Smart radar unit
After we have developed an algorithm on the computer to analyze the radar data, the whole thing now has to be implemented on the device. Our goal is that all the data is already analyzed in the box and we only need to store the number of cars and their speed.
Compared to the evaluation on the computer, there are a few things that need to be done differently on the device: On the computer, we worked with recorded data. On the device, we do the analysis live. This means that we have to buffer values in some places. For example, for smoothing the noisy raw signal. In one direction of travel, we have to buffer the speeds until the trigger of a passing car arrives. Only then can we save the data. For cars traveling in the other direction, we receive a trigger and then have to wait for the speed data.
The evaluation should later run completely on our sensor unit.
In addition, there is still a lot to optimize in order to evaluate the data efficiently on the small computing core.
You can follow our development in the SensorUnit repository on github.
Data analysis
After all our experiments with amplifier circuits and a low-noise power supply, our sensor now seems to be working well. At least you can clearly see different vehicles in the spectral images of the radar data and recognize how fast they are driving. But how can the whole thing be evaluated with an algorithm? In the end, we just want to count vehicles and save the speed of each vehicle.
Data analysis on the computer. The algorithm counts cars and measures speeds.
Screenshot: Nanu Frechen / CC-BY-CA
The eye can easily distinguish the actual signal from the noise. In data analysis, this requires some smoothing and well-chosen limit values. The noise also changes over time. When the battery discharges. We also had to find a solution for this.
The signal analysis is based on the fact that certain frequencies stand out from the spectrum. This can be seen as lines over time. Each line is a moving object. A moving car, for example. The speed can then be calculated from the frequency.
We use a special trick to recognize when a car passes by: As the car passes, the angle to the Rarsensor changes. This causes the signal to bend downwards (towards 0 km/h). We recognize this bend and know that a car has just driven past the sensor. Whether this bend is to the left or to the right tells us in which direction the car was traveling. Now we just have to determine the detected speed before or after this trigger and save it.
What sounds simple is the result of a lot of fiddling around. And of course we first developed the whole thing on the computer using recorded data. This now has to be programmed and tested on the device itself. Only then will we be ready to give the device to interested parties for their own measurements. But that will be soon!
If you are interested in the technical details, you can take a look at our repository on github.
CitRad starts at the Prototype Fund
After the hardware was developed the year before, CitRad is one of the funded projects of the 16th round of the Prototype Fund Software. The funding from the Federal Ministry of Education and Research enables us to improve the sensor’s evaluation routines and work on a data platform. The funding period runs until February 2025.
Following the development of the hardware and the initial tests, we took the opportunity in 2024 to present CitRad at district festivals and events such as the car-free university day and Parking Day. The response was consistently positive. We also presented CitRad to the city of Cottbus in spring 2024. It quickly became clear that there was a basic level of interest from a wide range of parties - from private individuals to mobility research and urban development.
Successfull application to the Prototype Fund
It quickly became clear that we wanted to continue working on CitRad. The fact that the application phase for the 16th round of the Prototype Fund had just started played into our hands. So we had to write an application and hope. But not for too long. Soon the invitation to the kick-off event on September 1 in Berlin fluttered into our mailbox.
CitRad is now one of 25 open source projects that will be funded for six months. Six other projects can also be assigned to the topic of city/mobility. We are excited to see where we will find intersections and look forward to an exciting next six months