Project SAFAR aims to identify the leading causes of road accidents and fatalities in India and suggest hyper-local policy changes to bring down these incidents.
In most cities of India, policy decisions on road safety are taken at a city-wide level, typically with a one-size-fits-all approach. On the other hand, road safety is a hyperlocal challenge. For example, while one part of a city might require immediate engineering and road design fixes, another city might need ready access to hospitals and enhanced citizen awareness on safe road behavior. A lack of hyperlocal or street-level approach renders road safety efforts by the government less effective than ideal.
Thus, a localized approach leveraging big data and artificial intelligence (AI) is needed to enhance road safety in India. The project involves the creation of SAFAR Labs – an AI engine that conducts root-cause analysis at the hyperlocal level and recommends hyperlocal policy and regulatory actions. Upon successful development, the long-term goal is to suggest policy interventions while analyzing traffic management systems and road safety scenarios in-depth.
Team members will have different responsibilities. Aishwarya Raman will contribute to the building of the AI engine and handle partnerships and fundraising. Adway Mitra will be responsible for data analytics, AI engine development, and software implementation. Mahesh Devnani will study health aspects of road safety and data analysis. The main challenge of this project pertains to securing data. The project will ultimately benefit citizens, road users, and government authorities in India and reduce road accidents and fatalities.
While there is much research on road accidents in India, this project specifically aims to identify causal factors behind individual incidents. It will also use traffic microsimulations to generate counterfactual data for analysis. Additionally, the proposed engine will predict the severity of injuries in different scenarios and suggest road safety interventions at the hyperlocal level. This is a one-year project with four phases:
For more information, please visit safarlabs.org
Starting in 2020, Fellows of the Japan-India Transformative Technology Network formed several small teams as they discovered common interests and shared challenges. These teams then concentrated their efforts on designing a potential solution to a challenge they face in their professional or personal lives. Having refined these solution ideas with their colleagues in the Network and several external resource specialists, Salzburg Global is supporting select teams to take their project ideas to key stakeholders who can help make them a reality.
If you are interested in working with this project group in any way, please email Jennifer Dunn (jdunn@SalzburgGlobal.org) with your statement of interest.