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.
['Soo-Chang Pei', 'Ji-Hwei Horng']
Finding the optimal driving path of a car using the modified constrained distance transformation