ANTI-COLLISION SYSTEM For Vehicles

High-end cars now come with auto-braking, obstacle detection, and proximity alert, which are important parts of an Advanced Driver Assist System (ADAS).

- ASHWINI KUMAR SINHA

These use proximity sensors, cameras, and/or a lidar system. This project proposes to build a simple anti-collision system with a lidar.

Fig. 1 shows the lidar mounted on a car, along with the data generated by it for giving an alert. The components required to build the project are mentioned under Table 1.

You can use any lidar that is compatible with Python and has a Python SDK module for development, such as RPi lidar, YDLIDAR, Intel Real Sense lidar, and Velodyne lidar. The price of lidars available in the market varies considerably and so does their detection range. Most of them use USB serial communication.

In our design, we used YDLIDAR X2, but you can use any of the above-mentioned lidars. However, it is important to go through the datasheet (can search on Google) of the lidar and the Python module you are using to create the code around them.

In the datasheet, we can see the table that tells us that the field of view of this lidar is 360 degrees. So, this lidar can sense in any direction as it uses a motor to rotate. Some lidars provide 250- or 180-degree coverage only, so you need to choose the lidar as per your need.

The second important aspect of a lidar is its range and the conditions under which it can work. Some lidars use IR laser or red laser to work, some use doppler waves, and some others may be using yet another technology. So, to design a solution that works even in a foggy or rainy environment, we need to select the lidar accordingly.

In our design we have used laser-based YDLIDAR X2, whose parameters are given in Table 2 and whose image is shown in Fig. 2.