In today’s society, the futuristic concept is making a huge impact and so is the concept of Autonomous driving vehicles. In urban environments and on-road scenarios, self-driving cars are becoming more reliable and safer. More and more people are showing interest and taking the risk to invest in such concepts and try to be a part of such adventures.
Even though with huge demand, the mechanism of such vehicles is complex, and guarantee for safety have to be verified formally in order to have a safe operation for everyday function within the circumference of day-to-day public activity. In unstructured environments where the transportation rules and systems are cluttered, it faces a huge technological challenge.
Although Autonomous vehicles got their own challenges, the project is financed by European Union on the basis of describing the benefits in off-road navigation for commercial vehicles by CVC (Commercial Vehicles in Off-Road Environments) with Unimog as an Example.
The project focuses on developing concepts related to control and perceptions for commercial vehicles with an improved focus on cluttered and unstructured environments.
Another example is the Oshkosh TerraMax truck. In 2006, it took part in the DARPA Grand Challenge desert race and finished it in a quantified manner. It is designed with three main units; a system capable of detecting obstacles, a planner for real-time path, and behavior management.
With respect to the trajectory derived from the planning path, controlling steering, throttle, brake, and transmissions is achieved. Thereby using the behavior-based low approach method, dynamic limits, obstacles, road edges, and the terrain are reactively adapted by the robots.
The next example is the URO VAMTAC S3 vehicle which was designed for unstructured environments. It consists of planning units in low-level and high-level and detects pathways to follow predefined waypoints. The MuCAR- 3 provides off-road navigation which is working with perception, planning, and control system.
Obstacles in static and dynamic and estimation by ego-motion are provided by the perception while the planning system is with a machine state for path and velocity planning.
The last example is HX58 TULF military truck, with a focus on human-machine cooperation where better navigation system and safety interaction is provided.