A systematic map** review of surrogate safety assessment using traffic conflict techniques
Safety assessment of road sections and networks have historically relied on police-reported
crash data. These data have several noteworthy and significant shortcomings, including …
crash data. These data have several noteworthy and significant shortcomings, including …
A systematic review of traffic conflict-based safety measures with a focus on application context
Relative to safety assessment using data from observed crashes, conflict-based road safety
assessment can potentially provide additional insights into crash causation processes …
assessment can potentially provide additional insights into crash causation processes …
Toward safer highways, application of XGBoost and SHAP for real-time accident detection and feature analysis
Detecting traffic accidents as rapidly as possible is essential for traffic safety. In this study, we
use eXtreme Gradient Boosting (XGBoost)—a Machine Learning (ML) technique—to detect …
use eXtreme Gradient Boosting (XGBoost)—a Machine Learning (ML) technique—to detect …
Spatial analysis of shared e-scooter trips
Shared e-scooters have become a common mode of transportation in many cities around
the world. E-sooters provide convenient and quick rides for short distances and can act as a …
the world. E-sooters provide convenient and quick rides for short distances and can act as a …
Classifying travelers' driving style using basic safety messages generated by connected vehicles: Application of unsupervised machine learning
Driving style can substantially impact mobility, safety, energy consumption, and vehicle
emissions. While a range of methods has been used in the past for driving style …
emissions. While a range of methods has been used in the past for driving style …
Safety evaluation of connected and automated vehicles in mixed traffic with conventional vehicles at intersections
Abstract Connected and Automated Vehicles (CAVs) can potentially improve the
performance of the transportation system by reducing human errors. This paper investigates …
performance of the transportation system by reducing human errors. This paper investigates …
A proactive crash risk prediction framework for lane-changing behavior incorporating individual driving styles
Y Zhang, Y Chen, X Gu, NN Sze, J Huang - Accident Analysis & Prevention, 2023 - Elsevier
Driving style may have an important effect on traffic safety. Proactive crash risk prediction for
lane-changing behaviors incorporating individual driving styles can help drivers make safe …
lane-changing behaviors incorporating individual driving styles can help drivers make safe …
Integration of automated vehicles in mixed traffic: Evaluating changes in performance of following human-driven vehicles
Abstract The introduction of Automated Vehicles (AVs) into the transportation network is
expected to improve system performance, but the impacts of AVs in mixed traffic streams …
expected to improve system performance, but the impacts of AVs in mixed traffic streams …
Traffic conflict prediction using connected vehicle data
Transportation safety studies have been mostly focused on using crash data that are rare
events. Alternatively, conflict estimation can be used to assess safety. This has been proven …
events. Alternatively, conflict estimation can be used to assess safety. This has been proven …
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 …