Bus Lane or Congestion Charge
A mid-sized city's transport department has 18 months and a budget of ₹40 crore to cut peak-hour car trips by 15%. Consultants offer two options. Option A: a dedicated bus lane on the 12 km arterial road plus 60 new buses, modelled to cut car trips by 11% at a cost of ₹32 crore - but the lane takes one of three car lanes, and the model assumes this will not push drivers back into their cars. Option B: a ₹60 congestion charge at eight entry points, projected at 16% reduction for ₹9 crore, but a neighbouring city saw retail footfall fall 22% in its first year, and the state government has vetoed two similar proposals. A residents' survey shows 58% support for bus lanes and 31% for the charge; the chamber of commerce opposes both.
1. If the department must choose one option, which should it recommend, and what is the strongest argument against your own choice?
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Recommend Option A, but honestly framed as an 11% measure inside a 15% target rather than as a 15% measure.
The decisive factor is deliverability, not modelled effect. Option B's 16% is a projection for a policy the state government has already rejected twice; a proposal that cannot be approved delivers 0%, and the department has 18 months, not a mandate. Option A sits inside the approved budget, has 58% resident support against 31%, and its buses can be procured within the window. Expected value favours the option that survives the political filter.
Strongest argument against this choice: A does not meet the brief. The department was asked for 15% and is recommending 11% - a 27% shortfall against target - and its central modelling assumption is exactly the one that could fail. Removing one of three car lanes may choke the corridor so badly that drivers divert onto parallel roads or back into cars, in which case even the 11% evaporates and the department has spent ₹32 crore to make traffic worse. B, by contrast, is cheaper, stronger on the model, and its main risk (retail footfall) is a distributional problem that can be handled with exemptions and revenue recycling - not a reason to abandon a working instrument.
2. Identify the assumption in Option A's model that most needs testing, and describe a cheap way to test it within 90 days.
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The assumption: that converting one of three car lanes to a bus lane will not reduce general-traffic capacity enough to deter car users - that the lane loss does not itself cause the congestion that pushes drivers back into their cars (or onto parallel roads).
This is the load-bearing assumption, because the 11% figure is produced by a model in which buses get faster while cars are assumed to be largely unaffected. Take the lane away and the arithmetic changes on both sides of the ledger.
A 90-day test: mark a 2–3 km section of the corridor with cones and paint for a four-week temporary bus lane, then compare it with a matched control section of the same road. Measure four things, before and after: corridor travel time for cars and for buses, queue length at the two worst junctions, cordon counts of cars entering the corridor, and counts of diverted cars on the nearest parallel street. Two enumerators plus video counts and cones cost a small fraction of ₹32 crore and would test the assumption directly.
If cars divert rather than disappear, the bus lane is not delivering mode shift; it is redistributing congestion, and the model needs rewriting before ₹32 crore is committed.
3. The mayor wants to announce the 15% target as a guaranteed outcome. Explain why this is risky and what should be promised instead.
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Why it is risky: the 15% figure is the output of a model whose assumptions are untested, and the actual outcome depends on things the department does not control - fuel prices, whether the metro opens on schedule, school and office timings, enforcement of the lane, and the state government's stance on the charge. A public guarantee converts an estimate into a political liability: if the reduction reaches only 8%, the mayor owns a failure that a properly framed target would have absorbed as a mid-course correction. Announcing a number that the department's own consultants do not support also invites the obvious question of why Option A models only 11%.
Promise instead a measurable commitment:
- Publish the baseline cordon counts before the lane opens.
- Publish car and bus counts monthly, on a stated date, so nobody can dispute the trend later.
- Pre-commit to a review at 6 and 12 months with a named trigger - for example, if the reduction is under 8% at 6 months, feeder buses and a parking levy are added.
This gives the public a number to hold the department to without converting a projection into a promise. Accountability comes from publishing the baseline and the trigger, not from the size of the announced figure.