Journal ArticleDOI
Defining and screening crash surrogate events using naturalistic driving data.
Kun-Feng Wu,Paul P. Jovanis +1 more
TLDR
This paper demonstrates that a multi-stage modeling framework can be used to search through naturalistic driving data, extracting statistically similar crashes and near crashes, and is ready for testing in other applications.About:
This article is published in Accident Analysis & Prevention.The article was published on 2013-12-01. It has received 75 citations till now. The article focuses on the topics: Crash & Poison control.read more
Citations
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Journal ArticleDOI
Simulation of safety: a review of the state of the art in road safety simulation modelling.
TL;DR: Assessing the state of the art in the use of computer models to simulate and assess the level of safety in existing and future traffic systems focuses on stochastic numerical models of traffic behaviour and how reliable these are in estimating levels of safety on the traffic network.
Journal ArticleDOI
A feature learning approach based on XGBoost for driving assessment and risk prediction
TL;DR: A framework of feature extraction and selection that integrates learning-based feature selection, unsupervised risk rating, and imbalanced data resampling is designed, to assess vehicle driving and predict risk levels.
Journal ArticleDOI
A tree-structured crash surrogate measure for freeways
Yan Kuang,Xiaobo Qu,Shuaian Wang +2 more
TL;DR: The results show that the proposed indicator outperforms the three traditional crash surrogate measures in representing rear-end crash risks and is applied to evaluate the crash risks in a freeway section of Pacific Motorway, Australia.
Journal ArticleDOI
Modeling traffic conflicts for use in road safety analysis: A review of analytic methods and future directions
TL;DR: It is found that although substantial progress has been made in the modeling methodologies of traffic conflicts over the years, more research efforts are needed.
Journal ArticleDOI
Drive Analysis Using Vehicle Dynamics and Vision-Based Lane Semantics
TL;DR: “drive analysis” is introduced as one of the first steps toward automating the process of extracting midlevel semantic information from raw sensor data and to extract a set of 23 semantics about lane positions, vehicle localization within lanes, vehicle speed, traffic density, and road curvature.
References
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Journal ArticleDOI
Measuring the accuracy of diagnostic systems
TL;DR: For diagnostic systems used to distinguish between two classes of events, analysis in terms of the "relative operating characteristic" of signal detection theory provides a precise and valid measure of diagnostic accuracy.
MonographDOI
Microeconometrics: Methods and Applications
TL;DR: This chapter discusses models for making pseudo-random draw, which combines asymptotic theory, Bayesian methods, and ML and NLS estimation with real-time data structures.
Book
The Statistical Evaluation of Medical Tests for Classification and Prediction
TL;DR: A comparison of Binary Tests and Regression Analysis and the Receiver Operating Characteristic Curve shows that Binary Tests are more accurate than Ordinal Tests when the Receiver operating characteristic curve is considered.
Journal ArticleDOI
Receiver Operating Characteristic Curves and Their Use in Radiology
TL;DR: Several summary measures of the accuracy of a test, including the commonly used percentage of correct diagnoses and area under the ROC curve, are described and compared.
Related Papers (5)
The statistical analysis of crash-frequency data: A review and assessment of methodological alternatives
Dominique Lord,Fred L. Mannering +1 more