scholarly journals Exploring Determinants of Urban Motorcycle Accident Severity: The Case of Barcelona

2009 ◽  
Author(s):  
Daniel Albalate ◽  
Laura Fernández-Villadangos
Keyword(s):  
Motorcycle Accident ◽  
Accident Severity

Black-Spot Identification Using Accident Severity Approach for Cyberabad Region of Hyderabad City - A Case Study

2015 ◽  
Vol 5 (4) ◽  
pp. 36-42
Author(s):  
Sharath Goud ◽  
◽  
M. Kumar ◽  
A. Ramesh ◽  
◽  
...  
Keyword(s):  
Black Spot ◽  
Accident Severity

Machine learning based accident prediction in secure IoT enable transportation system

2021 ◽  
pp. 1-13 ◽  
Author(s):  
Bhabendu Kumar Mohanta ◽  
Debasish Jena ◽  
Niva Mohapatra ◽  
Somula Ramasubbareddy ◽  
Bharat S. Rawal
Keyword(s):  
Machine Learning ◽  
Smart City ◽  
Information Exchange ◽  
Secure Communication ◽  
Intelligent Transportation System ◽  
Transportation System ◽  
Information And Communications Technology ◽  
Classification Models ◽  
Architecture Model ◽  
Accident Severity

Smart city has come a long way since the development of emerging technology like Information and communications technology (ICT), Internet of Things (IoT), Machine Learning (ML), Block chain and Artificial Intelligence. The Intelligent Transportation System (ITS) is an important application in a rapidly growing smart city. Prediction of the automotive accident severity plays a very crucial role in the smart transportation system. The main motive behind this research is to determine the specific features which could affect vehicle accident severity. In this paper, some of the classification models, specifically Logistic Regression, Artificial Neural network, Decision Tree, K-Nearest Neighbors, and Random Forest have been implemented for predicting the accident severity. All the models have been verified, and the experimental results prove that these classification models have attained considerable accuracy. The paper also explained a secure communication architecture model for secure information exchange among all the components associated with the ITS. Finally paper implemented web base Message alert system which will be used for alert the users through smart IoT devices.

scholarly journals Weight Feedback-Based Harmonic MDG-Ensemble Model for Prediction of Traffic Accident Severity

2021 ◽  
Vol 11 (11) ◽  
pp. 5072
Author(s):  
Byung-Kook Koo ◽  
Ji-Won Baek ◽  
Kyung-Yong Chung
Keyword(s):  
Traffic Accidents ◽  
Average Rate ◽  
Modern Society ◽  
Rate Of Change ◽  
Weighted Voting ◽  
Independent Variables ◽  
Dependent Variables ◽  
Accident Severity ◽  
Harmonic Average ◽  
Bagging Method

Traffic accidents are emerging as a serious social problem in modern society but if the severity of an accident is quickly grasped, countermeasures can be organized efficiently. To solve this problem, the method proposed in this paper derives the MDG (Mean Decrease Gini) coefficient between variables to assess the severity of traffic accidents. Single models are designed to use coefficient, independent variables to determine and predict accident severity. The generated single models are fused using a weighted-voting-based bagging method ensemble to consider various characteristics and avoid overfitting. The variables used for predicting accidents are classified as dependent or independent and the variables that affect the severity of traffic accidents are predicted using the characteristics of causal relationships. Independent variables are classified as categorical and numerical variables. For this reason, a problem arises when the variation among dependent variables is imbalanced. Therefore, a harmonic average is applied to the weights to maintain the variables’ balance and determine the average rate of change. Through this, it is possible to establish objective criteria for determining the severity of traffic accidents, thereby improving reliability.

Client-Centered Emergency Care

1981 ◽  
Vol 2 (6) ◽  
pp. 1-4
Author(s):  
Jennifer MacPherson
Keyword(s):  
Emergency Room ◽  
Head Trauma ◽  
Emergency Care ◽  
Severe Head Trauma ◽  
Best Interest ◽  
Motorcycle Accident ◽  
Florence Nightingale ◽  
Centered Care ◽  
Patient Emergency

Since Florence Nightingale, nurses have agreed that care should be individualized for each patient. Emergency care is no different and texts on this subject instruct the nurse to involve the client in his own care and to recognize that being an emergency victim is physically and psychologically difficult for the client. But just what is client-centered emergency care and are clients getting it?A client is brought to the emergency room, unconscious, with severe head trauma resulting from a motorcycle accident. In this instance client-centered care consists of the nurse reacting swiftly and probably unemotionally. It is not in the client's best interest at this time for the nurse to try to ascertain that person's values and life views. Here client-centered care is compatible with the values and views of both the nurse and the institution.

Identifying the Factors Affecting the Probability of Accident Severity in Community Road - Focusing on Seoul City

2014 ◽  
Vol 641-642 ◽  
pp. 860-865
Author(s):  
You Jin Lim ◽  
Hak Ryong Moon ◽  
Won Pyoung Kang
Keyword(s):  
Logistic Regression ◽  
Binary Logistic Regression ◽  
Regression Technique ◽  
Road Accidents ◽  
Factors Affecting ◽  
Accident Severity

Since a variety of factors are associated with crash occurrence, the analysis of causes of crash is a hard task for traffic researchers and engineers. This study was attempted to identify factors affecting severity of the community road accidents. In particular, our analyses were focused on the community road accidents. A binary logistic regression technique was adopted for the analyses. The results showed that pedestrians of 65 years or older, cloudy, fence (sidewalk/driveway barrier), drivers of 24 years or younger, left/right turning, female pedestrian, non-business vehicle were dominant factors for the severity.

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