Computational intelligence and neuroscience
Nov 6, 2021
Recognizing vehicle plate numbers is a key step towards implementing the legislation on traffic and reducing the number of daily traffic accidents. Although machine learning has advanced considerably, the recognition of license plates remains an obst...
International journal of environmental research and public health
Nov 3, 2021
In many related works, nominal classification algorithms ignore the order between injury severity levels and make sub-optimal predictions. Existing ordinal classification methods suffer rank inconsistency and rank non-monotonicity. The aim of this pa...
OBJECTIVE: The aim of this study is to identify the effects of pedestrian physique differences on head injury prediction in car-to-pedestrian accidents via deep learning.
International journal of environmental research and public health
Oct 8, 2021
BACKGROUND: Alcohol-related road-traffic injury is the leading cause of premature death in middle- and lower-income countries, including Thailand. Applying machine-learning algorithms can improve the effectiveness of driver-impairment screening strat...
In road safety, real-time crash prediction may play a crucial role in preventing such traffic events. However, much of the research in this line generally uses data aggregated every five or ten minutes. This article proposes a new image-inspired data...
Computational intelligence and neuroscience
Sep 29, 2021
Road surface defects are crucial problems for safe and smooth traffic flow. Due to climate changes, low quality of construction material, large flow of traffic, and heavy vehicles, road surface anomalies are increasing rapidly. Detection and repairin...
The detection of obstacles at rail level crossings (RLC) is an important task for ensuring the safety of train traffic. Traffic control systems require reliable sensors for determining the state of anRLC. Fusion of information from a number of sensor...
It is well known that pedestrians are vulnerable road users. Their risk of being injured or killed in road traffic crashes is even higher as vehicle drivers often violate traffic rules and do not slow down or yield in front of crosswalks. In order to...
An innovative approach for real-time road safety analysis is presented in this work. Unlike traditional real-time crash prediction models (RTCPMs), in which crash data are used in the training phase, a real-time conflict prediction model (RTConfPM) i...
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