Whether redesigning an intersection, planning new cycling facilities, or optimizing traffic light phases, almost every traffic planning measure begins with a reliable data foundation. Today, simply counting the number of vehicles is no longer enough. Detailed information about traffic flows, speeds, vehicle types, and the interaction of all road users is required.
With the increasing diversity on the roads, the demands on data collection are also rising. Alongside cars and trucks, bicycles, e-scooters, and pedestrians shape the traffic environment. At the same time, measures should not only improve traffic flow but also increase safety and contribute to sustainable mobility planning in the long term. Modern traffic data collection must therefore achieve more than a classic count – and this is exactly where LiDAR traffic counting comes in.
What Information Does Modern Traffic Counting Provide?
A contemporary traffic data collection system maps the entire traffic environment and creates a solid foundation for analysis and planning processes. Depending on the use case, the following data can be recorded:
- Traffic volume and traffic flow
- Vehicle classification according to defined standards
- Speed distributions
- Directions of travel and turning movements
- Traffic jam detection
- Movements of cars, trucks, bicycles, pedestrians, and other vulnerable road users
This information enables not only the evaluation of current traffic volumes but also provides insights into actual mobility behavior and the use of existing infrastructure.
Traffic Monitoring Compared: Which Technology Suits Which Application?
Various technologies have been used for traffic data collection for many years, each with its specific advantages and disadvantages. Inductive loops and pneumatic road tubes are often used for classic traffic counts and provide reliable data on pure traffic volume. However, the installation of inductive loops requires extensive road construction work. Furthermore, they provide a rather reduced data set: while they can count vehicles, they often classify them inaccurately. Another significant blind spot is that pedestrians and cyclists outside the lane cannot be detected at all using this method.
Radar sensors additionally record speeds and enable reliable vehicle classification, but often reach their limits when it comes to precisely separating vehicles driving closely together or detecting vulnerable road users. Camera-based systems, on the other hand, can analyze traffic events in depth using image data. However, their performance is heavily dependent on prevailing light and weather conditions – in darkness, heavy rain, or fog, the detection rate drops significantly. In addition, processing image data always entails complex data privacy challenges.
The Classics at a Glance:
- Inductive loops: Cables embedded in the road surface react to metal. Using so-called double loops, they can distinguish between cars, trucks, and motorcycles based on vehicle length and the “magnetic footprint.” The catch: Extensive excavation work and no detection of pedestrians.
- Radar sensors: They emit electromagnetic waves and measure the reflection. This makes them extremely reliable at recording speeds in any weather. The catch: When vehicles or bicycles travel very closely together in a group, they often merge into a single object for the radar.
- Camera systems: They film the events and software analyzes the images. On paper, this provides the deepest insights into complex traffic situations. The catch: As soon as it gets dark, rains, or the sun glares, accuracy drops drastically. Furthermore, processing image data is often a legal hurdle in terms of privacy.
LiDAR Provides Data Beyond Classic Counting
LiDAR traffic counting expands the possibilities of existing traffic data collection systems with a high-resolution, three-dimensional mapping of the traffic space. The sensors create a precise spatial representation of the surroundings and capture movements regardless of color or lighting conditions.
The individual measurement points are merged into clearly identifiable objects. This not only detects that a road user is in the detection area but also determines what type of object it is. Features such as length, width, and height can also be determined. At the same time, the exact position in space is recorded, allowing cars, bicycles, and pedestrians to be precisely tracked throughout their entire movement path.
Another advantage lies in privacy-friendly data collection. Since only distance data and no identifiable image data are processed, LiDAR is particularly suitable for applications where both high data quality and the protection of personal information are paramount.
Why Permanently Installed LiDAR Sensors Offer Added Value
While mobile traffic counts are primarily used for short-term studies or before-and-after comparisons, permanently installed LiDAR sensors create a continuous data foundation. This allows developments to be observed over weeks, months, or years, and changes in traffic behavior to be identified early on.
Particularly at highly frequented intersections, accident hotspots, or newly designed traffic facilities, permanently installed sensors provide significant added value. Instead of individual snapshots, long-term datasets are created that reveal seasonal fluctuations, changes in mobility behavior, or the impact of structural measures.
Another advantage is that the same infrastructure can be used for different tasks. In addition to continuous LiDAR traffic counting, traffic flows can be analyzed, traffic jams detected, or safety-relevant events documented. As a result, the benefits of the installation grow far beyond the actual data collection.
How Does Smart LiDAR Technology Work?
LiDAR stands for Light Detection and Ranging. The sensor emits countless laser pulses per second, invisible to the human eye, and measures the time it takes for the light to be reflected by an object (e.g., a car or pedestrian), the Time-of-Flight principle. From this enormous number of measurement points, a highly precise, three-dimensional “point cloud” of the environment is created. An integrated software analyzes these points in real-time, classifies the road users, and calculates their exact speed and direction of movement – completely anonymously, without processing any image data.
Shaping the Mobility of Tomorrow with LiDAR Data
Today, traffic counting is much more than just recording vehicle numbers. Modern infrastructure projects require detailed information about traffic flows, movement patterns, and the use of public space.
Permanently installed sensors for LiDAR traffic counting create a continuous and precise data foundation for this purpose. They combine classic traffic counting with comprehensive traffic behavior analysis and provide long-term, reliable insights for the planning, operation, and optimization of traffic infrastructure. This turns a single measurement into a permanent tool for evaluating and advancing the traffic environment.
