Best-Path Planning for Public Transportation Systems

The author examines methods for a special class of path planning problems in which the routes are constrained. General search algorithms assume that we can move around in the traffic network freely, so they extend the partial paths from the very last location to each of its neighbors to form more partial paths. The best partial paths are then selected to expand, unless the selected partial path happens to be a solution. Without proper guidance, this strategy may lead to inefficient planning algorithms when the way one can move around in the networks is constrained. This scenario could happen in public transportation systems where passengers cannot order drivers to change the routes of public buses to meet individual travel needs. A few recently proposed path-planning algorithms for public transportation systems capture the route constraints by matrices. Although they work for some applications, they are not perfect for cooperating with traditional algorithms for best-path planning. Applying special properties of matrix multiplication, the author also employs matrices for capturing the route constraints. The author improves previous designs, and come up with the so-called Q matrices that serve well in the A* algorithm for best-path planning under route constraints. Keywords—Intelligent Transportation Systems, Advanced Public Transportation Systems, Path Planning under Constraints, Matrix Applications, A* Algorithm, Search