[HTML][HTML] Machine learning applied to road safety modeling: A systematic literature review
Road safety modeling is a valuable strategy for promoting safe mobility, enabling the
development of crash prediction models (CPM) and the investigation of factors contributing …
development of crash prediction models (CPM) and the investigation of factors contributing …
[HTML][HTML] Road crash prediction models: different statistical modeling approaches
A Abdulhafedh - Journal of transportation technologies, 2017 - scirp.org
Road crash prediction models are very useful tools in highway safety, given their potential
for determining both the crash frequency occurrence and the degree severity of crashes …
for determining both the crash frequency occurrence and the degree severity of crashes …
Evaluation of contributing factors affecting number of vehicles involved in crashes using machine learning techniques in rural roads of Cosenza, Italy
G Guido, S Shaffiee Haghshenas… - Safety, 2022 - mdpi.com
The evaluation of road safety is a critical issue having to be conducted for successful safety
management in road transport systems, whereas safety management is considered in road …
management in road transport systems, whereas safety management is considered in road …
[HTML][HTML] The usefulness of artificial intelligence for safety assessment of different transport modes
DI Tselentis, E Papadimitriou, P van Gelder - Accident Analysis & …, 2023 - Elsevier
Recent research in transport safety focuses on the processing of large amounts of available
data by means of intelligent systems, in order to decrease the number of accidents for …
data by means of intelligent systems, in order to decrease the number of accidents for …
Use of accident prediction models in road safety management–an international inquiry
Abstract Evaluation of road safety measures appears to be the weakest component of road
safety management systems in Europe. To improve Road Infrastructure Safety Management …
safety management systems in Europe. To improve Road Infrastructure Safety Management …
Predicting road crash severity using classifier models and crash hotspots
The rapid increase in traffic volume on urban roads, over time, has altered the global traffic
scenario. Additionally, it has increased the number of road crashes, some of which are …
scenario. Additionally, it has increased the number of road crashes, some of which are …
Utilizing support vector machine in real-time crash risk evaluation
R Yu, M Abdel-Aty - Accident Analysis & Prevention, 2013 - Elsevier
Real-time crash risk evaluation models will likely play a key role in Active Traffic
Management (ATM). Models have been developed to predict crash occurrence in order to …
Management (ATM). Models have been developed to predict crash occurrence in order to …
Applications of machine learning methods in traffic crash severity modelling: current status and future directions
As a key area of traffic safety research, crash severity modelling has attracted tremendous
attention. Recently, there has been growing interest in applying machine learning (ML) …
attention. Recently, there has been growing interest in applying machine learning (ML) …
[HTML][HTML] Assessment of the level of road crash severity: comparison of intelligence studies
In measuring road safety, accident severity is a key concern. Crash severity prediction
models inform researchers about the severity of a crash based on a variety of criteria. To …
models inform researchers about the severity of a crash based on a variety of criteria. To …
A review of models relevant to road safety
BP Hughes, S Newstead, A Anund, CC Shu… - Accident Analysis & …, 2015 - Elsevier
It is estimated that more than 1.2 million people die worldwide as a result of road traffic
crashes and some 50 million are injured per annum. At present some Western countries' …
crashes and some 50 million are injured per annum. At present some Western countries' …