Road Accidents In India Research Articles

Forecasting Road Accident Deaths in India Using SARIMA

Road accidents are one of the leading causes of death worldwide. The present study analysed the pattern of road accident deaths in India from the year 2014 till the year 2022. The data was taken from the government website, and we have split it into training and testing datasets. The training dataset was from the year 2014 to 2020, and the forecasting was done for the years 2021 and 2022. We have used the SARIMA model to forecast the number of road accidents in India for the years 2021 and 2022. The accuracy of the SARIMA model in forecasting the number of road accidents in India is also established in the present study. The study has insights for policymakers and administrators. Some of the policies that can be enforced to decrease the number of road accidents in India are better road infrastructure for vehicles across India, enforcement of safety regulations, easy access to trauma care centres, strictly following the speed limits on the road and so on.

Road Accident Analysis and Classification Using Machine Learning Algorithms

Abstract: India is facing a severe public health crisis characterized by a significant number of road accidents resulting in fatalities and life-altering injuries. This study undertakes a detailed analysis of road accidents in India using multi-year accident data to unveil recurring patterns and identify high-risk demographics. The research meticulously examines the primary causes of these accidents, including driver behavior such as speeding, and inadequate road infrastructure such as poor lighting, signage, potholes, and vehicle malfunctions. Moreover, the paper proposes a comprehensive approach to prevent these tragedies. It suggests strategies for enhancing road design and maintenance, enforcing traffic regulations more rigorously, and conducting targeted public awareness campaigns to promote responsible driving practices. By highlighting the alarming increase in fatalities and the substantial socio-economic costs associated with these accidents, this research emphasizes the critical need for immediate and effective interventions to establish a safer road environment for all citizens in India.

BIKE RIDER SAFETY SYSTEM USING STM 32 MICROCONTROLLER

This study focuses on the development of an innovative safety jacket designed for horse riders, high-altitude workers, and particularly two- wheeler riders to mitigate the impact of accidents and enhance life-saving measures. Given the high incidence of road accidents in India, with 499,628 reported in 2010 leading to 134,513 fatalities and over 500,000 injuries, the need for improved safety mechanisms is critical. The proposed safety jacket integrates a micro controller-based system to detect falls and trigger an emergency response, inflating air cushions around the jacket to cushion impacts. Additionally, the system incorporates an alcohol sensor and a helmet detection sensor to ensure the bike starts only if the rider is sober and wearing a helmet. Visibility issues for riders are also addressed, with the jacket featuring turn indicators and other visibility enhancements to alert other road users. The jacket is designed to be water-resistant and washable, ensuring durability and ease of maintenance. The Bike Rider Safety System (BRSS) further enhances safety through real-time monitoring and adaptive response to potential hazards, using accelerometer, gyroscopes, and proximity sensors. The Arduino-based system comprises four main functionalities: helmet and alcohol detection, accident detection, airbag deployment, and live location transmission to authorities. In summary, the smart jacket aims to significantly reduce the risks faced by riders by incorporating advanced technology and a robust design to ensure their safety on the road.

Determinants of Road Traffic Crash Fatalities: A Case of Road Accidents in India, 2004–2018

The purpose of this study is to determine the factors that influence deaths in road accidents in India. The study uses panel econometric methodologies such as the fixed effects model, random effects model, and Hausman–Taylor instrumental variable technique to achieve this goal. Unobserved heterogeneity between states/union territories (UTs) and time is accounted for by time-fixed and state-fixed effects. Based on the panel data set from Indian states/UTs for the period 2004–2018, the study confirms previous results that motorisation, population, urbanisation and income level are all potential contributors to road accidents and fatalities. It also shows that spending on health care and law enforcement appears to help the Indian states minimise mortality in road traffic accidents. On the one hand, spending on health care facilities can provide health-related assistance to persons who have been involved in traffic accidents; on the other hand, spending on police increases the enforcement of rules, resulting in a reduction in traffic accidents. Thus, to lessen the economic and financial cost of road accidents in the country, the government should focus on boosting both per capita health expenditure and per capita police expenditure. JEL Codes: C23, C26, H51, I18, L92, O18, R41, R42

Forecasting road accidental deaths in India: an explicit comparison between ARIMA and exponential smoothing method

The number of deaths due to road accident is increasing day by day and has become an alarming global problem over the decades. India, with her rising motorization is no stranger to this global catastrophe. In this paper two relatively simple yet powerful and versatile techniques for forecasting time series data, autoregressive integrated moving average method (ARIMA) and exponential smoothing method are used to forecast the number of deaths due to road accidents in India from the year 2022–2031. The results based on the two methods are compared and it is found that they are in sync with each other and pre-existing literature. Furthermore, this is a unique attempt to use two time series analysis techniques on the same data and carry out a comparative analysis. The data was collected from the annual report of Ministry of Road Transport and Highways, India (2020) and Accidental Deaths & Suicides in India (ADSI) Report of National Crime Record Bureau (2021). After examining all the probable models, it is observed that ARIMA (2, 2, 2) model and exponential smoothing (M, A, N) model are suitable for the given data. Amongst the two, ARIMA (2, 2, 2) model has a lower AIC and BIC value. Thus, this comes out to be the best model as per our model selection criterion. Further, the study also reveals an upward trend of number of road accidental deaths for the upcoming 10 years in India.

Road Accidents in India & Role of the Family- A Sociological Exploration with Special Reference to Ajmer

According to the recent report released by the WHO every year around 1.25 million people die due to road accidents. It is indeed a loss for any society, especially when people aged between 18-39 are the maximum and die from road accidents. Every death has a socio-economic ‘cost’ that can’t be repaid by any government. According to the Ministry of Road Transport and Highways’ 2020 report, there were a total of 1,31,714 deaths due to road accidents in India. India accounts for almost 10% of all crash-related deaths while accounting for only 1% of the world’s vehicles. Road Traffic Injuries (RTIs) are the eighth leading cause of death globally for all ages and the first cause in the 5-29 years age group. This paper is an attempt to explore if there is any relation between road accidents and the role of family in lessening them.

Insight on Vision Zero Strategy and Road Accidents in India

Abstract: Vision Zero is a road safety strategy that aspires to eliminate all traffic deaths and serious injuries while also promoting safe, healthy, and egalitarian transportation for all. It focuses on improving road infrastructure, lowering vehicle speeds, and encouraging everyone on the road to be safe. Vision Zero strategy has been implemented by India so that road deaths are minimized. The paper examines the attributes and reasons of road accidents in India. It further provides recommendations for minimizing the road accidents. The paper concludes with understanding the importance and need of vision zero strategies in India. Vision Zero proposes that all road accidents can be prevented and offers a basis for learning from accidents and improving processes should they occur.

Road Accidents in India: Looking Through the Behavioral Lens

While connecting people and their lives, roads also have a cost on them. It is clear that one of the major causes of death worldwide is traffic-related fatalities. In 2016, 1.35 million persons worldwide lost their lives in traffic accidents, 90% of which occurred in poorer nations (World Health Organization, 2018). One of the top causes of death for children between the ages of 5 and 29 is traffic-related injuries. More people lose their lives as a result of automobile accidents than from diarrheal illnesses or tuberculosis. The government has made a lot of efforts and implemented many mitigation techniques both locally and globally, but infrastructure, enforcement, and behavioural understanding of road safety are still lacking. The 50% reduction in the number of traffic accidents outlined in Sustainable Development Goal 3.6 is far from adequate. So, this study aims to provide an overview of road accidents at the global and national levels as well as behavioural attributions and changes in people's behaviour for road safety. Key words: Road accidents; behavioural intervention; road safety; traffic accidents; SDG2030

The Prevalence of Road Accidents in India

The Prevalence of Road Accidents in India

Safety Aspects of Minor Road Junctions on MDR 132 – Nuh to Hodal

Accident occurring at junctions is a major problem in India. As per the annual report 2019, almost 50% of road accidents in India occurred at junctions. In this study, an attempt has been made to study the safety aspects of minor road junctions on MDR 132 in the Palwal District of Haryana State. The main aims of the present study are to study the safety aspects of minor road junctions on MDR-132 from Nuh to Hodal by analyzing various features of minor road junctions like markings, signs, shoulders, sight distances, lightings, median, etc., and to give suggestions to minimize the accidents. Two types of data were collected. One is from the field, and the other is from registered FIRs. The first one includes pavement width, shoulder width, marking, speed breaker, signs, types of junctions, sight distance, etc. The second one includes hitting and victim vehicle, fatal, grievous and minor injury, visibility, age of the victim, etc. It was observed that the number of accidents is being affected by various road parameters. For example, the number of accidents at uncontrolled junctions is decreasing as pavement width, shoulder width, sight distance, and presence of speed breaker [especially on minor roads] are increasing. Similarly, it was also observed that the number of fatalities decreased as the considered road parameters were increased.

Accident analysis and road safety audit: a case study on NH-76

Road accidents in India are on the rise as the country’s vehicle population grows. As a result, a considerable number of lives and assets have been lost. The formal process for determining causal factors responsible for road accidents in new or improvement of existing road projects without any major modification in the design is known as a road safety audit. This study examines the traffic safety situation on NH-76 from Udaipur to Chittorgarh in the state of Rajasthan, India, intending to identify causal factors responsible for road accidents so that the real damage resulting from road collisions can be reduced to some extent in the future. For this study, a 93.5-kilometer span was chosen and accident data was obtained from the enforcement department via recorded accident FIRs from 2017 to 2019. The accident data was studied to determine the reasons, taking into account yearly, hourly, time-wise, day-wise variation, accident nature-wise, and other factors. Black spots were also identified in the study area and recommendations based on analysis were made to prevent traffic accidents and make the route safer for users. The purpose of this study is to uncover flaws, improve design characteristics, and improve road credibility.

Driver Drowsiness Detection Using Machine Learning

In today’s world, the number of road accidents that occur is increasing very rapidly. Some of these road accidents are minor whereas some of them may seriously injure people or even take their lives. These road accidents may involve collision of vehicles with each other or crashing the vehicles on to the buildings or others. Road accidents may even result in the death of people. It is estimated that the total deaths due to road accidents in India is around 1,50,000 per year which is approximately 400 accidents per day. Almost 3 lives are lost in every 10 minutes due to road accidents. one of the main factors that lead to road accidents are fatigue and drowsiness. Some popular methods that detect drowsiness use ECG and EEG, which are very complex. Even though these approaches are very precise, they require human involvement and have limitations that make them unsuitable for real-time driving. We’re working on a technique to detect drowsiness in driver by monitoring the eyes and mouth while they’re driving. The proposed method uses python along with two libraries OpenCV and dlib for facial landmark detection. A mathematical values Eye Aspect Ratio (EAR) and Mouth Aspect Ratio (MAR) is then calculated for determining whether the eyes are closed or not and weather the person is Yawning, The proposed systems detects these signs and plays an alarm.

Vanet‐TSMA: A traffic safety management approach for smart road transportation in vehicular ad hoc networks

SummaryOver the past two decades, vehicular collisions have been a significant concern for governments, researchers, and automobile manufacturers. However, collisions are unexpected and occur regularly on roads, resulting in deaths, infrastructure destruction, and health injuries. As a result, it is essential to avoid, prevent, and detect traffic collisions at the highest degree possible for minimizing human loss. In this article, the trend of road traffic accidents in India has been analyzed graphically. Towards the end, a VANET‐based traffic safety management approach (VANET‐TSMA) has been proposed to reduce road accidents in India. This approach uses message distribution, traffic management, and congestion control efficiently for reducing the overall rate of road accidents. This method is based on multiple information and communication technology (ICT)‐based safety mechanisms which include collision avoidance, collision detection, and traffic congestion avoidance for the protection of future connected automobiles on roads.

Brainy Road Accident Mitigation System

Many precious lives are lost due to road accidents because of over speeding and negligent driving every day. This is the matter of great concern for departments that deal with road safety and for the citizens. It is estimated that 80% of crashes and 65% of near collisions are due to driver’s lack of attention to traffic for three seconds before the event. The number of road crash deaths has increased by 31% from 2007 to 2017. As per the survey on the road accidents in India, according to the Ministry of Road Transport and Highways, 1, 50,785 people were killed and another 4, 94,624 were injured in 4, 80,652 road crashes in India in 2016. Now day’s accidents are taking place at large scale. Majority of the accidents occurs due to the over speeding of vehicles, though there are speed limiting boards placed at the roadside of highways also at the road side in the city. But none of vehicles (drivers) follows the speed mentioned in the speed limit boards, due to which accidents occurs.

A Narrative Review of Trauma Care Delivery in India: Challenges and Opportunities

It is estimated that the cost of road accidents in India is around 3% of the Gross Domestic Product of the country. On average, 400 persons die daily in road accidents in India, and cities, such as New Delhi and the national capital region are on the top of the list of road accident causalities. Based on the Basilica agreement, the Indian government has initiated various policy changes and infrastructure development along the national highways which include the redesign of blindspots on the roads and the infliction of heavy penalties for the violation of traffic rules and compliances. On the academic front, the Indo-US Emergency Medicine forum has inaugurated an academic college for emergency medicine in India that cooperates with various government and private healthcare providers and policymakers for the improvement of emergency/trauma care delivery. Lately, few business schools and healthcare educational institutes have focused on interdisciplinary training and research centers in the area of emergency care delivery. Policymakers are also proactively working with various organizations to implement new rules and compliance mechanisms. This prospective study entails a detailed review of the literature using keywords in the PubMed journals, news articles, and media reports. Authors encountered studies in the area of trauma care delivery in India and other countries in their comprehensive field research. Almost 100% of the cases were medico-legal and only one case out of 100 was an insured patient. Furthermore, 87% of the cases were new and only 13% were review cases. Based on the conducted analysis, the number of accidents reduced across the country after the implementation of the New Motor Vehicle Act in the year 2019. It is worth mentioning that, the government launched awareness programs for the public as well. Some of the major challenges identified included lack of coordination and institutional mechanisms for an integrated emergency care delivery, poor referral processes, inadequate ambulance services, lack of third-party coordination, and poor in-hospital resources, particularly in public healthcare organizations. Apart from these, there was an acute shortage of trained emergency medicine experts at all levels. Trauma care delivery is a complex issue and its accomplishment requires good coordination and collaboration among stakeholders. The study identified various challenges and opportunities for the improvement of trauma care delivery in India. There is an immense need and opportunity for the modification of the emergency care delivery system through the introduction of appropriate changes in the transportation policy, emergency care delivery models, institutional mechanisms, such as referral process, and appropriate resource allocation at different levels of care delivery system.

Vulnerable road user safety: A systematic review and mesh‐networking based vehicle ad hoc system using hybrid of neuro‐fuzzy and genetic algorithms

SummaryIntelligent Transport System (ITS) involves a number of Information and Communication Technology (ICT) interventions for efficient road safety management. Over the last few decades, there has been a significant increase in the safety of Vulnerable Road Users (VRU's). This study aims to identify the most frequent, regularly occurring causes of road accidents and outline actions that can be used as a baseline for improving road traffic safety. The main contributions in this paper include the following: a graphical investigation for finding out the overall rate of road accidents (injuries and deaths) in India. Based on graphical analysis, major loopholes responsible for road accidents in India are summed up. This paper discusses various issues faced by already available pedestrian and vehicular safety techniques. After analysis of the available techniques and their related case studies in a systematic way, it is observed that they are not able to overcome the loopholes (Collision Occurrence, Traffic Congestion, Pedestrian Crossing alert, Red Light violation, and Non‐Propagation of Distress Signal) present in the current “Road Transport Management (RTM) System” of India. Finally, after deep analysis of already available techniques, a futuristic approach “Mesh‐Networking based Vehicle Ad‐Hoc System (MN‐VAS) using hybrid of Neuro‐Fuzzy and Genetic Algorithm based Load Balancing on Node” is proposed for the safety of VRU's. This hybrid approach has been discussed with domain experts for practical input, and we concluded that this might be a good option for better RTM System in India.

Intelligent speed breaker system design for vehicles using Internet of Things

Bad visibility conditions which occur due to fog in winters or night time driving are the major causes of road accidents in India. The principal cause for such accidents is the unintentional ignorance of speed breakers which may be due to the driver not being able to detect them or may be due to over speeding of vehicles. This paper brings an idea of an intelligent speed breaker system that helps in detecting speed breakers well in time so that such accidents can be avoided. This system makes use of a RF module that warns the person who is driving about the existence of a speed breaker in proximity, with this it assists in automatically reducing the vehicle’s speed if no action is taken by the driver in time. Through Internet of Things (IoT), GPS Location (latitude & longitude) of speed breaker can be sent to cloud using GPS and stored on cloud to use it for future to avoid mishaps.

Real Time Driver Drowsiness Detection App using ML

Every year road accidents are increasing rapidly as technological and mechanical advancements in vehicles permits drivers to drive at high speed. Approximately 1.35 million people die each year as a result of road accidents in India alone 151 thousand casualties were recorded last year. From this nearly 78% road accidents are caused due to driver's fault. Main factors for this accidents are drowsiness, drunk and drive and over speeding from which nearly 40% of the accidents caused due to drowsiness. People are conscious about the risk of drinking and driving but don’t realize the dangerous of drowsiness because no instruments exist to measure the driver drowsiness. If the Driver fails to concentrate on driving it reduces the driver reaction time and impairs steering behavior To solve this problem we are going to use the power of machine learning to identify if the driver is drowsy or not. Generally when someone feels drowsy his\hers eye blinking speed decreases by specifying threshold value we can detect if the driver is drowsy or not. This programme provides a mechanism for scanning facial landmarks and then using the essential landmarks for eye tracking after recognising the face. this insures that the driver is in full control of his vehicle. The system make use of device’s front camera to monitor drivers’s face to detect drowsiness and alarms the driver if system founds him drowsy. More functionality will be added to the system, such as issuing an SOS if something occurs to a car in a remote location. The software also has emergency numbers, so that in the event of an emergency, the driver may call the appropriate authorities as needed. This system may also be used for navigating by utilising the app's map functionality. Flutter will be utilised to provide a native and user-friendly system interface. As a result, the software will be available for both Android and iOS smartphones. The use of as little hardware as possible will ensure seamless processing. This technology may be employed in a variety of circumstances, including cab services, state transportation and on-road goods delivery.

Assessment and Prioritization of the Critical Factors Triggering Road Accidents in India

Road safety and its risk assessment has become very significant due to the increasing population and usage of transports in the current scenario. This research work primarily focuses on assessing the critical risk factors that trigger road accidents in India. Based on literature review and expert’s opinion, twenty-eight risk factors are identified and rated on a scale from 1 – 6. These critical factors are prepared as a questionnaire and the required input data is collected from a diversified set of automotive users. Further, the data is carefully processed and analyzed for identification of severe risk factors and its allied route cause based on the survey pattern. Three different cut-off patterns (Low risk, high risk & medium risk zone) are included to make the study more interesting, and the 28 factors are clustered with the aid of the collective results. Also, the dominant risk factors that has higher probability in triggering road accidents are identified for possible rectification.

Knowledge, attitude, and practice toward road safety regulations among college students in Telangana state.

BACKGROUND:Road traffic continues to be a major developmental issue and a public health concern. Road accidents in India kill almost 1.5 lakh people annually, and India accounts for almost 11% of the accident-related deaths in the world. Prevention of road traffic accidents is very crucial by creating awareness and taking proper measures toward road safety.AIMS:The aims of this study were to assess the knowledge about road safety regulations and to assess the attitude and practices regarding road safety regulations.SETTINGS AND DESIGN:This cross-sectional study was conducted in a pharmacy college.SUBJECTS AND METHODS:Study participants were all 4 academic years' pharmacy students who know driving two- or four-wheeler motor vehicle. Data were collected from a sample of 132 by predesigned pretested semi-structured questionnaire.STATISTICAL ANALYSIS USED:Data were presented in proportions with confidence interval using SPSS ver. 22.RESULTS:81.1% of the participants knew the minimum age to obtain driving license. Only 16% follow the road signs strictly and 76% wear helmet for long-distance ride. Poor attitude was observed for wearing helmet for short-distance ride, pillion rider wearing helmet, and drink and drive.CONCLUSIONS:Majority of the participants were aware of road safety regulations. In spite of having positive attitude toward road safety measures by participants, they could not translate attitude into practice.