India AI Impact Summit 2026

leadership-dialogue-on-ai-in-mobility-accelerating-the-future-of-intelligent-transport

7 min read

TRACK:Economic Growth and Social Good
SPEAKERS
  • Dr Shiv Kumar, ITS India Forum
SESSION OVERVIEW

Leadership Dialogue on AI in Mobility: Accelerating the Future of Intelligent Transport

VIDEO RECORDING

Leadership Dialogue on AI in Mobility: Accelerating the Future of Intelligent Transport

Abstract

The dialogue convened senior leaders from industry, academia, government and the judiciary to examine how artificial intelligence can transform India’s mobility ecosystem—coined “Mobility 5.0”. Participants charted the evolution from “Mobility 1.0” (animal‑drawn transport) to the present “Mobility 4.0” (connected, shared, electric) and argued that AI will embed intelligence into vehicles, infrastructure and the broader transport network. Key themes included road‑safety analytics, congestion mitigation, V2X communications, spectrum allocation, and the need for coordinated policy and implementation to meet the nation’s ambitious safety and sustainability goals.

Detailed Summary

  • ITS India highlighted two preparatory AI summits (IIT Hyderabad & IIT Mumbai) that built the groundwork for today’s leadership dialogue.
  • The session’s purpose: generate concrete recommendations for the AI Impact Summit 2026, focusing on the mobility sector—a government‑designated priority.
  • A striking safety statistic was cited: 1.5‑2 % of vehicles cause ≈12 % of road fatalities in India, underscoring the urgency of AI‑enabled interventions.

2. Defining “Mobility 5.0” – The Evolution Narrative (Moderator)

  • Mobility 1.0 – animal‑drawn carts.
  • Mobility 2.0 – introduction of railways and government‑owned “vacules”.
  • Mobility 3.0 – private vehicle ownership, expanded road network.
  • Mobility 4.0 – connectivity, shared services, electrification.
  • Mobility 5.0 – AI‑infused “intelligent” vehicles, infrastructure and ecosystem.
  • AI will move the system from merely “connected” to truly “intelligent”: vehicles will sense, decide and act autonomously; infrastructure will anticipate demand and respond in real time.

3. Road‑Safety Imperative: Numbers & Challenges

  • Fatalities: 4.8 lakh accidents (2023) → 1.7 lakh deaths, one of the highest global rates.
  • Road‑type contribution: National & State highways (≈50 % of length) account for ≈59 % of deaths.
  • Vehicle‑type contribution: Two‑wheelers (44.8 % of deaths), pedestrians (20.4 %) and cars/taxis (12.4 %).
  • Key risk factors: Over‑speeding (68.68 % of accidents), wrong‑lane travel (5.5 %), hit‑and‑run (18 %), head‑on and side collisions (≈34 % combined).
  • The Supreme Court panel emphasised that electronic enforcement (e‑chalan, auto‑graded licences) and data integration (Transport Dept., CCTNS, IRAC) are essential prerequisites for AI solutions.

4. AI Applications Across the Mobility Value Chain

4.1 Vehicle‑Centric AI (Mr. P. K. Banerjee, SIAM)

  • Concept‑to‑cradle transformation: AI‑driven market‑need analysis shortens product definition cycles, reducing time spent on jigs, fixtures and tooling.
  • Supplier & material optimisation: AI selects lightweight, locally sourced materials, predicts geopolitical risks, and manages vendor compliance via blockchain‑based contracts.
  • Manufacturing & Quality: Industry 4.0 robots guided by AI ensure consistent assembly; AI‑based quality assurance accelerates defect detection.
  • Post‑sale ecosystem: AI powers personalised finance, insurance, and service offers; predictive maintenance and OTA software updates extend vehicle life‑cycle.
  • End‑of‑life recycling: AI helps meet India’s six‑fold “CPR” (Plastic, Rubber, Ferrous, Non‑ferrous, E‑waste, Fluids) recycling targets, improving material recovery rates.

4.2 V2X & Connected‑Vehicle Intelligence (Dr. Puneet Rathod, Qualcomm)

  • Software‑Defined Vehicles: High‑compute platforms host AI models that interpret sensor data beyond line‑of‑sight.
  • Presence‑based communication: Vehicles broadcast their status (speed, intent) within a 500‑600 m radius; roadside units (RSUs) broadcast traffic‑signal phase and congestion data.
  • Intersection safety: Since ~20‑25 % of crashes occur at intersections, V2X enables coordinated signal timing and pre‑emptive alerts to drivers, reducing collision risk.
  • Spectrum needs: 5.9 GHz band earmarked for V2X; coexistence with other services must be harmonised globally (ETSI standards).

4.3 Infrastructure‑Centric AI (Mr. Samik Joshi, MNEX)

  • City‑level corridor optimisation (Surat): Camera‑based vehicle‑type detection feeds a corridor‑wide green‑wave algorithm; emergency vehicles receive dedicated green channels.
  • Highway‑level incident management (Samariti Expressway, Mumbai–Nagpur): 5,000+ AI‑enabled cameras detect stalled/overspeeding/over‑size vehicles, phone‑use violations, and trigger drone‑assisted dispatch and hospital coordination.
  • Multimodal integration (Mumbai): A unified app aggregates 13 transport modes (5 bus operators, 3 railways, 4 metro lines) into a single QR‑code ticket, simplifying last‑mile planning and encouraging modal shift.

4.4 Academic & Research Contributions

  • Fog‑penetration imaging: AI converts hazy camera feeds into clear images, aiding driver visibility in winter fog zones (North India).
  • Crowd‑counting for pilgrimage sites: AI‑driven footfall estimation at Char Dham Yatra enables proactive crowd‑management and safety planning.
  • Smart parking & feeder‑bus coordination (Nainital): AI predicts parking demand, dynamically allocates feeder‑bus capacity, and nudges travelers toward public transport via a convenient mobile interface.

4.5 Policy & Spectrum (Mr. Arun Pallai, DoT)

  • Regulatory roadmap: Allocation of the 5.9 GHz band for V2X (regulated and on‑license sub‑bands) to give industry certainty for ecosystem development.
  • Standards alignment: Adoption of ETSI (European) V2X protocols; ongoing work with TR‑I (Technical Regulations‑India) to finalise signalling specifications.
  • Future connectivity: Vision of a hyper‑connected mobility grid powered by 5G, forthcoming 6G, and LEO/MEO satellite constellations, delivering end‑to‑end low‑latency AI services even in remote corridors.

4.6 Road‑Safety Enforcement & Judicial Perspective (Mr. Sanjay Bandupadhyaji)

  • Data‑driven enforcement: Integration of accident data (IRAT) with CCTNS enables real‑time licence validation, automated penalty issuance and driver‑score tracking.
  • Electronic enforcement (e‑Chalan) gap: Current recovery rate ≈18 %; AI can boost detection, issuance and follow‑up, reducing repeat offences.
  • Pre‑hospital care & “Uberisation” of ambulances: AI‑enabled dispatch, tele‑consultation en route, and real‑time vehicle‑to‑hospital data sharing aim to shrink the “golden hour”.
  • Post‑accident rehabilitation: AI‑driven monitoring of disability benefits and rehabilitation pathways to help victims return to productive life.

4.7 Congestion‑Pricing & Demand Management (Mr. Sonal Ahuja)

  • Road‑space pricing: Proposal for GPS‑based, pay‑as‑you‑go tolling targeting commercial trucks; revenue to fund public‑transport upgrades and intelligent‑traffic‑light systems.
  • CITS (Cooperative Intelligent Transport Systems): Mandatory onboard units for OEMs to enable real‑time traffic‑signal interaction, aiming for a “zero‑crash” target within five years.

4.8 AI‑Driven Traffic‑Signal Optimisation (Mr. Jitin, Onix)

  • Zero‑capital approach: Utilises existing traffic‑signal data streams plus crowd‑sourced vehicle telemetry; AI recalibrates signal phases without additional hardware deployment.
  • Results: Initial pilots report up to 12 % reduction in average stop‑time and smoother corridor flow.

5. Audience Q&A – Highlights

QuestionSpeaker(s) RespondingCore Insight
Near‑miss detection – how to act before accidents happen?Mr. Samik JoshiAI can flag hotspots by analysing near‑miss telemetry, enabling pre‑emptive engineering or enforcement actions.
Driving‑licence quality – can AI improve testing & monitoring?Mr. Bandupadhyaji & DoT representativeAutomated theory & practical tests are being piloted; driver‑monitoring cameras will generate real‑time licence‑score updates.
Hardware vs. software solution for collision‑avoidance – OEM vs. aftermarket?Mr. Banerjee & Mr. JitinOEM integration gives fastest rollout, but AI‑enabled aftermarket kits (e.g., camera‑based V2X modules) can bridge the gap for existing fleets.
Spectrum harmonisation – is 5.9 GHz globally aligned?Mr. PallaiYes; India’s allocation mirrors US/EU V2X bands, facilitating cross‑border OEM adoption.
Implementation timeline for V2X – regulatory hurdles?Dr. RathodCurrent pending approvals expected within 12‑18 months; once spectrum is finalised, OTA updates will enable rapid deployment.

6. Closing Remarks & Recommendations (Dr. Shiv Kumar)

  • The panel agreed on a set of immediate actions:

    1. Finalize 5.9 GHz V2X spectrum allocation and publish technical specifications within the next quarter.
    2. Launch a national AI‑based accident‑data platform (linking IRAT, CCTNS, transport databases) to fuel enforcement and research.
    3. Mandate CITS‑ready onboard units for all new vehicle registrations, with an aftermarket retrofit incentive for existing fleets.
    4. Deploy AI‑driven corridor‑green‑wave pilots in at least three major cities (Surat, Mumbai, Delhi) and evaluate impact on congestion and emissions.
    5. Scale electronic enforcement (e‑chalan, automated licence checks) using AI‑powered camera networks on national highways.
    6. Integrate multimodal ticketing into a single national mobility app, leveraging AI for journey‑optimisation and demand‑management.

  • A report summarising the dialogue and detailed recommendations will be submitted to the AI Impact Summit 2026 organising committee within a few days, with OMI and ITS India serving as technical consultants.

Key Takeaways

  • Mobility 5.0 will be defined by AI‑enabled intelligence in vehicles, infrastructure and the whole transport ecosystem, moving beyond mere connectivity.
  • Road‑safety is the most compelling use‑case: AI can cut the disproportionate 12 % fatality share caused by only 1.5‑2 % of vehicles.
  • V2X communications (5.9 GHz band) are the backbone for intersection safety, cooperative traffic‑signal control and emergency‑vehicle priority.
  • Government policy is aligning – DoT is allocating spectrum, adopting ETSI standards, and the Supreme Court is pushing electronic enforcement and data integration.
  • AI can dramatically improve congestion through corridor‑wide signal optimisation, GPS‑based road‑space pricing, and unified multimodal ticketing.
  • Full‑vehicle life‑cycle AI (from concept, design, supplier selection, manufacturing, post‑sale service to recycling) promises faster product development and higher sustainability.
  • Data‑centric enforcement (e‑chalan, licence‑score, driver‑monitoring) will close the gap between detection and prosecution, enhancing compliance.
  • Public‑private‑academic collaboration is already delivering pilots (Surat camera‑based green‑wave, Samariti Expressway incident AI, fog‑penetration imaging) that can be scaled nationally.
  • Immediate next steps include finalising spectrum allocation, launching a unified accident‑data platform, mandating CITS‑ready units, and piloting AI‑driven corridor optimisation in major metros.

These points capture the consensus and actionable roadmap that emerged from the Leadership Dialogue on AI in Mobility.

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