CAVSense uses a combination of sensors to provide the full picture; real-time HD video with Radar, and LIDAR remote sensing methods to detect objects and obstructions around the vehicle.
Autonomous vehicles need to be able to react to the world around them so we have developed a range of sensor input modules and accompanying software to make decisions on whether vehicles should adjust their course, slow down, accelerate or stop based on what is happening nearby.
Our Artificial Intelligence system can identify foreign objects in the path of the vehicle.
Accurate, robust and reliable GPS, which is essential for determining the location of autonomous vehicles.
Real-time RADAR data detects hundreds of objects in and calculates their relative velocities to foresee potential collisions way in advance.
We use a new type of Flash Radar unit that is very robust in many difficult conditions such as heavy rain, fog and snow. This gives a 360 degree view around the vehicle which can be used for object collision detection.
High resolution cameras complete the picture. We use these in conjunction with AI algorithms to classify nearby objects and predict their movements.
If objects are detected in the path of a vehicle CAVSense can make decisions about how to avoid a collision. It can either bring the vehicle to a halt or it can calculate a new route around the object.
This is done whilst obeying strict rules to ensure vehicles make safe decisions.
CAVSense also uses geofencing to ensure that if a vehicle deviates off path it is spotted instantly and the necessary corrections are made.
The Cavonix video processing system uses Ethernet HD cameras to detect and classify objects such as other vehicles and pedestrians.
Detected objects can be tracked and from the tracking data we can determine their direction of movement.
This informs decision making at junctions and collision avoidance.
©2022 Cavonix. All rights reserved.