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 …
Macro-level literature analysis on pedestrian safety: Bibliometric overview, conceptual frames, and trends
Due to the high volume of documents in the pedestrian safety field, the current study
conducts a systematic bibliometric analysis on the researches published before October 3 …
conducts a systematic bibliometric analysis on the researches published before October 3 …
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 …
A negative binomial Lindley approach considering spatiotemporal effects for modeling traffic crash frequency with excess zeros
Statistical analysis of traffic crash frequency is significant for figuring out the distribution
pattern of crashes, predicting the development trend of crashes, formulating traffic crash …
pattern of crashes, predicting the development trend of crashes, formulating traffic crash …
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 …
Advancing proactive crash prediction: A discretized duration approach for predicting crashes and severity
Driven by advancements in data-driven methods, recent developments in proactive crash
prediction models have primarily focused on implementing machine learning and artificial …
prediction models have primarily focused on implementing machine learning and artificial …
A new econometric approach for modeling several count variables: a case study of crash frequency analysis by crash type and severity
There is limited adoption of research modeling crash severity frequency considering
different crash types due to the challenge associated with analyzing large number of …
different crash types due to the challenge associated with analyzing large number of …
Multivariate Poisson-Lognormal models for predicting peak-period crash frequency of joint on-ramp and merge segments on freeways
Because of a growing crash occurrence in conflict areas, the ramp and merge segments on
freeways are a concern for transportation researchers and practitioners. Therefore, short …
freeways are a concern for transportation researchers and practitioners. Therefore, short …
Predicting motorcycle crash injury severity using weather data and alternative Bayesian multivariate crash frequency models
Motorcycle crashes constitute a very high proportion of the overall motor vehicle fatalities in
the United States, and many studies have examined the influential factors under various …
the United States, and many studies have examined the influential factors under various …
A Bayesian multivariate hierarchical spatial joint model for predicting crash counts by crash type at intersections and segments along corridors
The safety and operational improvements of corridors have been the focus of many studies
since they carry most traffic on the road network. Estimating a crash prediction model for total …
since they carry most traffic on the road network. Estimating a crash prediction model for total …