Quantifying and comparing the effects of key risk factors on various types of roadway segment crashes with LightGBM and SHAP
Understanding and quantifying the effects of risk factors on crash frequency is of great
importance for developing cost-effective safety countermeasures. In this paper, the effects of …
importance for developing cost-effective safety countermeasures. In this paper, the effects of …
Identification of dynamic traffic crash risk for cross-area freeways based on statistical and machine learning methods
Y Yang, K He, Y Wang, Z Yuan, Y Yin, M Guo - Physica A: Statistical …, 2022 - Elsevier
Freeway traffic safety should be given great attention due to the frequent and serious
consequences that arise from freeway traffic crashes. With the possibility of obtaining high …
consequences that arise from freeway traffic crashes. With the possibility of obtaining high …
Road surface friction prediction using long short-term memory neural network based on historical data
Road surface friction significantly impacts traffic safety and mobility. A precise road surface
friction prediction model can help to alleviate the influence of inclement road conditions on …
friction prediction model can help to alleviate the influence of inclement road conditions on …
Predicting intersection crash frequency using connected vehicle data: A framework for geographical random forest
Accurate crash frequency prediction is critical for proactive safety management. The
emerging connected vehicles technology provides us with a wealth of vehicular motion data …
emerging connected vehicles technology provides us with a wealth of vehicular motion data …
Modeling of freeway real-time traffic crash risk based on dynamic traffic flow considering temporal effect difference
Y Yang, Y Yin, Y Wang, R Meng… - Journal of transportation …, 2023 - ascelibrary.org
With the development of traffic detection facilities technology, it is currently possible to obtain
high-resolution traffic flow data. Due to the particular driving characteristics of vehicles on …
high-resolution traffic flow data. Due to the particular driving characteristics of vehicles on …
Machine learning approaches for biomolecular, biophysical, and biomaterials research
CA Rickert, O Lieleg - Biophysics Reviews, 2022 - pubs.aip.org
A fluent conversation with a virtual assistant, person-tailored news feeds, and deep-fake
images created within seconds—all those things that have been unthinkable for a long time …
images created within seconds—all those things that have been unthinkable for a long time …
Inferring heterogeneous treatment effects of crashes on highway traffic: A doubly robust causal machine learning approach
Accurate estimating causal effects of crashes on highway traffic is crucial for mitigating the
negative impacts of crashes. Previous studies have built up a series of methods via …
negative impacts of crashes. Previous studies have built up a series of methods via …
On the interpretability of machine learning methods in crash frequency modeling and crash modification factor development
Abstract Machine learning (ML) model interpretability has attracted much attention recently
given the promising performance of ML methods in crash frequency studies. Extracting …
given the promising performance of ML methods in crash frequency studies. Extracting …
Geographically weighted random forests for macro-level crash frequency prediction
D Wu, Y Zhang, Q Xiang - Accident Analysis & Prevention, 2024 - Elsevier
Abstract Machine learning models such as random forests (RF) have been widely applied in
the field of road safety. RF is a prominent algorithm, overcoming the limitations of using a …
the field of road safety. RF is a prominent algorithm, overcoming the limitations of using a …
Monitoring public transit ridership flow by passively sensing Wi-Fi and Bluetooth mobile devices
Real-time public transit ridership flow and origin-destination (OD) information is essential for
improving transit service quality and optimizing transit networks in smart cities. The …
improving transit service quality and optimizing transit networks in smart cities. The …