Self-driving vehicles are one of the emerging technologies. This technology has potential to save lives and make lives comfortable. However, the technology used in self driving cars has to perform series of task for building perceptions. This has some certain prerequisites related to road infrastructure and is affected by daylight and weather conditions of the place. If these prerequisites are not satisfied then it could affect the performance of the vehicle and can be considered as compromise with safety of the users. This research work is focused on trying to find a new approach using which the underdeveloped countries will also be able to implement self driving cars in their county. The objective of this paper is to propose a new approach to supplement the technology used in the self-driving cars for perception. Using this approach the countries who don’t satisfy the prerequisites would be eligible to implement them without compromising the safety.
The proposed approach uses the technology Augmented Reality to create and augment artificial objects of navigational signs and traffic signals based on vehicles location to reality. Later the augmented scene is fed into the conventional Deep learning object detection algorithm to detect the navigational artificial objected along with other real objects. This approach help navigate the vehicle even if the road infrastructure does not have very good sign indications and marking.
The approach was tested locally by creating a local navigational system and a smartphone based augmented reality app. The approach performed better than the conventional method as the objects were clearer in the frame which made it each for the object detection to detect them.