Leveraging Technology: Relying on automated solutions to reduce road accidents

Relying on automated solutions to reduce road accidents

Akhilesh Srivastava, World Economic Forum, and IT Advisor, Government of Uttarakhand

Road traffic injuries (RTIs) are the eighth leading cause of death worldwide for all age groups and the leading cause for those aged 5 to 29. Close to 1·4 million people die each year and up to 50 million are injured by RTIs. Over half of these deaths are attributable to vulnerable road users such as pedestrians, cyclists and motorcyclists.

Road traffic accidents reduce a country’s annual gross domestic product by 1-3 per cent. India has the highest number of road fatalities in the world; every four minutes, one person di­es on Indian roads, costing the Indian economy nearly $55 billion, or 1.85 per cent of GDP.

The WEF approach

The issue of road safety has always been multi­faceted. Despite the fact that numerous factors contribute to fatal and non-fatal road injuries, evidence indicates that, in the context of a safe system approach, four primary risk factors continuously increase the risk of road injuries and deaths. The World Health Organization (WHO) has also identified these as key risk factors under the safe system approach. Risk factors include speeding, drunk driving, not wearing a helmet, and not using a seat belt or child res­tra­int. Although many other factors contribute to road injuries and fatalities, these four risk factors have a quantifiable impact on road mortality and morbidity.

According to a study published in The Lan­cet journal, approximately 30,000 lives in India could have been saved by implementing simple road safety measures. During the same study, researchers discovered that in India, 20,554 lives could have been saved by enforcing speed limits, 5,683 by wearing helmets, and 3,204 by using seat belts.

The World Economic Forum-led Road Sa­fety 2.0 pilots also indicate that over 80 per cent of accidents are due to human errors and the ma­jority can be prevented with the use of technology to compensate for human limitations. Besi­d­es the human errors of overspeeding, drunk dri­ving, driving on the wrong side of the road, driving without a licence, fatigue, stress, overloading, and traffic rule violations, accidents are also caused by deficiencies in road engineering that create accident-prone areas, the sudden appe­arance of potholes and inadequate safety measures in vehicles. However, driving behaviour continues to be the primary cause.

There is an urgent need for effective im­ple­­mentation of the safety system approach with evidence-based technological interventions to re­duce road traffic injuries. The WEF pilots sh­ow that addressing the aforementioned road safety risk factors using next-generation technologies can make it possible to avert between 25 per cent and 40 per cent of annual road ac­cident deaths. Technology has great potential for scalability with transparency and low-cost solutions.

Scope for improvement

Having identified the primary causes of traffic collisions, the steps that must be taken to improve driver behaviour in order to reduce the likelihood of collisions are not overspeeding, using seat belts and helmets, not driving wh­ile intoxicated or on the wrong side of the road, never overloading vehicles, and ensuring drivers always obey traffic laws.

According to the aforementioned study, be­haviour can be altered either by self-motivation or by fear of punishment through severe en­for­ce­ment. Motivating drivers to drive better th­rou­gh incentives and rewards is preferable in a densely populated nation such as India. The idea is to incentivise safe driving instead of spending resources tracking down and punishing reckless drivers.

The success of the WEF-led Road Safety 2.0 pilots demonstrates that this theory is effective in reducing accidents significantly. The second decade of Action for Global Road Safety has already begun, with the ambitious target of ac­hie­ving Sustainable Development Goal (SDG) 3.6, which calls for a 50 per cent reduction in road traffic injuries and deaths by 2030.

Reward ecosystem

Driver behaviour, which is a subjective matter, can be tracked using internet of things (IoT) and converted into scores that may be called “safe driving scores”. If these scores are popularised like Credit Information Bureau Limited (CIBIL) scores and utilised to reward, incentivise and give financial benefits to good drivers or to encourage vehicle owners to employ drivers with higher safe driving scores, a chan­ge from reckless to safe driving can be achie­ved. This has the potential to revolutionise traffic safety in India.

However, few vehicle original equipment manufacturers (OEMs), fuel companies, wayside amenities and vehicle spare parts companies have shown keenness to be part of this reward ecosystem.

Due to regulatory limits, insurance firms, the main stakeholders, were cautious. How­ever, the Insurance Regulatory and Develop­me­nt Autho­rity of India has now approved the change. This will lessen the road safety sector’s re­liance on third-party finance and create a self-sustaining environment. Good driving scores mean better drivers, who will get more rebates in insurance premiums. Similarly, careful drivers will lead to fewer accidents and thus fewer payouts for in­surance companies. This will lead to drivers stri­ving for higher safe driving scores in order to receive maximum insurance premium disco­un­ts. As a result, they will drive more cautiously, resulting in fewer road ac­cidents, which is a win-win situation for everyone.

Tech-based automated enforcement system

Self-motivating measures for improving driver behaviour alone can’t be the complete solution for road safety. Strict enforcement of traffic rules is equally essential.

In India, the manual enforcement system for detecting traffic violations and penalising violators is practically impossible. The enforcement system needs to be automated, comprising sp­e­ed cameras, incident detection cameras and au­to­matic number plate recognition systems, IoT and high-end software for real-time detection of violations and issuance of automated penalties with a robust recovery system.

Automated enforcement system via PPP model

The WEF conducted another trial for automated enforcement in the public-private partnership (PPP) model, with astounding results. The issue with automated systems is not the accessibility of technologies, but rather the availability of finances. The hardware and software of automated enforcement systems are relatively costly, and their flawless operation necessitates highly trained personnel. The majority of Indian cities and municipalities lack sufficient financial resources for this.

The WEF pilot project has devised an economically viable PPP model for the installation and operation of the automated enforcement system. The technology companies/OEMs are willing to bear the initial installation costs of the automated system, manage and operate it through their skilled workforce, and recover their capital and operations and maintenance costs as a portion of the penalty fees recovered by the government. Other than enhancing road safety and saving the lives of residents, this is financially feasible and will also generate additional revenue for cities and municipalities.

The global community is still a long way from meeting SDG 3.6, and accomplishing this objective will become more difficult now that the Covid-19 pandemic has altered governme­nt priorities and posed new challenges.