Identification of Accident Black Spots on NH-65 (Chaudhriwas, Hisar to Hisar City)

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Identification of Accident Black Spots on NH-65 (Chaudhriwas, Hisar to Hisar City) Sunny Tawar 1, Sachin Dass 2 1 Assistant Manager, Traffic and Transportation Department, Intercontinental Consultants and Technocrats Pvt. Ltd., A-8 & A-9, Green Park, New Delhi. India 2 Assistant Professor, Department of Civil Engineering, Deenbandhu Chhotu Ram University of Science and Technology, ---------------------------------------------------------------------***--------------------------------------------------------------------- Abstract - Road accidents are increasing rapidly in India with the increase in traffic density. Due to which there is a huge loss of life and property. The location of road where the maximum number of accidents occurs is known as a Black Spot. This paper deals with the study and to analyze the traffic safety situations in the section from Chaudhriwas, Hisar to Hisar City on NH-65(new NH-52) in the state of Haryana(India) and to identify countermeasures for the stretch so that the total harm caused by the road crashes can be reduced to some extent in future. The stretch of 19.5 kms is taken for study. In this paper, the identification of road accidents and its causes, variations with respect to yearly, monthly, hourly, user type, vehicle, age, seasonal and also the number of black spots by further giving the suggestions and conclusions to reduce the road crashes and to make safer for road users. Key Words: Road Accidents, Fatalities, NH-65 (NH-52), Black Spots, Improvement Measures cent of these casualties are associated with motorcycles and trucks. The most accident-prone time on Indian roads is during the peak hour at afternoon and evening. According to road traffic safety experts, the actual number of casualties may be higher than what is documented, as many traffic accidents go unreported. Moreover, victims who die sometime after the accident, a span of time which may vary from a few hours to several days, are not counted as car accident victims. 2 STUDY AREA National Highway-65 (NH-65) (from Chaudhriwas, Hisar to Hisar City in the state of Haryana i.e. 19.5 kms.) is one of the major national highway starting from Ambala (Haryana to Pali (Rajasthan) as shown in the Fig.-1:- 1 INTRODUCTION Road accidents are increasing day by day in India, as India is the largest country in the phase of larger number of Accidents in the Worldwide. More than 700 Black spots were identified & analyzed on National Highways across the country in the year 2011 to 2014 according to Ministry Of Road, Transport & Highways (MORTH). The accident rate is much higher in India as compared to the other countries such as USA, Canada, Europe As, there is a huge network of Highways in India but traffic density is also very much high. Indian Literacy percentage is 65% and hence people are less aware of the traffic rules and regulations. These factors have added in increase in road accidents and further increase in the loss of life and property. Traffic collision-related deaths increased from 1.5% in 20014 to 2.5% rises in. More than 40 per (Source: Google Map) Fig. 1: Stretch under Study 3 OBJECTIVE & SCOPE OF THE WORK The selected stretch is a part of NH-65 which is further named as NH-52. The accident data collected for the last five years from 2011 to and to derive the improvement measures. The objectives of study include: 2017, IRJET Impact Factor value: 5.181 ISO 9001:2008 Certified Journal Page 848

a) Identification of suitable black spots. b) Analysis of top ranked black spots and suggestion of possible improvements & measures. 4 DATA COLLECTION Datas were collected from FIR index of police department during period 2011-. It has been collected from various Police Station i.e City Hisar, Sadar Thana Hisar, Barwala Sadar Thana and Uklana. Accident data was collected under the following heads: 1. Date of accident. 2. Time of accident 3. Day of accident 4. Type of Hitting Vehicle 5. Type of Hitten Vehicle. 6. Injuries (Severe/Minor). 7. of deaths/fatalities 8. Monoveour Type/Collision Type 9. Location of accident 10. Ref. or Entry 11. Beat duty. 12. Driver Age(years) 13. Victim Age(years) 14. Village/landmark nearby location. 15. Damage to property 5 DATA ANALYSIS 5.3.1 Yearly Variation of Accidents Table -1: Yearly variation of Accidents data from 2011- Year of Accidents 2011 14 2012 20 2013 10 2014 19 15 Table1 shows that there are 78 numbers of accidents took place from the year 2011-. 5.3.2 Monthly Variation of Accidents Table -2: Monthly variation of Accidents data from 2011- Month of Accidents January 6 February 3 March 6 April 3 Month of Accidents May 8 June 4 July 11 August 10 September 9 October 6 November 9 December 3 Table 2 shows that there are 78 numbers of accidents took place from the year 2011-. Maximum no. of accidents occurred in the month of July and August which is the summer season and driver s do move at excessive speeds and are also inattentive. 5.3.3 Hourly Variation of Accidents Table -3: Hourly variation of Accidents data from 2011- Time of Accidents 12:00 a.m. to 02:00 a.m. 3 02:00 a.m. to 04:00 a.m. 0 04:00 a.m. to 06:00 a.m. 4 06:00 a.m. to 08:00 a.m. 3 08:00 a.m. to 10:00 a.m. 5 10:00 a.m. to 12:00 p.m. 6 12:00 p.m. to 02:00 p.m. 15 02:00 p.m. to 04:00 p.m. 8 04:00 p.m. to 06:00 p.m. 7 06:00 p.m. to 08:00 p.m. 9 08:00 p.m. to 10:00 p.m. 16 10:00 p.m. to 12:00 a.m. 2 Table3 shows that the maximum accidents occurred during night time between 08:00 p.m. to 10:00 p.m. Accidents are occurred more during night time as compared to day time. Its seen that during day time visibility is more and no. of strips are also more, so drivers have a tendency to take risks more in the day timings. It is also seen that the persons leaving from work in the late night hours shows the rise in accidents. 5.3.4 Accident Identify as per Vehicle Type Table-4: Accident as per vehicle hitted type Vehicle Hitted Car/Jeep 28 Bus 4 2017, IRJET Impact Factor value: 5.181 ISO 9001:2008 Certified Journal Page 849

Vehicle Hitted Truck 19 M/C 8 Unknown 5 Auto-Rickshaw 4 Pick-Up 4 Canter 2 Tractor 4 Table 4 shows maximum no. of accidents occurred due to Car/Jeep and Trucks; this may be due to formation of ruts and cracks on the highway which creates unsuitability for the traffic to flow properly. 5.3.5 Accident Identify as per Vehicle Type Table-5: Accident as per vehicle hitten type Vehicle Hitten Pedestrian 21 Auto-Rickshaw 2 Canter 3 Cycle 4 M/C or Scooty or Scooter 28 Animal 1 Car/Jeep 13 Bus 1 Truck 2 Public Property 1 Unknown 2 Table5 shows that Motorcycle/Scooty/Scooter and Pedestrians becomes the main victims of the accidents. This is may be due to the inadequate and improper installation of traffic signs and symbols and poor pavement markings. Table 6 shows that maximum no. of accidents occurred due to Head-on-collision type and then vehiclepedestrian collision type; this may be due to speeding of vehicles and overtaking from wrong side. 5.3.7 Accident Identify as per Accident Type/Severity Table-7: Accident as per accident type/severity of a during 2011- Injuries Minor 24 Fatalities 26 Serious 64 Total 114 Table 7 shows that there are 114 no. of severity occurred which consists of 64 serious injuries, 26 fatal and 24 minor. There is a high rise in the severity of the injuries during 2011-. 6 BLACK SPOT IDENTIFY Table-8: shows Black Spot details Location of Accidents Chaudhriwas Village, Hisar (A) 17 Gangwa Village, Hisar (B) 25 Azad Nagar, Hisar (C) 21 Hisar City (D) 15 Black Spot Locations are shown in the Fig.-2 and stretch condition including formations of ruts, pot holes and poor maintenance is shown in Fig. 3 & 4 respectively :- 5.3.6 Accident Identify as per type of Collision Table-6: Accident as per type of collision during 2011- Type of Collision Vehicle-Pedestrian Collision 21 Head-on-collision 28 Rear-end collision/shunt 14 Side Collision 9 Single-Vehicle collision 4 Vehicle-Animal collision 2 (Source: Google Map) Fig.-2: Black Spot Locations 2017, IRJET Impact Factor value: 5.181 ISO 9001:2008 Certified Journal Page 850

4) Maximum no. of accidents occurs due to Car/Jeep and further due to Trucks. 5) Two-wheelers and Pedestrians became the main victims of accidents and severity. 6) Most of accidents are caused during monsoon season in the month of July and August indicating lack of driver s alertness during bad weather conditions. 7) Maximum accidents are caused due to heavy traffic. 8 REMEDIAL MEASURES Fig.-3: Formation of ruts, cracks and pot holes nearby Gangwa Village, Hisar. Fig.-4: Poor pavement markings and maintenance nearby Chaudhriwas Village, Hisar 7 CONCLUSIONS From the accident analysis, it is observed that maximum accidents are occurring during night as compared to day time. This may be attributed due to heavy road traffic, poor lighting conditions on highway, poor pavement markings and formation of ruts, pot holes and cracks. Policies during rush hours must be there on highway. This will reduce the accident on black spots considerably. On the basis of data recorded and analyzed, it can be concluded that: 1) Maximum accidents found to occur due to head-oncollision and further due to vehicle-pedestrian collision. 2) Majority of accidents occur at village junction on highway. 3) Maximum are recorded during day time (12:00 p.m. to 02:00 p.m.) as well as during night time/peak hours (08:00 p.m. to 10:00 p.m.) but the accidents during peak hours are more than during day time. 1) There is a need to maintain the pavement marking in the selected stretch from Chaudhriwas, Hisar to Hisar City. 2) Speadbreakers/Rumble Strips need to be constructed upto the approach road near Gangwa Village and Azad Nagar. 3) Inadequate hoardings on the shoulders including advertisements which further results in lack of concentration while driving by driver. 4) Pedestrian crossing required for the pedestrians to move freely on the road near Gangwa Village. 5) Separate bus bays must be constructed for the passenger safety and facility near Gangwa Village. 6) There are many road links near Azad Nagar, so there is need to provide service road for the local traffic to move freely without merging into the heavy traffic on highway. 7) Various stalls are there on the shoulder of highway near Azad Nagar, so there is need to provide them another space for their selling of goods which will further results in efficient movement of pedestrians. 8) Proper lighting in the village areas like Gangwa and Chaudhriwas needs to be installed for the efficient movement of heavy traffic on highway. 9) Filling of cracks, patch work need to be done on the complete stretch as there is heavy traffic flow takes place. REFERENCES [1] A.N. Dehury (2013), Black spot analysis on national highways; estimating accident severity on nh-55 and black spot analysis, Page 1-7 [2] Prof S.M. Damodariya (2014), Road safety audit for kapurai - dabhoi section of state highway-11, Page 1-4 [3] Vivek, Rakesh Saini (), Identification and improvement of accident black spots on nh-3 district una, himachal pradesh a case study, Page 2-22 [4] Liyamol Isen, Shibu A, SaranM.S. (2013), Identification and Analysis of Accident Black Spots Using Geographic Information System, Page 2-6 [5] Apparao. G, P. Mallikarjunareddy, Dr. SSSV Gopala Raju (2013), Identification of accident black spots for national highways using gis, Page 1-4 2017, IRJET Impact Factor value: 5.181 ISO 9001:2008 Certified Journal Page 851

[6] Rajivas V.A., Bindhu B.K., Bino.I. Koshy (2014), Road safety audit of kochi metro during its construction stage, Page 2-5 [7] Reshma E.K., Sheikh Umar Sharif (2012), Prioritization of accident black spots using gis, Page 2-4 [8] David.D.Clarke, Patrick Ward, Craig Bartle, Wendy Truman (2010), Accident anlaysis and prevention, Page 2-6 [9] Patel A.K. and Desai M.M., 2011, Road accidents study based on regression model: a case study of ahemdabad city, National Conference on Recent Trends in Engineering and Technology. [10] Ravishankar Rajaraman (2009), Analysis of road traffic accidents on nh-45, kanchipuram district (tamil nadu), IRTAD Conference,16-17 September, 2009, South Korea [11] Francisca Nonyelum Ogwueleka, Sanjay Misra, Toochukwu Chibueze Ogwueleka, L. Fernandez-Sanz 2014, An artificial neutral network model for road accident prediction : a case study of a developing country, 1-22 BIOGRAPHIES Sunny Tawar did Bachelor of Technology in Civil Engineering from B.R.C.M. College of Engineering & Technology, Bahal, Haryana, India in 2013, Masters of Technology in Civil Engineering in 2016 with specialization in Highway Safety & Engineering from DCRUST, Currentlly working as an Assistant Manager in Traffic & Transportation Department in Intercontinenetal Consultants & Technocrats Pvt. Ltd., New Delhi, India. Sachin Dass did B.Tech. (Civil Engg.) and M.Tech. (Civil Engg.) having specialization in Highway Engineering from NIT Kurukshetra respectively. Currently, working as an Assistant Professor at DCRUST, having teaching experience of 6 years, also 5 international/ national papers in journal and conference received. 2017, IRJET Impact Factor value: 5.181 ISO 9001:2008 Certified Journal Page 852