Analysis of Road Accidents

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Abstract – Road accidents is a matter of serious concern in India. There is tremendous increase in number of road accidents with increase in vehicular population. Road traffic accidents injuries are one of leading cause of death, disabilities and hospitalization in the country imposing huge socio-economic costs. Accurate data of road accidents is required to control and suggest safety measures on road traffic accidents. Without accurate data and deep understanding of crash risks the problem of road accidents cannot be solved. This paper aims to study research work done on literature of road accident analysis and to study the scenario of road accidents in Himachal Pradesh.

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Keywords – vehicular population, road accidents, safety measures, socio-economic

I. INTRODUCTION

India has the highest number of road deaths across the globe. One in every 10 deaths is reported from India (times of India). Road accidents in India report 2016, reflecting information that total number of registered motor vehicle in country grew at a rate of compound annual growth rate (CAGR) 9.8 percent between 2005 to 2015, while total number of length of road accident increased compound annual growth rate (CAGR) 3.7 percent over period 2005 to 2015, implying a worsening vehicular congestion on road. Most of the roads are heavily encroached by parked vehicles. This results in restricting traffic flow. Accident severity in India in 2016 is 31.4 whereas in Himachal it is noted to be 40.1 in 2016.

Table 1
Road accidents in India

Year Total Accidents Number of Vehicles Registered (in thousands) Fatal Accidents Number of persons killed Number of persons injured Accident severity
2010 4,99,628 1,27,746 1,19,558 1,34,513 5,27,512 26.9
2011 4,97,686 1,41,866 1,21,618 1,42,485 5,11,394 28.6
2012 4,90,383 1,59,491 1,23,093 1,38,258 5,09,667 28.2
2013 4,86,476 1,81,508 1,22,589 1,37,572 4,94,893 28.3
2014 4,89,400 1,90,704 1,25,828 1,39,671 4,93,474 28.5
2015 5,01,423 2,10,023 1,31,726 1,46,133 5,00,279 29.1
2016 4,80,652 2,30,031 1,36,071 1,50,785 4,94,624 31.4

Source – Road accidents in India 2016 ( Government of India and Ministry of Road Transport and Highway)
Accident Severity: number of peoples killed per 100 accidents

Table 2
Road accidents in Himachal Pradesh

 

Year Total Accidents Fatal Accidents Number of persons killed Number of persons injured Accident severity
2013 2981 736 1054 5081 35.4
2014 3058 831 1199 5576 39.2
2015 3010 843 1096 5108 36.4
2016 3168 1000 1271 5764 40.1

Source – Road accidents in India 2016 ( Government of India and Ministry of Road Transport and Highway)

II. LITERATURE REVIEW

A. FSHATSYON BRHANE GEBRETENSAY, JAYESH JUREMALANI “A Road traffic accident analysis and prediction model: A case study of Vadodara city”, dept. of Civil engineering, Parul University, Gujarat, India.

This paper aims to perform a micro level analysis of road traffic accident data of last seven years (2010 to 2016) and to develop an accidental model in Vadodara city. Data is collected from nearest police station and a detailed analysis is done on basis like hour, year, location, type of collision, type of road accident, weather condition, vehicle wise distribution, vehicle ownership. On above analysis an accident prediction model is develop between (a) vehicle-population ratio and number of accidents (b) vehicular composition and total number of accidents using Regression analysis. Model is validated using Chi Square test.
Study concluded:

During last seven years number of killed peoples of city is increasing year to year with increase in population.
Most number of accidents occur in month of May and between Time 10:00 to 11:00 am.
Highest cause of accident is fault of driver and two-wheeler (32%) type of vehicle in the city.

B. SANJAY KUMAR SINGH, ASHISH MISHRA “Road accident analysis: A case study of Patna city.” Department of humanities and social sciences IIT Kanpur, Uttar Pradesh, India

In this paper road accident analysis of Patna city is done from year 1996-2000. It provides an overview of road accident scenario in India and also deals with existing transport system in India. Data was collected from police station and Deaths and Suicide in India 1996, 1997, 1998 published by National Crime Record Bureau. It conveyed a detail analysis on rate of road accident deaths, fatality rate, type of accidents, category of fatality, age wise distribution, vehicle responsible, percentage of accidents during day and night, location, black pots in Patna. Vehicular population has increased from 219906 to 294164 from 1996 to 2001 in Patna. He conclude that public transport system i.e. Rail and bus plays a negligible role in urban transport system in Patna. Due to this vehicle population is increasing.

Study concluded:
According to vehicle-vise accident rates, buses are most risky.
From year 2000 onwards, new road bypass (NH-38) is most accident prone location in city. (Contributed 15% of total)
31 to 45 years people are more responsible for accidents.

C. MIAOMIAO LIU, YONGSHENG CHEN, GUANGQUAN LU “The Analysis of serious fatal road traffic accidents in China”, Research institute of Highway, Ministry of Transport, 8 Xitucheng road, Haidian district, Beijing 100088
In this paper analysis of Serious Fatal Road Traffic Accident data of year 2004 to 2014 is done using Statistics Software SPSS. Regression analysis between number of serious fatal road traffic accidents (SF-RTA) and various factors including human, vehicle, road, society was done. Decision tree analysis is also performed. Data is collected from Road Accident Statistics Annual Report of People’s Republic of China. Analysis is performed on basis of regional distribution (Eastern, Middle, Western), provinces, hour, week, month, vehicle distribution, type of road, accident type

Study concluded:
From Regression analysis it is concluded that S1, H1 and R4 (denoted gross domestic product, total population and substandard highway mileage) has larger impact on number of SF-RTA than other factors.
Decision tree Analysis also concluded that R4 and H1 are main factors affecting SF-RTA. Results were found similar to Regression analysis.
SF-RTA occurred in western region the most. Timing were found to be 6 to 8 and 12 to 16. Accidents occur on Saturdays are most.

D. MUKUL NAMA, MR. NANDESHWAR LATA, DR. BHARAT NAGAR “A statistical data analysis of road traffic accidents in Jaipur city.” Civil Engg. Department, Jagannath University, Chaksu, Jaipur, India
Objective of this study is to analyze the traffic data of Jaipur, to identify the black spots and to suggest safety measure to minimize road accidents. Collected the data from three police stations. Collected road width data and traffic volume in PCU/hour manually of three locations. After analyzing the data road intersection with maximum frequency of accident is identified and found that number of road accidents in Nri circle (77 to 143), Trivani Tiraha (64 to 118), B2 Bye Pass (180 to 224) has increased from year 2006 to 2015.

Study concluded:
Designed a signal for NRI Circle.
In B2 Bye Pass most accidents occur at night. Reason behind the accidents is that road to Mansarovar is having the divider but there is no obstruction so the glazing of vehicle head light is falling on opposite side. For decreasing accidents he suggested proper arrangement in dividents and provocations of cameras and a speed breaker.
In Trivani Tiraha he designed a signal.

E. RAHUL BADGUJAR, PRIYAM MISHRA, MAYANK CHANDRA, SAYALI SANDBHOR, HUMERA KHANUM “Accident data analysis using statistical methods- case study of Indian highway” Department of civil engg, Symbiosis Institute of Technology, Pune, India
The aim of this study is to study various factors causing road accidents and to use regression technique to predict the occurrence of accidents for certain situation. Data of road accidents for a stretch of 101 kms of NH-9 was collected for past 3 years. From regression analysis an equation was obtained:
y = (-0.00357×1 + 0.016035×2 – 0.01715×3 + 0.009262×4) + 2.460883
y = classification of accident, x1 = road feature, x2 = road condition, x3 = intersection type and control, x4 = weather condition
For validation of regression analysis predicted values from regression analysis were compared with available accident data and found that prediction model for classification of accident predicts 66% values.

Study Concluded:
Analysis based on accident location predicts 180- 189 km on right lane and 240-249 km on left lane have highest no. of accidents on study stretch. Safety provisions must be done for these locations.
Analysis based on time predicts 18:00-20:50 hrs have highest no. of accidents on study stretch. Lighting provisions must be improved.

F. VELURU SAILAJA, DR. S. SIDDI RAJU, “Accident Analysis on NH-18 by using Regression Model and its preventive measures.” Deptt of civil engineering, Siddharth institute of Engineering and Technology, Puttur, A.P 517583, India
This paper discusses the influence of various factors on accident caution based on statistical package regression analysis collected from the most accident prone stretch, Ayalurmetta to Thammarajupalli (30km) in Andhra Pradesh on NH18. Accident data of 5 years (2008-2012) was collected from near police stations. The data was analyzed using SPSS software.

Study Concluded:
Trucks are responsible for most accidents (27%).
Most accidents took place between 9 to 10 and 16 to 17.
From data stimulation, it was found that Road Markings, Conditions, Traffic Volume, Median Opening and Carriageway condition were main parameters for causing accidents.
Suggestions to reduce road accidents like, penalties of fine, check on drivers by police, maximum hour of work for drivers, rules for cyclist, motor cycle riders, uniform road signs was given.

G. MANU.N.NAIR, DR.V. THANGAMANI, “An Analysis of Spatially explicit Scenario of Road Traffic Accidents in Kerala Using GIS.” School of Earth and Atmospheric sciences, Madurai Kamaraj University, Madurai, Tamil Nadu, India
The aim of the study is to examine the temporal variation in the patterns of road traffic accidents, to identify the factors leading to road accidents and to formulate suggestions to avoid road traffic accidents. Road accident details were taken from Kerala police (2001-2014), and number of vehicles registered are taken from Motor Vehicle department Kerala and NATPAC. Details were analyzed using GIS.

Study Concluded:
In 2007 and 2010 the most number of accidents are recorded in Ernakulum followed by Thiruvananthapuram the capital city. Also the number of accidents has reduced from 2007 to 2010 to 3.09%.
Most of accidents are due to carelessness of drivers or the pedestrians.
Accidents are decreasing from year 2007 to 2010 but the injuries and deaths rate are increasing in many districts.

III. CONCLUSION

The number of road accidents are increasing with increase in population and with number of registered vehicles. The number of road accidents in Himachal Pradesh are increasing from year 2013 to 2016 and also the severity index is increasing year by year. Severity index of Himachal Pradesh is more than the Severity index of Country means that more people are killed due to lack of hospitalization.
The major cause of accidents are fault of driver, over-speed, carriageway condition, over- loading and pedestrians.
Trucks and two wheeler type of vehicles are most responsible for road accidents.
Most of accidents occur in between 9:00 to 11:00 am and 5:00 to 8:00 pm.

REFERENCES

FSHATSYON BRHANE GEBRETENSAY, JAYESH JUREMALANI “A Road traffic accident analysis and prediction model: A case study of Vadodara city”, dept. of Civil engineering, Parul University, Gujarat, India.
SANJAY KUMAR SINGH, ASHISH MISHRA “Road accident analysis: A case study of Patna city.” Department of humanities and social sciences IIT Kanpur, Uttar Pradesh, India
MIAOMIAO LIU, YONGSHENG CHEN, GUANGQUAN LU “The Analysis of serious fatal road traffic accidents in China”, Research institute of Highway, Ministry of Transport, 8 Xitucheng road, Haidian district, Beijing 100088
MUKUL NAMA, MR. NANDESHWAR LATA, DR. BHARAT NAGAR “A statistical data analysis of road traffic accidents in Jaipur city.” Civil Engg. Department, Jagannath University, Chaksu, Jaipur, India
RAHUL BADGUJAR, PRIYAM MISHRA, MAYANK CHANDRA, SAYALI SANDBHOR, HUMERA KHANUM “Accident data analysis using statistical methods- case study of Indian highway” Department of civil engg, Symbiosis Institute of Technology, Pune, India
VELURU SAILAJA, DR. S. SIDDI RAJU, “Accident Analysis on NH-18 by using Regression Model and its preventive measures.” Deptt of civil engineering, Siddharth institute of Engineering and Technology, Puttur, A.P 517583, India
MANU.N.NAIR, DR.V. THANGAMANI, “An Analysis of Spatially explicit Scenario of Road Traffic Accidents in Kerala Using GIS.” School of Earth and Atmospheric sciences, Madurai Kamaraj University, Madurai, Tamil Nadu, India      

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Analysis of Road Accidents. (2020, Mar 10). Retrieved November 27, 2022 , from
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