The primary objective of this study is to investigate how the deep learning approach contributes to citywide short-term crash risk prediction by leveraging multi-source datasets. This study uses data collected from Manhattan in New York City to illus...
Use of Deep Learning to Examine the Association of the Built Environment With Prevalence of Neighborhood Adult Obesity.
JAMA network open
Aug 3, 2018
IMPORTANCE: More than one-third of the adult population in the United States is obese. Obesity has been linked to factors such as genetics, diet, physical activity, and the environment. However, evidence indicating associations between the built envi...
Context-dependent effects of built environment factors on pedestrian-injury severities with imbalanced and high dimensional crash data.
Accident; analysis and prevention
Aug 1, 2025
Built environment is an important component that influences pedestrian injury severities in pedestrian-vehicle crashes. Previous studies indicated that the effects of various built environment factors on pedestrian injury severities are heterogeneous...
Revealing the impacts of the built environment factors on pedestrian-weighted air pollutant concentration using automated and interpretable machine learning.
Journal of environmental management
Jul 1, 2025
Urban air pollution poses significant health risks, especially to pedestrians due to their proximity to pollutants and lack of physical protection. Understanding the influence of built environment factors is essential to mitigate this pollution and s...
Deep Learning-Based Assessment of Built Environment From Satellite Images and Cardiometabolic Disease Prevalence.
JAMA cardiology
Jun 1, 2024
IMPORTANCE: Built environment plays an important role in development of cardiovascular disease. Large scale, pragmatic evaluation of built environment has been limited owing to scarce data and inconsistent data quality.
Artificial intelligence-based assessment of built environment from Google Street View and coronary artery disease prevalence.
European heart journal
May 7, 2024
BACKGROUND AND AIMS: Built environment plays an important role in the development of cardiovascular disease. Tools to evaluate the built environment using machine vision and informatic approaches have been limited. This study aimed to investigate the...
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