Counting cars over time: what road traffic history shows
Hourly car counts on the road nearest a site, going back to 2021, in the United Arab Emirates: what they reveal, how to read them, and what to use elsewhere.
Road traffic history counts the cars that pass on the road nearest a place, in both directions, hour by hour, with their average speed. In xMap Flows it is a Regional data dataset for the United Arab Emirates, reaching back to January 2021, and it turns into cars a day, the busiest hour and day, the slowest hour, the split by direction and the recent trend. Outside the United Arab Emirates there are no car counts: only live speeds and congestion, measured when a flow runs.
This article is for property, retail and outdoor advertising teams working in Dubai, Abu Dhabi, Sharjah and the other emirates, and for anyone elsewhere who wonders why their country has speeds but no counts. It covers what the dataset holds, how to read a count, why months of history beat a single reading, and the traps of the nearest road.
What the dataset holds
Pick United Arab Emirates and Road traffic history in the Regional data block. For each place that reaches it, the block finds the nearest measured road and reads its hours over the period you choose: the last 7, 30 or 90 days, the last 12 months, everything since January 2021, or your own first and last day. You can keep every day, weekdays only, or weekends (Saturday and Sunday).
It can give one row of totals for each place, or one row a month, a day or an hour per place, up to 5,000 rows a run. The totals carry these fields:
| Field | What it says |
|---|---|
| road_name, road_class, road_m | The road measured, its kind, and how far it is from the place |
| cars_per_day, cars_total | Average cars a day (both directions) and the total over the period |
| cars_peak_hour, cars_peak_hour_avg | The busiest hour, local time, and its average count |
| avg_speed_kmh, peak_speed_kmh | Average speed, and the speed in the busiest hour |
| slowest_hour, slowest_speed_kmh | When the road crawls, and how slowly |
| busiest_day, quietest_day | The days of the week with most and fewest cars |
| cars_trend_pct | The last 30 days against the 30 before |
| cars_by_direction | Cars a day in each direction |
| traffic_days, traffic_from, traffic_to | The days with data and the first and last of them |
Fields of the totals for each place in Road traffic history.
Reading a count
Cars a day is a volume: how many vehicles passed, whatever their speed. Read it with the peak hour and the direction split. A made-up example: two candidate kiosks in Dubai read 30,000 and 26,000 cars a day. The first looks better, until the direction split shows most of its morning traffic heading away from the business district, past the side of the road the kiosk is not on. The second carries its busiest hour inbound, on the kiosk's side. For a morning coffee stop, the smaller number may be the better site.
Speed adds the other half. The peak hour's speed compared with the day's average shows how much the road slows at the rush; a slowest hour well below the average tells a drive-through when queues on the road may stop customers turning in.
Why months beat a single reading
Traffic changes with the seasons, school terms, holidays and new roads. A week in summer can look nothing like a week in the cooler months. With history you can:
- Compare like with like: the same month this year and last year, or weekdays only.
- See a road change: a month-by-month series shows the step when a new interchange or metro line opened.
- Show an advertiser the trend: a billboard owner can chart cars a month since 2021 instead of quoting one number.
- Spot a temporary dip: roadworks that cut traffic for six weeks will not mislead a decision taken on twelve months.
When the nearest road is the wrong road
The dataset measures the road nearest the place, and the place is often set back from it. A mall entrance may sit beside a quiet service road while the motorway it overlooks carries the traffic. Always check road_name and road_m: if the road measured is not the one your sign faces, move the point to the frontage before you trust the count.
Everywhere else: live speeds over time
Outside the United Arab Emirates, the Traffic Flow block measures speed, free-flow speed and the jam factor around each place at the moment a flow runs. It does not count cars. To build a history of your own, schedule it at the same hours every weekday and keep each reading in a sheet: after a few weeks you have each site's typical morning and evening speeds. That is a record of how the road moves, not how many cars use it, and it should be read that way.
A traffic history report with an AI employee
- Upload your shortlisted sites in the emirates to My data, each placed on the road it faces.
- Add Regional data: United Arab Emirates, Road traffic history, the last 12 months, totals for each place.
- Add Sort and limit to put the most cars a day first.
- Add Make a report for a PDF the expansion committee can read, or an email.
- For a billboard, use since January 2021, month by month, and Slides, on a Schedule on the first day of each month.
The committee gets each site's cars a day, busiest hour, rush-hour speed and trend side by side, with the road each figure was measured on, so nobody mistakes a service road for the main one.
Questions
Which countries have car counts?
Only the United Arab Emirates, through the Road traffic history dataset in Regional data. Elsewhere there are live speeds and congestion through Traffic Flow, without counts.
How far back do the counts go?
The dataset reaches back to January 2021. Each place says which days had data in traffic_days, traffic_from and traffic_to.
Are both directions counted?
Yes. cars_per_day counts both directions, and cars_by_direction splits them.
Can I get hour-by-hour rows?
Yes. Set it to give one row an hour, a day or a month per place, up to 5,000 rows a run.