Shows cities who pays and who gains before they price roads or parking
TL;DR Roadprice is an analysis service for Indian cities weighing a congestion charge or higher parking fees. It models which households would pay, which would switch to buses or metro and which areas gain, and then tests rebate designs. Urban transport bodies and their consultants pay per study plus a software licence.
Indian cities are inching towards charging for road space with no way to judge whether it's fair. In March 2026, Karnataka's Fifth State Finance Commission recommended a charge on vehicles entering Bengaluru's busiest corridors, likely through FASTag, without proposing amounts[1]. Mumbai's planning authority studied the idea with ITDP back in 2019, when private vehicles made 12% of trips but took up over three-quarters of road space[2].
The objection never changes. A flat charge can push lower-income drivers off roads while wealthier ones pay and carry on[3]. Without numbers on who actually drives into a zone, the debate stays stuck on slogans and proposals stall.
What it does, in regulatory terms: analysis and advice only. Roadprice does not set, collect or enforce any charge, because that needs state or municipal law and a public operator. It handles survey and trip data under the DPDP Act[4].
For a proposed zone or corridor, Roadprice builds a picture of the trips crossing it from traffic counts, household travel surveys, bus and metro ridership and parking records. Then it runs a set of charge designs like a flat entry fee, time-of-day rates or parking-led pricing, and shows by income band and ward who pays, who shifts mode and how much revenue comes in. Rebate options sit on top - bus pass credits, resident allowances and discounts for enrolled low-income owners.
The original version of this idea was road prices that change with each driver's income in real time. No Indian city charges for congestion yet, and a toll gantry can't check anyone's income. Where income-linked relief exists, it runs on enrolment, and New York gives enrolled low-income owners 50% off peak tolls after their first 10 trips a month[5]. Designing that relief well is a job a startup can actually do.
The buyer is a public body, like a unified metropolitan transport authority, a development authority or a state urban development or finance department. The consultancies they hire for mobility plans are an easier first customer, buying the model as a subcontract. Pricing is my assumption - a fixed fee per corridor study and an annual licence for scenario updates.
Bengaluru's finance commission recommendation landed in March 2026, and the Economic Survey 2025-26 also pointed to congestion pricing as a tool for Indian cities[1]. FASTag gives a ready collection channel if a city wants one[1]. New York started its own charge with a phased toll that rises from $9 to $15 for cars by 2031[6], which hands Indian officials a fresh, documented example.
Nobody publishes a figure for spending on congestion or parking-pricing studies in India. The cost of doing nothing is better documented, with a 2018 consulting-firm estimate putting congestion losses in four metros above ₹1.4 lakh crore a year[7]. That's context for why cities might buy, not your market size.
Large transport consultancies run demand models for mobility plans, but equity analysis is usually a chapter rather than a product. One parking-software firm sells to operators and municipalities in 15+ countries, with no distributional modelling[8]. ITDP India does advocacy and studies, including Mumbai's 2019 work[2]. I found no Indian product focused on who pays and who gains from a road or parking charge.
| Difficulty | Moderate (41/100) |
| Starting capital | ₹59 L–1 Cr |
| Time to launch | 6–9 months |
The modelling is well understood. Data and politics are the hard parts. Indian cities rarely have recent household travel surveys with income, so you'll often have to commission one yourself, and then you're selling to bodies where one transfer or election can freeze a project for a year.
No licence is needed for the analysis itself. Setting or collecting a charge needs state or municipal law, and that's the city's job, not yours[2].
Building this outside India? The categories above usually have a local equivalent, so check with your own regulator.
Don't let a model's output stand in for a policy decision. Who pays a road charge is a political and money call, and the assumptions behind every number need a named human owner.
Want to work out the AI layer for Roadprice? Talk to Yash →
Here's what can go south -
I see this as a narrow but credible business for a transport economist or modeller who already knows how Indian mobility plans get commissioned. As a venture-scale bet it is weak, because there just aren't many buyers. Prove one thing first - that a consultancy will pay for a corridor study as part of a live city project.
Plan for roughly ₹59 L–1 Cr, most of it going on modellers, data and the household survey you'll often have to commission yourself.
No. The analysis needs no licence, though you'll need DPDP compliance for survey data and usually a tender or empanelment for public work.
Yes, and the model may travel better than it sells at home. Many cities abroad already price roads or parking. Check local data protection rules for survey data.
The free Roadprice validation kit has the line-by-line capital breakdown, the effort scoring, the data-protection and procurement checklist, a 14-day validation sprint with pass/fail targets, a 90-day launch plan, 10 interview questions for transport officials and consultants, and 5 assumptions to test. Download the kit →
Thinking about building Roadprice or something close to it? The make-or-break bit is finding income-linked travel data good enough that both sides of the debate accept your numbers, and that's the kind of thing I help founders think through. If you need a hand, you know where to find me. Talk to Yash →
For illustration only. Names are fictional and ideas hypothetical; sourced facts are real but may be out of date. Nothing here is legal, financial or professional advice, and Yash Khatri is not personally liable for any use of it. Read the full disclaimer.