scholarly journals Traffic Accidents Classification and Injury Severity Prediction

2020 ◽  
Vol 9 (6) ◽  
pp. 845-849
Keyword(s):  
Logistic Regression ◽  
Predictive Model ◽  
Road Safety ◽  
Traffic Accidents ◽  
Injury Severity ◽  
Severity Prediction ◽  
Accident Data ◽  
Life Threatening ◽  
Analyse Data ◽  
Logistic Regression Algorithm

Traffic accidents are one of the most life-threatening dangers to human being. Deaths and injuries due to traffic accidents have a great impact on society. Traffic accidents information and data provided by public can be useful to classify these accidents according to their type and severity, and consequently try to build predictive model. Detecting and identifying injury severity in traffic accidents in real time is primordial for speeding post-accidents protocols as well as developing general road safety policies. In this project we are using Logistic Regression algorithm to classify accident data. The data to be analysed is collected from various sources, is both structured and unstructured and has several attributes. In this project we are going to detect and analyse data together to generate decision trees that give insights on previous accidents.

scholarly journals ROAD SAFETY CAMPAIGNS TO REDUCE TRAFFIC ACCIDENTS FOR YOUNG ROAD USERS

ICCD ◽  
2019 ◽  
Vol 2 (1) ◽  
pp. 601-606
Author(s):  
Widodo Budi Dermawan ◽  
Dewi Nusraningrum
Keyword(s):  
School Environment ◽  
Road Safety ◽  
Traffic Accident ◽  
Traffic Accidents ◽  
Road Traffic ◽  
School Administrators ◽  
Road User ◽  
The Road ◽  
Road Users ◽  
Accident Data

Every year we lose many young road users in road traffic accidents. Based on traffic accident data issued by the Indonesian National Police in 2017, the number of casualties was highest in the age group 15-19, with 3,496 minor injuries, 400 seriously injured and 535 deaths. This condition is very alarming considering that student as the nation's next generation lose their future due to the accidents. This figure does not include other traffic violations, not having a driver license, not wearing a helmet, driving opposite the direction, those given ticket and verbal reprimand. To reduce traffic accident for young road user, road safety campaigns were organized in many schools in Jakarta. This activity aims to socialize the road safety program to increase road safety awareness among young road users/students including the dissemination of Law No. 22 of 2009 concerning Road Traffic and Transportation. Another purpose of this program is to accompany school administrators to set up a School Safe Zone (ZoSS), a location on particular roads in the school environment that are time-based speed zone to set the speed of the vehicle. The purpose of this paper is to promote the road safety campaigns strategies by considering various campaign tools.

scholarly journals Empirical Modelling for exploring the factors contributing to disability severity from road traffic accidents in Thailand

1970 ◽  
Vol 6 (2) ◽  
pp. 176-185
Author(s):  
Jaratsri Rungrattanaubol ◽  
Anamai Na-udom ◽  
Antony Harfield
Keyword(s):  
Neural Network ◽  
Data Mining ◽  
Traffic Accidents ◽  
Injury Severity ◽  
Road Traffic ◽  
Road Traffic Accidents ◽  
Empirical Modelling ◽  
Standard Data ◽  
Accident Data ◽  
Computer Based

This paper introduces a computer-based model for predicting the severity of injuries in road traffic accidents. Using accident data from surveys at hospitals in Thailand, standard data mining techniques were applied to train and test a multilayer perceptron neural network. The resulting neural network specification was loaded into an interactive environment called EDEN that enables further exploration of the computer-based model. Although the model can be used for the classification of accident data in terms of injury severity (in a similar way to other data mining tools), the EDEN tool enables deeper exploration of the underlying factors that might affect injury severity in road traffic accidents. The aim of this paper is to describe the development of the computer-based model and to demonstrate the potential of EDEN as an interactive tool for knowledge discovery.

scholarly journals Enabling Equal Opportunity in Logistic Regression Algorithm

2021 ◽  
Author(s):  
Sandro Radovanović ◽  
Marko Ivić
Keyword(s):  
Logistic Regression ◽  
Prediction Model ◽  
Predictive Model ◽  
Prediction Accuracy ◽  
Equal Opportunity ◽  
Census Data ◽  
Research Question ◽  
Classification Model ◽  
Disparate Impact ◽  
Logistic Regression Algorithm

Research Question: This paper aims at adjusting the logistic regression algorithm to mitigate unwanted discrimination shown towards race, gender, etc. Motivation: Decades of research in the field of algorithm design have been dedicated to making a better prediction model. Many algorithms are designed and improved, which made them better than the judgments of people and even experts. However, in recent years it has been discovered that predictive models can make unwanted discrimination. Such unwanted discrimination in the predictive model can lead to legal consequences. In order to mitigate the problem of unwanted discrimination, we propose equal opportunity between privileged and discriminated groups in the logistic regression algorithm. Idea: Our idea is to add a regularization term in the goal function of the logistic regression. Therefore, our predictive model will solve both the social problem and the predictive problem. More specifically, our model will provide fair and accurate predictions. Data: The data used in this research present U.S. census data describing individuals using personal characteristics with a goal to provide a binary classification model for predicting if an individual has an annual salary above $50k. The dataset used is known for disparate impact regarding female individuals. In addition, we used the COMPAS dataset aimed at predicting recidivism. COMPAS is biased toward African-Americans. Tools: We developed a novel regularization technique for equal opportunity in the logistic regression algorithm. The proposed regularization is compared against classical logistic regression and fairness constraint logistic regression, using a ten-fold cross-validation. Findings: The results suggest that equal opportunity logistic regression manages to create a fair prediction model. More specifically, our model improved both disparate impact and equal opportunity compared to classical logistic regression, with a minor loss in prediction accuracy. Compared to the disparate impact constrained logistic regression, our approach has higher prediction accuracy and equal opportunity, while having a lower disparate impact. By inspecting the coefficients of our approach and classical logistic regression, one can see that proxy attribute coefficients are reduced to very low values. Contribution: The main contribution of this paper is in the methodological part. More specifically, we implemented an equal opportunity in the logistic regression algorithm.

scholarly journals IMPROVEMENT OF LEGISLATION ESTABLISHING LIABILITY FOR VIOLATIONS OF THE PROCEDURE FOR PROVIDING PUBLIC SERVICES IN THE FIELD OF ROAD SAFETY

2021 ◽  
Vol 6(72) (3) ◽  
pp. 338-344
Author(s):  
A. N. Osyak
Keyword(s):  
Traffic Safety ◽  
Police Officers ◽  
Road Safety ◽  
Traffic Accidents ◽  
Public Services ◽  
Injury Severity ◽  
Road Traffic ◽  
Dangerous Goods ◽  
Transport Of Dangerous Goods ◽  
The Right

Study of the tasks and functions of police in the sphere of traffic safety is dedicated to many scientific researches due to the fact that the significance of the topic has not lost its relevance, the evidence of the disappointing official statistics about the dead and received various degrees of injury severity in traffic accidents and also due to the fact that the quantity of transport in Russia is constantly increasing, and the problems of transport security are not solved. At the same time, research related to the implementation by the police of the functions of providing public services in this area is of particular importance, because despite the fact that this area of police activity is not the main one, and is not provided with state-power enforcement, it nevertheless plays a significant role in ensuring public safety in the field of traffic. Indirectly, the police, through the function of providing public services, by issuing permits for the transport of dangerous goods, issuing permits for the right to drive, etc., minimizes and reduces the threat of harm to life and health, property, and citizens involved in road traffic. In the article, the author sets a task to investigate the legislation that establishes liability for violation of the procedure for providing public services in the field of road safety, to suggest ways to improve it. The author defines public services in the field of road safety and defines their essence. The author analyzes Federal and departmental legislation, identifies the features of bringing to justice police officers for improper provision of public services. The article draws conclusions about the existence of certain shortcomings in the legislation in this area and suggests ways to eliminate them.

A Study on Injury Severity Prediction for Car-to-Car Traffic Accidents

2020 ◽  
Vol 19 (4) ◽  
pp. 13-29
Author(s):  
Changwan Ko ◽  
◽  
Hyeonmin Kim ◽  
Young-Seon Jeong ◽  
Jaehee Kim
Keyword(s):  
Traffic Accidents ◽  
Injury Severity ◽  
Car Traffic ◽  
Severity Prediction

Analysis of Characteristics of Vehicle-Bicycle/Pedestrian Conflicts Using Video Drive Recorder

2011 ◽  
Vol 243-249 ◽  
pp. 4413-4417 ◽  
Author(s):  
Qing Feng Lin ◽  
Bo Cheng ◽  
Guang Quan Lu
Keyword(s):  
Field Test ◽  
Traffic Control ◽  
Road Safety ◽  
Traffic Accidents ◽  
Safety Management ◽  
The Road ◽  
Road Design ◽  
Traffic Conflict ◽  
Accident Data ◽  
One Year

Vehicle to pedestrian/bicycle accidents account for a large proportion of traffic accidents in China. In order to study the characteristics of vehicle to pedestrian/bicycle conflicts, 50 taxis are chosen as the test vehicles. A field-test was conducted using video driver recorder in Beijing for one year. A large amount of traffic conflict and accident data was collected in real driving environment. Considering the factors including conflict type, conflict time, conflict location, traffic control and conflict speed etc., the traffic conflict characteristics of vehicle to pedestrian/bicycle were analyzed. The results might contribute to the road safety management, road design and accident prevention technology.

scholarly journals Effective Search of Triterpenes with Anti-HSV-1 Activity Using a Classification Model by Logistic Regression

2021 ◽  
Vol 9 ◽  
Author(s):  
Keiko Ogawa ◽  
Seikou Nakamura ◽  
Haruka Oguri ◽  
Kaori Ryu ◽  
Taichi Yoneda ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Natural Products ◽  
Predictive Model ◽  
Binary Classification ◽  
External Validation ◽  
Area Under The Curve ◽  
Classification Model ◽  
Active Compounds ◽  
Logistic Regression Algorithm ◽  
Hsv 1

Natural products are an excellent source of skeletons for medicinal seeds. Triterpenes and saponins are representative natural products that exhibit anti-herpes simplex virus type 1 (HSV-1) activity. However, there has been a lack of comprehensive information on the anti-HSV-1 activity of triterpenes. Therefore, expanding information on the anti-HSV-1 activity of triterpenes and improving the efficiency of their exploration are urgently required. To improve the efficiency of the development of anti-HSV-1 active compounds, we constructed a predictive model for the anti-HSV-1 activity of triterpenes by using the information obtained from previous studies using machine learning methods. In this study, we constructed a binary classification model (i.e., active or inactive) using a logistic regression algorithm. As a result of the evaluation of predictive model, the accuracy for the test data is 0.79, and the area under the curve (AUC) is 0.86. Additionally, to enrich the information on the anti-HSV-1 activity of triterpenes, a plaque reduction assay was performed on 20 triterpenes. As a result, chikusetsusaponin IVa (11: IC50 = 13.06 μM) was found to have potent anti-HSV-1 with three potentially anti-HSV-1 active triterpenes. The assay result was further used for external validation of predictive model. The prediction of the test compounds in the activity test showed a high accuracy (0.83) and AUC (0.81). We also found that this predictive model was found to be able to successfully narrow down the active compounds. This study provides more information on the anti-HSV-1 activity of triterpenes. Moreover, the predictive model can improve the efficiency of the development of active triterpenes by integrating many previous studies to clarify potential relationships.

scholarly journals Statistical Overview of Factors Influencing Traffic Accidents Severity On El-Brega Coastal Freeway in Libya

2019 ◽  
Vol 13 (1) ◽  
pp. 154-161
Author(s):  
Buseif Omar Mohamed ◽  
Nur Izzi Yusoff ◽  
Muhammad Mubaraki ◽  
Sri Atmaja Rosyidi
Keyword(s):  
Road Safety ◽  
High Speed ◽  
Traffic Accidents ◽  
Injury Severity ◽  
Influence Factor ◽  
Road Traffic ◽  
Seat Belt ◽  
Descriptive Analysis ◽  
Binary Logistic Regression Model ◽  
Accident Injury

Background: Globally, Road Traffic Accidents (RTAs) are one of the significant causes of fatality and injury. In Libya, RTAs have resulted in disabilities and were the third leading cause of death. However, there is a lack of information on RTAs and road safety in Libya. Objective: The present study aims to fill the knowledge gap by performing a statistical analysis to identify the factors associated with road accident severity in El-Brega Coastal Freeway. Methods: RTAs data extracted from police investigation reports in Ajdabiya Municipality for the period from 2001 to 2010. Then descriptive analysis and Binary logistic regression model (BLM) are applied to analyzing the data. Results: Descriptive analysis results showed that between 2001 and 2010, approximately 45% of RTAs in Ajdabiya Municipality occurred on El-Brega Coastal Freeway, and more than 1225 individuals lost their lives or sustained injuries in these RTAs. Furthermore, Sixty-two percent (n = 137) of those who died in accidents were from the 20–45 age group. BLM Results concluded that only eight predictors have statistical significant with accident injury severity. Five of them increase the likelihood of injury severity. A head-on collision is the prime influence factor to increase injury severity odds, followed by high-speed driving, Weekends, horizontal curves, and driver’s age. While accident injury tends to be less severe with the other predictors like rollover collision, rear-end collision, and accidents involving animals. Conclusion: Thus, implementing the use of seat-belt and speed control regulations, with activating ambulance services are the urgent countermeasures to enhance road safety.

scholarly journals Influence Factors on Injury Severity of Traffic Accidents and Differences in Urban Functional Zones: The Empirical Analysis of Beijing

2018 ◽  
Vol 15 (12) ◽  
pp. 2722 ◽  
Author(s):  
Zhiyuan Sun ◽  
Jianyu Wang ◽  
Yanyan Chen ◽  
Huapu Lu
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Logistic Regression Analysis ◽  
Traffic Accidents ◽  
Injury Severity ◽  
Influence Factors ◽  
Binary Logistic Regression ◽  
Binary Logistic Regression Analysis ◽  
Functional Zones ◽  
The Impact

The objective of this study was to identify influence factors on injury severity of traffic accidents and discuss the differences in urban functional zones in Beijing. A total of 3982 sets of accident data in Beijing were analyzed from the perspective of whole city and different urban functional zones. From the aspects of accident attribute, occurrence time, infrastructure, management status, and environmental condition, the influence factors set of injury severity of traffic accidents in Beijing are set up in this paper, which include 17 influence factors. Based on Pearson’s chi-squared test, factors are preselected. On the basis of binary logistic regression analysis, the impact of the value of influence factors on injury severity of traffic accidents is calibrated. Based on classification and regression tree analysis, the impact of influence factors is analyzed. Through Pearson’s chi-squared test and binary logistic regression analysis, it is found that there are similarities and differences among different urban functional zones. There are two common influence factors, including accident type and cross-section position, and six personalized influence factors, including lighting conditions, visibility, signal control, road physical isolation facility, occurrence period and road type, and the other nine weak influence factors. The results of binary logistic regression analysis and classification and regression tree analysis are basically the same. The factors that should be paid attention to in different urban functional zones and the value of the factors that need special attention are determined by synthesizing two methods.

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