[HTML][HTML] Enhancing road safety with machine learning: Current advances and future directions in accident prediction using non-visual data
Road traffic accident (RTA) poses a significant road safety issue due to the increased
fatalities worldwide. To address it, various artificial intelligence solutions are developed to …
fatalities worldwide. To address it, various artificial intelligence solutions are developed to …
[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 …
Factors propelling fatalities during road crashes: A detailed investigation and modelling of historical crash data with field studies
M Mohanty, R Panda, SR Gandupalli, RR Arya… - Heliyon, 2022 - cell.com
One of the major concerns in developing countries like India is to maintain traffic safety
under mixed and heterogenous scenario. Although zero accidents is the need of the hour …
under mixed and heterogenous scenario. Although zero accidents is the need of the hour …
Recent Advances in Traffic Accident Analysis and Prediction: A Comprehensive Review of Machine Learning Techniques
Traffic accidents pose a severe global public health issue, leading to 1.19 million fatalities
annually, with the greatest impact on individuals aged 5 to 29 years old. This paper …
annually, with the greatest impact on individuals aged 5 to 29 years old. This paper …
Analysis and modelling of crash severity of vulnerable road users through discrete methods: a case study approach
SR Gandupalli, P Kokkeragadda… - Innovative Infrastructure …, 2023 - Springer
Road traffic injuries rank as the eighth most prevalent cause of mortality among individuals
of various age groups while specifically representing the primary cause of death for …
of various age groups while specifically representing the primary cause of death for …
Real-Time Freeway Crash Detection Framework using Connected Vehicle Waypoint Data
R Kandiboina, V Ravichandra-Mouli… - Transportation …, 2024 - journals.sagepub.com
Accurate and timely detection of traffic accidents is crucial for transportation agencies
seeking swift responses and effective traffic management, particularly on freeways where …
seeking swift responses and effective traffic management, particularly on freeways where …
[PDF][PDF] Developing pedestrian fatality prediction models using historical crash data: application of binary logistic regression and boosted tree mechanism
Pedestrian fatality rate plays a key role in examining effectiveness of the road safety. The
present study attempts to examine the effect of various categories of accused vehicles and …
present study attempts to examine the effect of various categories of accused vehicles and …
Traffic crash severity: comparing the predictive performance of popular statistical and machine learning models using the Glasgow Coma Scale
Crash severity analysis and prediction is a promising field in traffic safety. Various statistical
methods have been used to model the severity of road crashes. However, machine learning …
methods have been used to model the severity of road crashes. However, machine learning …
Modeling road traffic fatalities in Iran's six most populous provinces, 2015–2016
F Jahanjoo, H Sadeghi-Bazargani… - BMC public health, 2022 - Springer
Background Prevention of road traffic injuries (RTIs) as a critical public health issue requires
coordinated efforts. We aimed to model influential factors related to traffic safety. Methods In …
coordinated efforts. We aimed to model influential factors related to traffic safety. Methods In …
R-TAP: A Cloud-Based Multi-Region Road Traffic Accident Severity Prediction Model
The tremendous impact of road traffic accidents (RTAs) remains a global concern, especially
in low-and middle-income countries (LMICs). While most LMICs have limited budget to …
in low-and middle-income countries (LMICs). While most LMICs have limited budget to …