Data clustering: application and trends
Clustering has primarily been used as an analytical technique to group unlabeled data for
extracting meaningful information. The fact that no clustering algorithm can solve all …
extracting meaningful information. The fact that no clustering algorithm can solve all …
Traffic volume and crashes and how crash and road characteristics affect their relationship–A meta-analysis
AK Høye, IS Hesjevoll - Accident Analysis & Prevention, 2020 - Elsevier
The present study has investigated the relationship between traffic volume and crash
numbers by means of meta-analysis, based on 521 crash prediction models from 118 …
numbers by means of meta-analysis, based on 521 crash prediction models from 118 …
Predicting crash frequency for multi-vehicle collision types using multivariate Poisson-lognormal spatial model: A comparative analysis
According to crash configuration and pre-crash conditions, traffic crashes are classified into
different collision types. Based on the literature, multi-vehicle crashes, such as head-on, rear …
different collision types. Based on the literature, multi-vehicle crashes, such as head-on, rear …
[HTML][HTML] Urban Traffic Accident Features Investigation to Improve Urban Transportation Infrastructure Sustainability by Integrating GIS and Data Mining Techniques
Urban traffic accidents pose significant challenges to the sustainability of transportation
infrastructure not only in Vietnam but also all over the world. To decrease the frequency of …
infrastructure not only in Vietnam but also all over the world. To decrease the frequency of …
Influence of segmentation approaches on the before-after evaluation of engineering treatments: A hypothetical treatment approach
The segmentation of highways is a fundamental step in estimating crash frequency models
and conducting a before-after evaluation of engineering treatments, but the effects of …
and conducting a before-after evaluation of engineering treatments, but the effects of …
Clustering algorithms to analyze the road traffic crashes
Selecting an appropriate clustering method as well as an optimal number of clusters in road
accident data is at times confusing and difficult. This paper analyzes shortcomings of …
accident data is at times confusing and difficult. This paper analyzes shortcomings of …
Effects of globally obtained informative priors on Bayesian safety performance functions developed for Australian crash data
The precision and bias of Safety Performance Functions (SPFs) heavily rely on the data
upon which they are estimated. When local (spatially and temporally representative) data …
upon which they are estimated. When local (spatially and temporally representative) data …
Develo** local safety performance functions versus calculating calibration factors for SafetyAnalyst applications: A Florida case study
Safety performance functions (SPFs) are a required input to the newly released
SafetyAnalyst software tool. Although SafetyAnalyst provides default SPFs that were …
SafetyAnalyst software tool. Although SafetyAnalyst provides default SPFs that were …
Heterogeneity in crash patterns of autonomous vehicles: The latent class analysis coupled with multinomial logit model
Understanding the heterogeneity in autonomous vehicle (AV) crash patterns is crucial for
enhancing the safety and public acceptance of autonomous transportation systems. In this …
enhancing the safety and public acceptance of autonomous transportation systems. In this …
Hybrid segmentation approach to identify crash susceptible locations in large road networks
To perform crash analysis on large road networks, the network has to be segmented into
smaller units. Existing approaches split road networks into road segments such that they …
smaller units. Existing approaches split road networks into road segments such that they …