Multi-Robot Traffic Planning Using ACO

Path planning is useful in various ways that includes transportation. Traffic planning (direct vehicles through path planning) is a well known, really important and real time problem and it is important to make multi robot path planning scenario more similar to day to day traffic situation. Practically, reducing the monitoring time and to ensure that the system can adopt the dynamic changes, congestions and other situations are the main features required in a traffic planning system. We have proposed a fast approach for that situation to find the best shortest paths and also prepare other better alternatives paths. The main objective of each robot is to reach to its destination as soon as possible while avoiding collisions and deadlocks. We want to minimize the cost of travelling between the origin node and destination node. At intersection point robot are directed to an intermediate temporarily sub-goal. If quickest path is busy then next quickest alternative ways are selected. We proposed an Advance Ant Colony Optimization Algorithm in dynamically changing traffic scenario and compare the results with ACO as well as with Dijkstra algorithm. Key-Words: ACO(Ant Colony Optimization), VANET(Vehicular Ad-hoc Network)