Injury severity on traffic crashes: A text mining with an interpretable machine-learning approach
The analysis of traffic crash severities provides significant information for the development of
safety countermeasures. Most available traffic crash datasets contain rich information …
safety countermeasures. Most available traffic crash datasets contain rich information …
Identifying secondary crashes using text mining techniques
Secondary crashes, roadway clearance time, and incident clearance time are three primary
performance measures for traffic incident management. Crash databases, which are the …
performance measures for traffic incident management. Crash databases, which are the …
Examining the potential of generative language models for aviation safety analysis: Case study and insights using the aviation safety reporting system (asrs)
This research investigates the potential application of generative language models,
especially ChatGPT, in aviation safety analysis as a means to enhance the efficiency of …
especially ChatGPT, in aviation safety analysis as a means to enhance the efficiency of …
[HTML][HTML] Using Bidirectional Encoder Representations from Transformers (BERT) to classify traffic crash severity types
Traffic crashes are a critical safety concern. Many studies have attempted to improve traffic
safety by performing a wide range of studies on safety topics with the application of diverse …
safety by performing a wide range of studies on safety topics with the application of diverse …
Discovering latent themes in traffic fatal crash narratives using text mining analytics and network topology
The proliferation of digital textual archives in the transportation safety domain makes it
imperative for the inventions of efficient ways of extracting information from the textual data …
imperative for the inventions of efficient ways of extracting information from the textual data …
Injury severity analysis of pedestrian and bicyclist trespassing crashes at non-crossings: A hybrid predictive text analytics and heterogeneity-based statistical modeling …
Non-motorists involved in rail-trespassing crashes are usually more vulnerable to receiving
major or fatal injuries. Previous research has used traditional quantitative crash data for …
major or fatal injuries. Previous research has used traditional quantitative crash data for …
Semantic N-gram feature analysis and machine learning–based classification of drivers' hazardous actions at signal-controlled intersections
Abstract In the United States, it is common for crash reports to include a narrative that
contains a police officer's written summary of the crash. The crash narratives provide …
contains a police officer's written summary of the crash. The crash narratives provide …
[HTML][HTML] Applying interpretable machine learning to classify tree and utility pole related crash injury types
In spite of enormous improvements in vehicle safety, roadway design, and operations, there
is still an excessive amount of traffic crashes resulting in injuries and major productivity …
is still an excessive amount of traffic crashes resulting in injuries and major productivity …
Machine learning approaches to analysing textual injury surveillance data: a systematic review
K Vallmuur - Accident Analysis & Prevention, 2015 - Elsevier
Objective To synthesise recent research on the use of machine learning approaches to
mining textual injury surveillance data. Design Systematic review. Data sources The …
mining textual injury surveillance data. Design Systematic review. Data sources The …
[HTML][HTML] Application of text mining techniques to identify actual wrong-way driving (wwd) crashes in police reports
Wrong-way driving (WWD) has been a long-lasting issue for transportation agencies and
law enforcement, since it causes pivotal threats to road users. Notwithstanding being rare …
law enforcement, since it causes pivotal threats to road users. Notwithstanding being rare …