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Injury severity prediction of traffic crashes with ensemble machine learning techniques: A comparative study
A better understanding of injury severity risk factors is fundamental to improving crash
prediction and effective implementation of appropriate mitigation strategies. Traditional …
prediction and effective implementation of appropriate mitigation strategies. Traditional …
Transparent deep machine learning framework for predicting traffic crash severity
Abstract Analysis of crash injury severity is a promising research target in highway safety
studies. A better understanding of crash severity risk factors is vital for the proactive …
studies. A better understanding of crash severity risk factors is vital for the proactive …
Automated vehicle data pipeline for accident reconstruction: New insights from LiDAR, camera, and radar data
As automated vehicles are deployed across the world, it has become critically important to
understand how these vehicles interact with each other, as well as with other conventional …
understand how these vehicles interact with each other, as well as with other conventional …
Analyzing the impact of curve and slope on multi-vehicle truck crash severity on mountainous freeways
H Wen, Z Ma, Z Chen, C Luo - Accident Analysis & Prevention, 2023 - Elsevier
Many studies examine the road characteristics that impact the severity of truck crash
accidents. However, some only analyze the effect of curves or slopes separately, ignoring …
accidents. However, some only analyze the effect of curves or slopes separately, ignoring …
The dilemma of road safety in the eastern province of Saudi Arabia: Consequences and prevention strategies
Road traffic crashes (RTCs) are one of the most critical public health problems worldwide.
The WHO Global Status Report on Road Safety suggests that the annual fatality rate (per …
The WHO Global Status Report on Road Safety suggests that the annual fatality rate (per …
The role of pre-crash driving instability in contributing to crash intensity using naturalistic driving data
While the cost of crashes exceeds $1 Trillion a year in the US alone, the availability of high-
resolution naturalistic driving data provides an opportunity for researchers to conduct an in …
resolution naturalistic driving data provides an opportunity for researchers to conduct an in …
A latent class approach for driver injury severity analysis in highway single vehicle crash considering unobserved heterogeneity and temporal influence
Temporal variation has been recognized as one of the major sources of unobserved
heterogeneity in traffic safety research that has not been completely addressed. Overlooking …
heterogeneity in traffic safety research that has not been completely addressed. Overlooking …
Impact of traffic and road infrastructural design variables on road user safety–a systematic literature review
Road transportation is more favoured as it is less expensive and relatively faster than other
modes of transportation. A higher probability of getting involved in crashes reveals its …
modes of transportation. A higher probability of getting involved in crashes reveals its …
Applying hierarchical logistic models to compare urban and rural roadway modeling of severity of rear-end vehicular crashes
A rear-end crash is a widely studied type of road accident. The road area at the crash scene
is a factor that significantly affects the crash severity from rear-end collisions. These road …
is a factor that significantly affects the crash severity from rear-end collisions. These road …
Vehicle collisions analysis on highways based on multi-user driving simulator and multinomial logistic regression model on US highways in Michigan
Traffic collision on the highway has become a serious issue because they delay the
sustainable development of society. Highway accidents on I-69 have one of the highest …
sustainable development of society. Highway accidents on I-69 have one of the highest …