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 …
Real-time conflict-based Bayesian Tobit models for safety evaluation of signalized intersections
Highlights•Conflict-based real-time safety performance functions are developed for
signalized intersections.•Several Tobit models including GRP-Tobit, RI-Tobit, and GRP-Tobit …
signalized intersections.•Several Tobit models including GRP-Tobit, RI-Tobit, and GRP-Tobit …
Anticipated Collision Time (ACT): A two-dimensional surrogate safety indicator for trajectory-based proactive safety assessment
SP Venthuruthiyil, M Chunchu - Transportation research part C: emerging …, 2022 - Elsevier
Abstract Surrogate Safety Measures (SSMs) are widely used to assess potential crash risk
proactively. Notably, most of the existing safety indicators are fundamentally designed to …
proactively. Notably, most of the existing safety indicators are fundamentally designed to …
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 …
Temporal instability of truck volume composition on non-truck-involved crash severity using uncorrelated and correlated grouped random parameters binary logit …
M Fanyu, NN Sze, S Cancan, C Tiantian… - Analytic Methods in …, 2021 - Elsevier
With the growing demand for inter-city freight transport, proportion of trucks in the freeway
traffic has been increasing in China and worldwide in the past decade. There have been …
traffic has been increasing in China and worldwide in the past decade. There have been …
The effect of human mobility and control measures on traffic safety during COVID-19 pandemic
As mobile device location data become increasingly available, new analyses are revealing
the significant changes of mobility pattern when an unplanned event happened. With …
the significant changes of mobility pattern when an unplanned event happened. With …
A joint probability model for pedestrian crashes at macroscopic level: Roles of environment, traffic, and population characteristics
Road safety is a major public health issue, with road crashes accounting for one-fourth of all
documented injuries. In these crashes, pedestrians are more vulnerable to fatal and/or …
documented injuries. In these crashes, pedestrians are more vulnerable to fatal and/or …
Modeling correlation and heterogeneity in crash rates by collision types using full Bayesian random parameters multivariate Tobit model
Crashes present different collision types. There usually exist unobserved risk factors which
could jointly affect crash rates of different types, resulting in correlation and heterogeneity …
could jointly affect crash rates of different types, resulting in correlation and heterogeneity …
A multivariate spatial model of crash frequency by transportation modes for urban intersections
This study proposes a multivariate spatial model to simultaneously analyze the occurrence
of motor vehicle, bicycle and pedestrian crashes at urban intersections. The proposed model …
of motor vehicle, bicycle and pedestrian crashes at urban intersections. The proposed model …
A deep generative approach for crash frequency model with heterogeneous imbalanced data
Crash frequency model is often subject to excessive zero observation because of the rare
nature of crashes. To address the problem of imbalanced crash data, a deep generative …
nature of crashes. To address the problem of imbalanced crash data, a deep generative …