AIMC Topic: Accidents, Traffic
Clear Filters Showing 111 to 120 of 284 articles
How Do Autonomous Vehicles Decide?
Sensors (Basel, Switzerland)
Dec 28, 2022
The advancement in sensor technologies, mobile network technologies, and artificial intelligence has pushed the boundaries of different verticals, e.g., eHealth and autonomous driving. Statistics show that more than one million people are killed in t...
Unusual Driver Behavior Detection in Videos Using Deep Learning Models.
Sensors (Basel, Switzerland)
Dec 28, 2022
Anomalous driving behavior detection is becoming more popular since it is vital in ensuring the safety of drivers and passengers in vehicles. Road accidents happen for various reasons, including health, mental stress, and fatigue. It is critical to m...
Multimodal Warnings Design for In-Vehicle Robots under Driving Safety Scenarios.
Sensors (Basel, Switzerland)
Dec 23, 2022
In case of dangerous driving, the in-vehicle robot can provide multimodal warnings to help the driver correct the wrong operation, so the impact of the warning signal itself on driving safety needs to be reduced. This study investigates the design of...
Predicting intersection crash frequency using connected vehicle data: A framework for geographical random forest.
Accident; analysis and prevention
Nov 4, 2022
Accurate crash frequency prediction is critical for proactive safety management. The emerging connected vehicles technology provides us with a wealth of vehicular motion data, which enables a better connection between crash frequency and driving beha...
Identification and Improvement of Hazard Scenarios in Non-Motorized Transportation Using Multiple Deep Learning and Street View Images.
International journal of environmental research and public health
Oct 28, 2022
In the prioritized vehicle traffic environment, motorized transportation has been obtaining more spatial and economic resources, posing potential threats to the travel quality and life safety of non-motorized transportation participants. It is becomi...
Vehicle Driving Risk Prediction Model by Reverse Artificial Intelligence Neural Network.
Computational intelligence and neuroscience
Oct 7, 2022
The popularity of private cars has brought great convenience to citizens' travel. However, the number of private cars in society is increasing yearly, and the traffic pressure on the road is also increasing. The number of traffic accidents is increas...
Multi-Section Traffic Flow Prediction Based on MLR-LSTM Neural Network.
Sensors (Basel, Switzerland)
Oct 4, 2022
As the aggravation of road congestion leads to frequent traffic crashes, it is necessary to relieve traffic pressure through traffic flow prediction. As well, the traffic flow of the target road section to be predicted is also closely related to the ...
Real-time driving risk assessment using deep learning with XGBoost.
Accident; analysis and prevention
Sep 30, 2022
Traffic crashes typically occur in a few seconds and real-time prediction can significantly benefit traffic safety management and the development of safety countermeasures. This paper presents a novel deep learning model for crash identification base...
The driver's instantaneous situation awareness when the alarm rings during the take-over of vehicle control in automated driving.
Traffic injury prevention
Sep 28, 2022
OBJECTIVE: The driver's instantaneous situation awareness in the process of take-over of vehicle control in automated driving has not yet been thoroughly investigated. The proposed research can provide a better understanding of the driver's perceived...
Prediction of Duration of Traffic Incidents by Hybrid Deep Learning Based on Multi-Source Incomplete Data.
International journal of environmental research and public health
Sep 1, 2022
Traffic accidents causing nonrecurrent congestion and road traffic injuries seriously affect public safety. It is helpful for traffic operation and management to predict the duration of traffic incidents. Most of the previous studies have been in a c...
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