Improving Road Safety through Smart Data

Data gathering eco-system

Conventionally, road accidents are attributed to driver error as the main problem. Due to this type of analysis, the contribution of human errors is grossly exaggerated without considering the role of vehicle and environmental factors in an accident and injury causation in developing countries. Even in the US, the UK, Germany, Sweden and other countries, driver error is the major reason for crashes. So how do they manage to reduce fatalities and crashes?

To understand the entire ecosystem involved in a crash, an important concept that every person working towards road safety should know is the Haddon Matrix. This is the fundamental concept that is being used by all countries that have successfully reduced fatalities. Created by Dr. William Haddon Jr., who is widely regarded as the father of modern injury epidemiology, the Haddon Matrix is a scientifically driven approach for understanding how injuries occur in road accidents and developing strategies for intervention. Every crash has three main factors – human, vehicle and infrastructure – and they need to be examined over three-time phases – pre-crash, crash and post-crash. These three factors (columns) and three-time phases (rows) together form the Haddon Matrix. Each cell of the Haddon Matrix identifies a factor and a time-phase and what elements go into it. For example, head injuries to motorcyclists caused as a result of a crash during which the motorcyclist was not wearing a helmet, is a human-crash problem. While poor intersection layouts that lead to the occurrence of crashes are an infrastructure-precrash problem.

The Haddon Matrix is a powerful concept which JP Research India crash investigators use for examining every crash. The objective of their scientific crash investigations is to determine the failures, in each of these nine cells, which led to the occurrence of the crash and the resulting injuries. By finding out the failures of a good number of crashes, it is possible to identify the areas of priority, in each of the nine cells, where planned interventions and investments will result in targeted reduction of fatalities and injuries.

Ravishankar Rajaraman, Technical Director, JP Research India Pvt Ltd explained, “To collect good quality crash data, the core problem is finding organizations and government agencies in India who understand the importance of crash data and are willing to support the data collection work. Many still think it is impossible to conduct crash investigations in India. But our experience has been that the police and other local entities dedicated to public safety show great interest and provide good co-operation for undertaking such studies. Over the past decade, we have successfully engaged police, road engineers, government agencies, NGOs and other stake holders to work together and use data-driven approaches to improve road safety.

“Today, even after a decade of crash investigations, the main challenge we face is in getting post-crash data from emergency medical services and hospitals where victims have been admitted. It is important for the medical fraternity in India to share detailed injury data using techniques such as Abbreviated Injury Scale (AIS), which combined with in-depth crash data, can help engineers design safer roads and safer vehicles, and help policy makers come up with data-driven road safety policies.”

Data Driven Road safety practices in India are still in a nascent stage. Crash data collection is usually trivialized by many agencies in India who think that they are collecting sufficient data as prescribed by Indian Roads Congress (IRC) or by the Ministry of Road Transport and Highways (MoRTH).

JP Research’s assessment of the data formats witnessed that the data being collected is barely scratching the surface of the problem. More in-depth data is required to identify, understand and address road safety issues scientifically.

Another problem in data collection is the poor focus on data collection methodologies. Crash data collection, or for that matter any data collection activity, is more about deciding what to collect and why to collect, and then coming up with clear instructions on the methodologies on how to collect the crash data required and ensure uniform interpretation. Technology such as tablets, apps, dashboards, etc. are only tools to make the data collection process efficient.

The importance of well-defined and in-depth crash data goes beyond just reporting number of fatalities, injuries and crashes. Even basic laws and rules mentioned in the Motor Vehicles Act, Central Motor Vehicles Rules, IRC codes, Automotive Industry Standards, etc. need to be constantly monitored for their effectiveness and have to be revised or updated using crash data as evidence. Unless we adopt a data-driven approach right from the central governance level to the road user level, the benefits of datadriven road safety practices will not be realized and we will find it extremely difficult and expensive to arrest and reverse the trend of rising fatalities in India.