Intangles, an AI-powered predictive intelligence company specialising in commercial vehicles, has released an analysis of commercial vehicle performance on the Mumbai-Pune corridor following the opening of the Connecting Link. The findings indicate that improved movement on the corridor could generate potential annual fuel savings of 2.7 crore litres, translating into approximately ₹272 crore in annual fuel cost reduction. The estimated savings could also help avoid nearly 64,905 metric tonnes of CO₂ emissions annually — pointing to the wider economic and environmental value of smoother freight and passenger movement on one of India’s most critical transport corridors.
The analysis tracked 1,849 unique commercial vehicles across four categories — buses, MCV trucks, three-axle vehicles, and multi-axle trucks — covering more than 2,200 trips through the ghat section of the corridor. Performance was compared across two periods: April 26–30, before the Connecting Link opened, and May 2–15, after its opening. Among the categories studied, MCV trucks recorded the highest increase in average speed at 18%, alongside a 19% reduction in travel time and 17% reduction in fuel consumption. Three-axle vehicles saw the highest reduction in travel time at 20%, while buses achieved the strongest improvement in fuel consumption at 24% per trip. Multi-axle trucks also recorded gains across speed, travel time, and fuel use.
Unlike conventional infrastructure assessments that rely on modelled assumptions, Intangles’ analysis drew every fuel figure from actual vehicle sensor streams, processed through terrain-aware algorithms that account for gradient, load behaviour, and real-time driving patterns. The analysis also observed an early reduction in hard braking events across vehicle categories — an initial indication of improved driving conditions on the stretch, though longer-term tracking will be needed before firm safety conclusions can be drawn.
“Fuel is a direct measure of operational efficiency, and on a corridor carrying this volume of freight, even modest per-trip savings compound into material economic impact. What this analysis demonstrates is that vehicle data, collected and processed at scale, can quantify infrastructure value in the terms that actually matter to fleet operators: litres saved, minutes recovered, emissions reduced,” Anup Patil, CEO, Intangles.
“The finding that heavier vehicle categories showed the strongest proportional gains is not intuitive, but it is exactly what the physics predicts. Vehicles most constrained by stop-go conditions on steep gradients benefit most when that constraint is removed. As India’s transport infrastructure expands, this kind of sensor-based measurement framework gives planners, operators, and policymakers something they have not had before: infrastructure ROI expressed in operating terms, not projections,” Hariharan Ravishankar, Chief AI Scientist, Intangles.