Traffic counting methods compared: tube, radar, camera or LiDAR?
Every method counts vehicles. They differ in what else they see, how long they last, what they cost to move, and what they mean for privacy in a public street. Here is the honest comparison.
Ask three suppliers how to count traffic and you will get three answers that happen to match their hardware. This guide compares the four method families on their own merits, what each actually measures, where each fails, and what each means for privacy in a public street, so you can choose on your requirements instead of a vendor’s catalogue.
Pneumatic tubes: the proven sample
The classic short-term count: rubber tubes across the lane, axle pulses in, a report out. Tubes are inexpensive, familiar to every traffic department, and fine for a one-off answer on a free-flowing road. Their limits are structural: they deliver a sample of a week or two rather than a continuous series, they wear and detach, accuracy drops in queues and at low speeds, and they are blind to pavements and cycle paths. A tube count from one September week becomes the truth about a street for years, because repeating it costs money every time.
Radar: robust presence and speed
Radar sensors survive weather and darkness, need little maintenance, and measure vehicle presence and speed reliably on flowing roads, which is why they run permanent motorway stations. In dense urban scenes their picture narrows: mixed and crossing movement, queues, and the pedestrian-and-cyclist layer of a street are not what they were built to describe. Privacy is a non-issue, nothing resembling identity is captured.
Cameras with built-in counting: rich scenes, optical baggage
Modern AI cameras count in the camera and output numbers, not footage; in counting mode no personal images are stored. They read complex scenes well and reuse a hardware family many organisations already run. Two things temper them in public streets: lighting still shapes optical performance at night and in glare, and a camera pointed at a public street carries a surveillance perception, and a compliance conversation, that pure measurement hardware avoids. Inside a site, at entrances and service points, AI camera counting is often exactly right.
LiDAR: the continuous series, with privacy by physics
LiDAR sweeps the street with eye-safe laser pulses and measures moving geometry: position, size, direction, speed of movement, in any light, with no image ever existing. That combination fits urban measurement unusually well. One installation counts continuously rather than sampling, separates vehicles from cyclists and pedestrians in the same scene, and walks into a privacy review with nothing to explain, because nothing about anyone was ever captured. It is newer than tubes and radar, and the hardware is not the cheapest per point, but per answered question, a continuous multi-class series usually beats a stack of single-purpose samples.
Choosing: match the method to the question
A short-term, single-road, vehicles-only question is still a fair job for a tube. A permanent speed-and-flow station on open road suits radar. The moment the question involves a street rather than a road, mixed movement rather than vehicles alone, continuity rather than samples, or a privacy-sensitive public setting, laser-based measurement earns its place. And the methods mix: traffic counting from Bumbee Labs is designed per site, drawing on LiDAR and AI cameras where each is strongest, delivered in the same platform as pedestrian and bicycle data, from the company behind the only footfall method in Europe approved by a data protection authority.
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Frequently asked questions
What is the most common way to count traffic?
Pneumatic tubes remain the workhorse for short-term road counts: two rubber tubes across the lane, counting axle pulses for a week or two. They are cheap and proven, but they are samples, not series, they wear out, they struggle with slow or queueing traffic, and they say nothing about pedestrians or cyclists on the same street.
When is radar the right choice?
Radar suits permanent, weather-exposed installations focused on vehicle presence and speed on flowing roads. It is robust and privacy-neutral, but gives a narrower picture in complex urban environments with mixed movement, queues and crossing flows.
What does LiDAR add over cameras for traffic counting?
Both see complex scenes, but LiDAR measures geometry with laser light and never produces an image, so there is no footage to store, mask or justify in a public street. It also works identically in darkness and glare. Cameras with built-in counting output numbers rather than footage in counting mode, but the optical hardware itself carries a surveillance perception that matters in public space.
Can one system count vehicles, cyclists and pedestrians together?
Yes, that is where modern sensors overtake single-purpose equipment. A LiDAR deployment can be configured to separate movement classes, so one street reports vehicles, cyclists and pedestrians as distinct series in one dashboard, which is exactly what mixed-use urban planning questions need.