An A*-Based Search Approach for Navigation Among Moving Obstacles

Finding an optimal route in a dynamic transportation network affected by disasters is a critical problem for emergency response. Although many routing algorithms have been developed, and some of them show the ability to guide first responders around the static damaged infrastructure, there are few efforts devoted to the efficient routes avoiding moving obstacles. Emergencies caused by natural or man-made disasters can result in both static and moving obstacles in a transportation network, which poses a set of serious challenges for researchers in the navigation field. In this paper, we study the shortest-path problem for one moving object to one destination in a dynamic road network populated with many moving obstacles. Existing approaches, which are developed for stationary networks, are incapable of managing complex circumstances where the status of the road network changes over time. We propose a model to represent the dynamic network and an adapted A* algorithm for shortest path computations in the context of moving obstacles. Moreover, this paper presents a web-based application for route planning. It integrates an agent-based simulation tool for both analysis of the dynamic road network and simulation of first responders' movements, and web technologies for enabling the response community to easily and quickly share their emergency plans and to work collaboratively. We provide an experimental comparison of performance with the standard A* algorithm under different circumstances to illustrate the effectiveness of our approach.