Forecasting of Road Accident in Kerala: A Case Study

Sunny, Christine Maria; Nithya, S; Sinshi, K S; Vinodini, M D Vidya; Lakshmi, K G Aiswaria; Anjana, S.; Manojkumar, T.K.

doi:10.1109/icdse.2018.8527825

Cited by 25 publications

(15 citation statements)

References 8 publications

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“…The results from the analysis predict that there will be an overall increase in the number of fatal crashes for the upcoming years by 4.5%. In a similar study conducted by Sunny et al [29] in Kerala, using Holt-Winters exponential smoothing, an increased number of crashes was predicted for the upcoming years in that region. Furthermore, other studies also [28] have forecasted and reported that there will be an overall increase in the number of road crashes in their respective study settings.…”

Section: Discussionmentioning

confidence: 68%

“…The results of the few studies conducted in India forecast an increase in the number of road crashes. For instance, Sunny et al [29] in Kerala predicted an increase in the number of crashes for the upcoming years. Other studies also [28] forecasted and reported that there will be an overall increase in the number of road crashes in their respective study setting.…”

Section: Literature Reviewmentioning

confidence: 99%

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An Exploration of Characteristics and Time Series Forecast of Fatal Road Crashes in Manipal, India

et al. 2022

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Road crashes are the sixth leading cause of death in India. There has been a fourfold increase in the number of road traffic crashes in India in the last four decades and an increase of 9.8 times in the fatalities associated with that exponential increase. Manipal is a coastal place with a population of approximately 50,000 inhabitants lying in between the western Mountain range and the Arabian sea. The study’s objective is to explore the characteristics of fatal road crashes in Manipal from 2008–2018 using the data pertaining to fatal crashes retrieved from the office of the superintendent of police. Furthermore, it aims to forecast crashes by time series analysis prediction. The results show that most of the fatal crashes are due to exceeding the lawful speed limit, followed by driving under the influence of alcohol and going ahead and overtaking. The time series analysis forecasted the number of fatal crashes until the year 2025 and predicted that there will be an increase in the number of fatal road crashes by 4.5%. The results also provide essential leads for initiating specific intervention programmes targeting the causes of fatal road crashes.

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Section: Discussionmentioning

confidence: 68%

Section: Literature Reviewmentioning

confidence: 99%

An Exploration of Characteristics and Time Series Forecast of Fatal Road Crashes in Manipal, India

et al. 2022

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“…However, the shortcoming of this metho is the inability to assess the quality of the forecast based on outdated forecasts and the frequent autocorrelation of the residuals [5]. Procházka et al [6,7] used a multiple seasonality model for forecasting; in contrast, Sunny et al [8] chose the Holt-Winters exponential smoothing method.…”

Section: Introductionmentioning

confidence: 99%

Forecasting the Number of Road Accidents in Poland Depending on the Day of the Week using Neural Networks

Gorzelańczyk

Tylicki

2023

LOGI – Scientific Journal on Transport and Logistics

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The number of road accidents in the world is decreasing year by year. This number has been affected by the pandemic in recent years but is still very high. Therefore, it is necessary to take all possible measures and steps to reduce this number. The objective of the article is to forecast the number of road accidents in Poland depending on the day of the week. For this purpose, the annual data on the number of road accidents in Poland broken down by days of the week were analyzed, and a forecast for the years 2022-2040 was prepared on the basis of the police statistics. The forecast was made using selected models of neural networks. The research results show that a decrease in in the number of road accidents can be expected. However, the obtained results could be affected by the selected number of random samples (training, testing and validation).

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“…Among the most popular of these are the time series methods [2,3], which have the disadvantages of not being able to assess the quality of the forecast based on outdated forecasts and frequent autocorrelation of the residual component [4]. In contrast, Procházka et al [5,6] used the multiple seasonality model for forecasting, and Sunny et al [7,8] used the Holt-Winters exponential smoothing method. The disadvantage of these methods is that exogenous variables cannot be introduced into the models [9][10][11].…”

Section: Introductionmentioning

confidence: 99%

The Use of Neural Networks to Forecast the Number of Road Accidents in Poland

Gorzelańczyk¹

2023

SJSUT.ST

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Every year, a large number of traffic accidents occur on Polish roads. However, the pandemic of recent years has reduced the number of these accidents, although the number is still very high. For this reason, all measures should be taken to reduce this number. This article aims to forecast the number of road accidents in Poland. Thus, using Statistica software, the annual data on the number of road accidents in Poland were analyzed. Based on actual past data, a forecast was made for the future, for the period 2022-2040. Forecasting the number of accidents in Poland was conducted using selected neural network models. The results show that a reduction in the number of traffic accidents is likely. The choice of the number of random samples (learning, testing and validation) affects the results obtained.

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Forecasting of Road Accident in Kerala: A Case Study

Cited by 25 publications

References 8 publications

An Exploration of Characteristics and Time Series Forecast of Fatal Road Crashes in Manipal, India

An Exploration of Characteristics and Time Series Forecast of Fatal Road Crashes in Manipal, India

Forecasting the Number of Road Accidents in Poland Depending on the Day of the Week using Neural Networks

The Use of Neural Networks to Forecast the Number of Road Accidents in Poland

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