Car wash wait time after a snowstorm: how to measure the line and staff the next salt day

To measure car wash wait time after a snowstorm, count three things by the hour: cars joining the line, cars entering the tunnel, and cars that pull in and leave. Your stacking-lane cameras can count all three. Wait time is then the number of cars in line divided by the cars per hour you're actually washing, and the gap between cars that joined and cars that washed is the revenue you lost to the line.

Most operators know the first sunny day after a storm is their biggest day. Few know how long the line really got, how many cars gave up, or whether the tunnel ran at full speed all day. This post is a method for getting those numbers from cameras you already have, an example hour-by-hour table, and a salt-day checklist you can use for the next storm.

Quick answer

• Count by the hour: cars joining the line, cars entering the tunnel, cars leaving the line without washing.
• Wait time: cars in line ÷ cars washed per hour. 30 cars in line at 60 cars an hour is about a 30-minute wait.
• Lost cars: cars that joined or pulled in but never reached the pay station.
• Staffing: staff to the hours where the line was longest last storm, not to the day total.
• Start with: the hour-by-hour table below for your last storm day.

How busy does a car wash get after a snowstorm?

Busier than any other day, and the published numbers are mostly managers' estimates. An Evansville, Indiana manager told 14 News in January 2025 that the site averages "about 400 cars a day, but after snow the number jumps up to 700." A Hamden, Connecticut site told WTNH in February 2026 it averages "over 400 cars per day." In 2018, a Nashville tunnel manager told NewsChannel 5 the site could do "as many as 111 cars every hour" and that its record hour was 102 cars.

Those are useful for scale but they don't tell you what happened at your site. A day total of 700 can hide two hours where the line stretched onto the road and a lot of drivers gave up. That's why the hour, not the day, is the unit to measure.

Why can't the POS tell you your car wash wait time?

The POS only sees cars that paid. It can't see:

• cars that joined the line and left before the pay station,
• cars that turned in, saw the line and drove off,
• how long each paying car waited,
• the minutes the tunnel was stopped or running below full speed.

Cameras on the entrance and the stacking lanes see all of that. Most sites already have them for security and damage claims. Nobody is counting with them.

How do you measure car wash line length and wait time with cameras?

You need three counting zones, set up once per site:

1. Entrance zone: cars turning into the lot.
2. Line zone: the stacking lanes before the pay station or loader.
3. Tunnel entry zone: cars actually entering the wash.

Then, for every hour:

If your cameras can't follow a single car from line to tunnel, use the queueing rule known as Little's law instead: average wait ≈ average cars in line ÷ cars washed per hour. With 30 cars in line and 60 cars washed an hour, the average wait is about half an hour.

Then put the camera counts next to your POS sales by hour. If the tunnel camera counted 62 cars and the POS shows 55 washes, you have seven cars to explain: re-washes, free washes for complaints, staff cars, or washes that weren't rung up. That gap is worth watching on every busy day, not just storm days. We cover it in more detail in car count vs tickets.

Example: one salt day, hour by hour (made-up numbers, not real store data)

A tunnel site on the first sunny day after a storm. The day total looks great. The hours tell a different story.

Est. wait is average line ÷ cars washed per hour × 60. Walk-aways are cars that entered the lot or line and left without reaching tunnel entry. In any hour, cars in = cars washed + walk-aways + the change in the line, and by 4 p.m. the line is empty, so the totals tie out: 537 = 459 + 78.

What the table shows that the day total doesn't:

• The tunnel dropped to 50 cars from 11 to 12. Every other busy hour ran at 62–64. Something slowed it: a stop, a slow loader, a pay station issue. That one hour cost about 14 washes at normal speed, and the line never recovered until 2 p.m.
• The line peaked at 11–1. That's where the extra staff should go, not spread across the whole day.
• 78 cars left. At a made-up $15 average wash, that's about $1,170 in a day. Put your own average in.

What should you change before the next salt day?

Look at three things from the last storm:

1. Your real cars per hour at full speed. Use the best full hour, not the brochure number. In the example, 64.
2. Hours where cars washed fell below that. Each one needs a reason: a stop, a staffing gap, a pay station queue.
3. The hour the line passed the point where people leave. In the example, walk-aways jumped once the wait passed about 25 minutes. That's your line limit for this site.

Salt-day checklist

The day before (forecast says sun after snow):

• Text the on-call list. Payroll vendor Netchex suggests an on-call roster of three to six people you can text the night before.
• Put extra people on the hours where last storm's line was longest, not on opening.
• Check chemicals, especially presoak and undercarriage, and any spares that stopped you last time.
• Check the tunnel and lot heaters. The Hamden manager told WTNH heaters keep water from freezing in the tunnel.
• Decide who watches the line camera and what number of cars triggers action (a second loader, a staff member walking the line, opening another pay lane).

During the day:

• Check cars washed per hour every hour against your full-speed number.
• If an hour falls short, find out why right away. A slow hour at 11 a.m. pushes the line into the afternoon.
• Watch walk-aways. If they climb, move people to the pay lanes and loading.

The day after:

• Fill in the hour-by-hour table above.
• Write down the cause of every slow hour.
• Update the on-call plan for next time.

How do you compare salt days across several sites?

Put each site's best full hour, its slowest busy hour, peak line, and walk-aways side by side the morning after. One site at 64 cars an hour and another at 48 with the same tunnel length is a staffing or equipment question you can answer that week. The car wash KPIs by location page has the full list of by-site measures and how to set a target per site, and car wash equipment monitoring covers catching the stops that slow a tunnel down.

How Trilix fits

We build camera analytics on top of the cameras your sites already have. For car washes, that means cars in, cars washed, line length, wait time and walk-aways counted by hour at every site, matched against your POS sales, and shown each morning on one owner dashboard. It sits on top of your POS rather than replacing it. More on what camera AI can track at a wash in our car wash camera AI guide.