Making Roads Safer

With the use of AI & hyperlocal data

About Safar

SAFAR (Safe, Accessible Future using AI on Roads) uses road accident data to analyse the reasons for accidents and provides insights at a hyperlocal level to make our roads safer. Safar also allows policymakers and planners to simulate planned safety interventions, gauging their potential impact before taking suitable action.

Safar Labs

The Safar Labs is an AI/ML engine that conducts root-cause analysis of road accidents at the hyperlocal level (street, neighbourhood levels), and recommends hyperlocal policy and regulatory action. Safar Labs has three main components:

Safar View

A map-based interface which shows statistics, time-series and spatial analysis of different types of traffic accidents.

Safar Cause

Using machine-learning based analysis and classification using Decision Trees or Random Forests, we provide causal attribution and severity prediction.

Safar Sim

By interfacing with a traffic simulation engine such as MATSIM or VISSIM, policymakers and urban planners can choose various interventions at specific accident-prone sites and see the effects of such simulation.

Solution Process

STAGE 1

Data collection:

Accidents data, FIRs, Medical records, Video feeds, etc. at the hyperlocal level
STAGE 2

Data Analysis & Software Development:

Data analytics and pattern mining, Traffic Microsimulations to create counterfactual data, Predictive modelling
STAGE 3

Policy Insights Generation:

Analysis of policy interventions in India, Japan, USA, among others, Microsimulations: accurate exploratory analysis of road safety issues, Recommend policy interventions at the hyperlocal (street/ locality) level

Making our Roads Safer

For Policy Makers

For Road Users

For Nodal Agencies and Researchers

Road accidents are a multi-causal issue and therefore, there’s no one-size-fits-all response possible. City authorities need to implement interventions in a prioritised manner at a hyperlocal level. Using hyperlocal data and machine learning algorithms, we enable policy stakeholders to understand causes of accidents at a local level and simulate interventions in a localiszed fashion to get the maximum benefit. Multiple stakeholders, involved at the city level, can benefit. This includes Smart City CEOs and officials, Collectors, Mayors, Municipal Ward Commissioners, Unified Metropolitan Transport Authority (UMTA) CEO and officials, Transport department, Regional Transport Offices, Traffic Police department, Law and order Police department, Health department and Hospitals, among others. In addition state governments, transport commissionerate, road transport ministry can also benefit from policy interventions that will be possible.

The accident to fatality ratio in India is very high. Road users - especially pedestrians and cyclists - are often the casualties. Understanding accident hot spots at a local level will increase awareness among citizens, and help them take corrective actions at such accident prone spots.

Our rich data set at a localized level can help researchers build on that for traffic planning, legislation and education. It will also enable creating a standardized data set and data dictionary for road safety.

This could benefit academic institutions, or mobility institutes or agencies including Smart Cities missions, multilateral agencies, and others.

Case Study

Analysis of Accidents in Purba Bardhaman district, West Bengal

Accidents in the period 2018-2021 were analysed in East Bardhaman district to identify hot spots...

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Team involved in Making our Roads Safer

Aishwarya Raman

Executive Director, OMI Foundation

Aishwarya holds an M.SC in Sociology from University of Oxford, and has 10+ years of professional experience in the mobility domain. She is a member of the Global Future Council on Urban Mobility Transitions at the World Economic Forum, a Salzburg Global Fellow, and advises and mentors organisations, researchers, and young professionals, including the Global Partnership for Informal Transportation, Young Leaders for Active Citizenship, among others. She was a mobility entrepreneur and an academic in her previous avatar.

Dr Adway Mitra

Asst Professor, Centre of Excellence in Artificial Intelligence, IIT Kharagpur

Dr Adway holds a Phd in the field of machine learning from Indian Institute of Science (IISc), Bangalore. He has 6+ years of experience in the application of Machine Learning (ML) and Data Science (DS) to different scientific disciplines. As a faculty member at IIT Kharagpur, Dr Adway designs new course materials to train undergraduate, postgraduate and doctoral research students about theoretical and applied aspects of AI/ML/DS in various domains such as Earth Sciences and Economics.

Akhilesh Srivastava

Project Lead - Road Safety 2.0, World Economic Forum, Former Board Member and Chief General Manager, National Highways Authority of India

Akhilesh is a globally recognised digital and innovation leader. He has successfully led many e-governance projects in India like FASTag (electronic toll collection system of India), e-Tendering platform (Central Public Procurement Portal used by almost all central, state governments and PSUs for procurement), e-Measuring Book (for transparent measurement of the project under execution), multiple citizen-centric highway information mobile apps, Geo-fencing of national highways, and next-gen AI-powered NHAI Data Lake. He currently leads the Road Safety 2.0 initiative of the World Economic Forum. He was formerly the Chief General Manager and Board Member of the National Highways Authority of India.

Supported By

Salzburg Global Seminar

Salzburg Global Seminar is an independent non-profit organization founded in 1947 with a mission to challenge current and future leaders to shape a better world.
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Japan India Transformative Technology Network

The Japan India Transformative Technology Network, launched in 2020 by Salzburg Global Seminar and The Nippon Foundation, connects tech entrepreneurs from India and Japan to foster collaborations and surface creative ideas to use tech and artificial intelligence as a force for good, solving some of the pressing challenges of today: mobility, equity and access, economic development. The founders—Aishwarya and Adway are Salzburg Global Fellows participating in the JITTN fellowship programme.
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