While the overall road network in India is similar to that of several developed countries, its quality is not internationally competitive at present. India has not only the highest crash fatality rate globally, but also the highest crash severity rate (with only 1 per cent of the world’s vehicles), both of which present a bleak image of road safety in India. The increasing number of road accidents and fatalities in India is largely due to poor road design and engineering, lax enforcement of traffic laws, and lack of timely trauma care.
Given the importance of the road sector in the Indian economy, the focus should be on rectification of black spots, widening of roads, deployment of a GPS system to alert drivers, maintenance and repair of roads and imparting driving training. Incorporating multiple safety features in a vehicle is not enough, they must also be optimally utilised.
The Ministry of Road Transport and Highways (MoRTH) has devised a multifaceted plan to address the issue of road safety. It has undertaken a number of initiatives to improve road safety in the country, including the dissemination of knowledge about road safety, road and vehicle engineering, enforcement of existing legal/legislative provisions for road safety, and emergency care. Roads are now constructed in line with the applicable Indian Roads Congress (IRC) standards and manuals.
The ministry has proposed that all vehicles of Category M1 manufactured after October 1, 2022 should be equipped with two side/side torso airbags, one for each person taking up an outboard front-row seat; two side curtain/ tube airbags, one for each person occupying an outboard front-row seat; and a three-point belt for all front-facing seats.
A mandatory fitment of safety technologies has been notified such as seat belt reminder (SBR) for the driver and co-driver, manual override for the central locking system, an overspeed warning system, and a reverse parking alert system for M and N category vehicles. In addition, a proposal has been issued to create one model inspection and certification centre in each state/union territory (UT), with the help of the central government, in order to evaluate the fitness of vehicles.
The National Highways Authority of India (NHAI) has made provisions for ambulances with paramedical personnel at toll plazas along the completed corridor of national highways (NHs). Road safety has been integrated into the planning, design and operation phases of road construction.
The detection and repair of black spots on national highways has been given top priority. Road design plays a crucial role in road safety. It is of utmost importance that road engineering standards be clearly defined and mandated for engineers and contractors to follow. Of the total 5,803 black spots identified by MoRTH, 4,002 black spots have been entrusted to NHAI. As of April 2022, 2,569 black spots have been rectified by NHAI. In addition, NHAI has decided to deploy network survey vehicles (NSVs) to improve the quality of the NHs as NSV utilises a high resolution digital camera for 3,600 imagery, record images/videos at regular intervals, laser road profilometer and other technologies for measuring road surface distresses.
Road accident data
Given its scale and severity, as well as its impact on the economy, public health and general welfare, road safety is both a health and development concern. At present, road traffic injuries are one of the main contributors to mortality, disability and hospitalisation in the world, resulting in significant socio-economic consequences.
As of July 2022, MoRTH has initiated a World Bank-funded project called the e-Detailed Accident Report (e-DAR), previously Integrated Road Accident Database (iRAD), to build a unified accident data collection mechanism. The project’s goal is to establish a central repository for reporting, management and analysis of road accident data for the entire country in order to comprehend the accident’s underlying causes and develop policies to facilitate the reduction of road accidents. Inferences derived from the report can then be utilised to identify gaps in the existing road safety provisions on Indian roads, which can be plugged to ensure that upcoming road stretches are as safe as possible, with an emphasis on road safety from the detailed project report stage itself.
Safety via road design
The assessment of data from various states and UTs demonstrates that road accidents are caused by a combination of elements, which can be roughly classified as human error, road condition/environmental factors and vehicle condition. Due to this, the ministry has taken initiatives via its implementing agencies, NHAI, the National Highways and Infrastructure Development Corporation and the NH wings of the state public works department. These include all-stage road safety audits for all national highways, the provision of rumble strips or bar markings at junctions on NHs, speed limit signs at desired network locations on NHs, speed breakers and corresponding signs on side roads, amber beacons for traffic approaching a junction, and installation of crash barriers on steep banks and terrain with hills. The ministry has also developed a black spot MIS site in which details of all black spots, pictures, rectification status, and post-rectification feedback would be monitored.
The ZFC model
In 2016, the SaveLIFE Foundation (SLF), an Indian non-profit organisation, introduced the Zero Fatality Corridor (ZFC) concept, which has enabled an unparalleled reduction in road crash fatalities along the segments of road where it has been implemented. The ZFC solution has modified and supplemented the Safe System Approach, which is a Western concept, to make it suitable for Indian requirements. The concept was deployed for the first time on the Mumbai-Pune Expressway (MPEW), where SLF used high-visibility patrol vehicles and drones to proactively locate parked or broken-down vehicles, remove or barricade them, and transmit the system to the police and road-owning agency. The enforcement capacity of the police was increased by putting speed enforcement cameras, particularly within and ahead of high-fatality zones. To expedite emergency medical response, data analytics was utilised to identify high-fatality zones; and moving ambulances closer to dangerous areas reduced the average response time from 35 minutes to less than 10 minutes.
Due to the success of the strategy, MoRTH has teamed with SLF to implement this model across the country’s 14 most dangerous highways. These highways are in Uttar Pradesh, Maharashtra, Karnataka, Tamil Nadu, Telangana, Haryana, Madhya Pradesh, Punjab, Gujarat, Bihar, Chhattisgarh, Andhra Pradesh, Rajasthan and West Bengal.
Artificial intelligence (AI)-powered technologies may make driving in India safer. Nagpur is currently implementing a novel AI approach that uses the predictive power of AI to identify risks on the road and a collision alert system to communicate timely alerts to drivers in order to make several improvements to road safety with the goal of achieving a significant reduction in accidents. The Intelligent Solutions for Road Safety via Technology and Engineering initiative in Nagpur will use the advanced driver assistance system to identify probable accident-causing events while driving a vehicle and inform drivers about them. This will also help discover grey spots, through data analysis and mobility analysis, by continuously monitoring dynamic threats across the entire road network.
Another dataset called Open World Object Detection on Road Scenes has been developed using the India Driving Dataset, which could be used by autonomous navigation systems in Indian driving conditions for the localisation and classification of objects. In addition, a Mobility Car Data Platform has been designed with multiple sensors – cameras, light detection and ranging (LiDAR) – for anyone to capture or process data on a car, allowing researchers and start-ups in India to test their automotive algorithms and approaches in navigation and research on Indian roads. LaneRoadNet, a new framework with an integrated mechanism considering lane and road parameters using deep learning, has been developed to address the problems of occluded lane markings, broken dividers, cracks, and potholes, etc., which pose a significant risk to drivers. Using a modular scoring function, a road quality score is calculated inside this framework. The final score assists the authorities in evaluating road quality and prioritising maintenance programmes to improve the road’s driveability.
The causes of unsafe roads are complicated and diverse, necessitating a methodical approach with road safety management, safer vehicles and road users, better infrastructure, and post-accident care. Road designs that regulate speeds appear to be the most effective means of preventing collisions. A substantial amount of additional work is required on the rural and urban road and infrastructure design for mixed traffic. According to the Stockholm Declaration, the Indian government is committed to lowering road traffic deaths and injuries by 50 per cent by 2030.