Finding the optimal driving path of a car using the modified constrained distance transformation
We propose an algorithm to solve the path planning problem in an automated vehicle guidance system. Many methods have been proposed to solve such a problem, but, none of them takes as many practical factors into consideration. Although the literature dealt with one or more of the above factors separately, none had included them in a single research. We have included the following factors into our model: size and orientation, intended directions, driving costs, and obstacles. A powerful but simple algorithm based on the constrained distance transformation is shown to: (1) determine the feasibility given the start and finish positions; (2) find the optimal collision-free driving path which minimizes the total driving cost subject to the constraints; (3) provide a smooth path.