Artificial Intelligence in India’s Intelligent Transportation Systems: Driving the Next Mobility Revolution

India’s urban transformation is unprecedented. By 2047, over 600 million citizens will reside in urban regions, and vehicle ownership is expected to triple. What India needs now is intelligent infrastructure with Artificial Intelligence integrated into Intelligent Transportation Systems. AI offers capabilities far beyond automation: predictive analysis, real-time adaptive systems, and the ability to learn from urban mobility patterns. AI is not merely an addition to traffic systems—it is the command centre for India’s next-gen mobility, writes Akhilesh Srivastava, President, ITS India Forum and IRF India.

Artificial Intelligence is no longer optional in urban transport—it is foundational. Its ability to synthesize data, make instant decisions, and predict system-wide outcomes makes it indispensable for India’s

mobility future.

– Akhilesh Srivastava

The Indian ITS market, as per the ITS India Forum Market Report (2025), is projected to grow at a CAGR of 14.79% between 2024 and 2035. AI-led systems such as Advanced Traffic Management Systems (ATMS), Vehicle-to-Everything (V2X), and AI-powered surveillance will be leading this growth.

Real-World AI Applications in ITS

In India, AI is already enhancing urban mobility outcomes across various areas. In cities like Pune and Bengaluru, AI-based Adaptive Traffic Signal Control (ATSC) systems have reduced travel times up to 25% on selected routes. The Video Incident Detection and Enforcement System (VIDES) deployed by NHAI detects up to 14 different traffic violations in real time, ranging from animals on the roads to stalled vehicles.

With the ITS India Forum, Delhi’s public transport body, DIMTS, utilizes AI to optimize bus fleet rotation and predict delays, enhancing punctuality and the overall commuter experience. In toll management, AI is now employed to detect fraudulent vehicle IDs and evasive driving behaviours with over 95% accuracy, thus improving revenue collection and transparency.

Even environmental benefits are measurable. In Ahmedabad, AI-enabled traffic routing has led to an 11% reduction in CO2 emissions by guiding vehicles away from congested corridors.

The Policy and Regulatory Landscape

India’s AI integration in ITS is supported by an evolving multi-tiered policy framework. The National Strategy on AI (2018) identified mobility as a priority sector. The Smart Cities Mission encourages the adoption of AI-enabled surveillance and transport analytics. Legal provisions under the Motor Vehicles (Amendment) Act, 2019, authorize AI-generated digital evidence.

In 2023, MoRTH published ATMS standards that formally required AI-based real-time traffic monitoring systems. Additionally, the National Clean Air Program (NCAP) has prioritized AI-driven ITS tools in high-pollution urban areas. Together, these policies are creating a fertile environment for the scaled adoption of AI in mobility.

Enabling Conditions for Scaled AI Adoption

To mainstream AI in ITS, India needs both technology and institutional enablers:

Data Infrastructure

• Establish an Open Mobility Data Exchange under the NIC, BIS, or MeitY.
• Mandate standardized APIs for vehicle OEMs, Infra Operators, and ITS vendors.

Edge AI Deployment

• Enable on-device AI computation at traffic lights, intersections, and toll plazas to reduce bandwidth latency.

Mobility AI Sandboxes

• Designate five cities like Delhi, Pune, Indore, Hyderabad, and Kochi as testing zones for AI pilots under regulatory relaxation.

Capacity Building

• Create a pool of at least 10,000 ITS professionals trained in AI applications by 2030 through the ITS India Forum’s capacity-building programs, IITs, NITs, and NIC-accredited programs.

AI Governance & Ethics

• MoRTH should collaborate with MeitY and NITI Aayog to develop a Code of Ethics for AI decision-making in mobility.

Challenges and Strategic Enablers

Despite positive momentum, India’s AI-ITS journey faces structural gaps that need to be addressed with urgency.

AI requires vast, clean, and standardized datasets. At present, traffic data across cities is fragmented. Establishing an Open Mobility Data Exchange under the NIC, BIS, or MeitY would enable developers, agencies, and startups to build scalable, interoperable AI models.

Infrastructure constraints are another barrier. To reduce latency and improve real-time accuracy, AI computation needs to shift toward the edge on traffic poles, signal boxes, and toll plazas. Infrastructure operators need to be fully integrated into the AI-enabled system.

Human resource development is equally crucial. By 2030, India will require at least 10,000 trained AI-for-Mobility professionals working within urban local bodies, state transport departments, and municipal command centers.

Finally, AI systems must operate within an ethical and legal framework. Given the use of facial recognition, license plate tracking, and behavioural data, India must develop privacy-first AI governance protocols specific to transport.

Public-Private Partnerships and Innovation Push

Private sector innovation is thriving. Companies like Netradyne and Awiros are building AI platforms for traffic analytics, and telecom giants like Jio and Airtel are investing in cloud-backed mobility AI solutions.

Public-private collaborations are delivering results. In Pune’s smart corridor, real-time data from private ITS firms is now integrated into the city’s Integrated Command and Control Center (ICCC), improving emergency response and route optimization.

A dedicated AI Mobility Innovation Fund worth `1,000 crore could catalyze broader deployment across India’s Tier 2 and Tier 3 cities. Additionally, India can benefit from bilateral AI partnerships—such as with Japan’s UTMS, which offers AI traffic forecasting models already tested in dense megacities.

Toward a National AI for Mobility Mission

India must now establish a National AI for Mobility Mission (NAIMM) under the PM Gati Shakti framework. This mission should unify AI deployment across public transit, highways, tolling, and safety systems, backed by R&D funding, standardization, and outcome-based governance.

By 2030, India must aim to:

• Integrate AI-based ITMS or ATMS in 100 cities
• Reduce urban travel times by 30%
• Cut transport-related fatalities by 50%
• Lower road emissions by 30%

By embedding intelligence at the heart of mobility, India has the opportunity to move faster, smarter, greener, and safer.

References: ITS India Market Report (2025) – Transparency Market Research; Ministry of Road Transport and Highways, 2023 – ATMS Guidelines; NITI Aayog – National Strategy for Artificial Intelligence, 2018; Smart Cities Mission Toolkit – MoHUA; National Clean Air Programme (NCAP) Guideline; Delhi Integrated Multi-Modal Transit System (DIMTS); Pune Municipal Corporation – Smart Traffic Control Pilot