Abstract:
Autonomous vehicles are mobile robots that integrate
advanced technology for navigation, decision-making, and
control. These vehicles have been developed in response to the
growing concerns around accidents and injuries caused by human
drivers, as well as to reduce the negative impact of cars on the
environment, including energy consumption, pollution, and
congestion. A combination of sensors and algorithms gives
autonomous cars a comprehensive understanding of their
surroundings, allowing them to safely navigate roads, detect other
vehicles, pedestrians, and traffic lights, and reach their
destination.
This research is intended plan the path with obstacle avoidance
while restricting to the constraints imposed by the maximum
lateral acceleration and turning angles along lane.The proposed
approach is capable of real-time detection and recognition of
obstacles and tracking lanes. Several obstacle detection sensors
are used to detect and avoid obstacles coming from the front, left
and right directions with the detection accuracies of 96%, 87%
and 81% respectively. Lane line detection and tracking are
performed by the real-time acquisition of images followed by realtime
image processing. Evaluation results prove that the proposed
method can efficiently detect and avoid obstacles while following
the lane lines on the road.
