scholarly journals Predicting Road Traffic Accident Severity using Decision Trees and Time-Series Calendar Heatmaps

2019 ◽  
Author(s):  
Charith Silva ◽  
Mo Saraee
Keyword(s):  
Time Series ◽  
Decision Trees ◽  
Road Traffic Accident ◽  
Traffic Accident ◽  
Road Traffic ◽  
Accident Severity

Application of Grey Model(1,1) in Road Traffic Accident Forecast

2011 ◽  
Vol 65 ◽  
pp. 551-556
Author(s):  
Xiao Kun Miao ◽  
Ming Yang Li
Keyword(s):  
Stochastic Process ◽  
Time Series ◽  
Road Traffic Accident ◽  
Traffic Accident ◽  
Road Traffic ◽  
Grey Model ◽  
Test Results ◽  
Matlab Software ◽  
The Future

Road traffic accident forecast is a complex stochastic process. Based on the statistics of road traffic accident, Grey Model (1, 1)( short for GM(1, 1)) was applied to forecast the future number of road traffic accident in this paper. GM(1, 1) was established according to the time-series. GM(1, 1) is usually applied for such stochastic unconfirmed problem as road traffic accident forecast. Base on MATLAB software, the forecast value of road traffic accident was given. The precision of the test results show that the model is accurate and the forecast results are reliable.

Suicides and road traffic deaths in Russia: A comparative analysis of trends

2017 ◽  
Vol 41 (S1) ◽  
pp. s891-s891
Author(s):  
Y. Razvodovsky
Keyword(s):  
Time Series ◽  
Road Traffic Accident ◽  
Traffic Accident ◽  
Motor Vehicle ◽  
Road Traffic ◽  
Motor Vehicle Crash ◽  
Actual Number ◽  
Aggregate Level ◽  
Confounding Variables ◽  
Competing Interest

IntroductionIt has long been recognized that there are difficulties in obtaining valid mortality rates for suicides. The evidence indicated that suicides are sometimes misclassified and “hidden” as accidental. Suicide by motor vehicle crash is a recognized phenomenon, leading to under-reporting of the actual number of suicides and inaccuracies in the suicides mortality statistics. Road traffic accident mortality and the suicides rates in Russia are both among the highest in the world. This phenomenon has attracted much attention in recent years, but remains poorly understood.AimsThe present study aims to test the hypothesis of the close aggregate level link between road traffic accident mortality and the suicides rates in Russia.MethodsTrends in sex-specific road traffic accident mortality and the suicides rates from 1956 to 2015 were analyzed employing a distributed lags analysis in order to assess bivariate relationship between the two time series.ResultsThe graphical evidence suggests that the trends in both road traffic accident mortality and the suicides for male and female seem to follow each other across the time series. The results of analysis indicate the presence of a statistically significant association between the two time series for male at lag zero. This association for female was also positive, but statistically non-significant.ConclusionsThis study indirectly supports the hypothesis that many of road traffic accident deaths in Russia are likely to have been suicides. Alternatively, common confounding variables, including binge drinking and psychosocial distress, may explain positive aggregate-level association between the two time series.Disclosure of interestThe author has not supplied his/her declaration of competing interest.

Road traffic accident severity analysis: A census-based study in China

2019 ◽  
Vol 70 ◽  
pp. 135-147 ◽  
Author(s):  
Deyu Wang ◽  
Qinyi Liu ◽  
Liang Ma ◽  
Yijing Zhang ◽  
Haozhe Cong
Keyword(s):  
Road Traffic Accident ◽  
Traffic Accident ◽  
Road Traffic ◽  
Accident Severity

scholarly journals A Time Series Model for Assessing the Trend and Forecasting the Road Traffic Accident Mortality

2016 ◽  
Vol 5 (3) ◽  
Author(s):  
Shahrokh Yousefzadeh-Chabok ◽  
Fatemeh Ranjbar-Taklimie ◽  
Reza Malekpouri ◽  
Alireza Razzaghi
Keyword(s):  
Time Series ◽  
Road Traffic Accident ◽  
Traffic Accident ◽  
Road Traffic ◽  
Time Series Model ◽  
The Road

scholarly journals Time series modeling of road traffic accidents in Amhara Region

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Kidane Alemtsega Getahun
Keyword(s):  
Time Series ◽  
Road Traffic Accident ◽  
Traffic Accident ◽  
Traffic Accidents ◽  
Time Series Data ◽  
Road Traffic ◽  
Series Data ◽  
Close Monitoring ◽  
Road Traffic Accidents ◽  
Amhara Region

AbstractRoad traffic accidents (RTA) are commonly encountered incidents that can cause injuries, death, and property damage to members of society. Ethiopia is one of the highest incident rates of road traffic accidents. Report of Transport and Communication from 2012 to 2014, shows an increment in the number of traffic accidents in Ethiopia. Amhara region accounted for 27.3% of the total road traffic accident-related deaths in Ethiopia during the year 2008/9, which is the highest share among all regions in Ethiopia. The current research aims to model the trend of injury, fatal and total road traffic accidents in the Amhara region from September 2013 to May 2017. Monthly reported traffic accidents were obtained from the traffic department of the Amhara region police commission. The most universal class of models for forecasting time series data called Auto-regressive Integrated Moving Averages (ARIMA) models were applied to model the trends and patterns of road traffic accident cases in the Amhara region. The average number of observed injury RTA, fatal RTA, and total RTA were 27.2, 14, and 78.2 per month respectively. It was observed that a relatively large number of RTA’s are reported on Tuesday, Thursday, and Saturday relative to other days of the week. The data also reveals that more than 60% of accidents involve drivers between the ages of 18–30 years. ARIMA (2,0,0) (1,0,0) ARIMA (2,0,0) and ARIMA (2,0,0) (1,1,0) were fitted as the best model for total injury accidents, fatal RTA and total RTA data respectively. A 48 months forecast was made based on the fitted models and it can be concluded that road traffic accident cases would continue at the non-decreasing rate in the Amhara region for the predicted periods. Therefore, the findings of this study draw attention to the importance of implementing improved better policies and close monitoring of road trafficking to change the existing non-decreasing trend of road traffic accidents in the region.

Sign in / Sign up

Export Citation Format

Share Document