Enabling obstacle avoidance for Google maps' navigation service
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Abstract
City infrastructures are sensitive to disasters. To aid rescue workers and citizens, a system is needed which determines the shortest route to a certain location, taking the damages of the infrastructure into account. The biggest disadvantage of current navigation systems is that they are “closed” i.e. they are built on top of commercial software packages and as such are only usable by rescue organizations which own licenses for these software packages. Modern web-technologies provide tools to ease information collection and to facilitate the dissemination of data. Recent successes of crowdsourced platforms such as OpenStreetMap, Ushahidi and Wikipedia, suggest the deployment of the crowdsourcing phenomenon to disaster management. The idea is to let the “crowd” in a disaster area collect information about the state of the infrastructure. People on the street form a highly dispersed network of sensors which is able to provide information in real-time at no cost to the rescue workers. This paper proposes and implements a method for performing shortest path calculations taking crowdsourced information, in the form of constraints and obstacles, into account. The method is built on top of Google Maps (GM) and uses its routing service to calculate the shortest distance between two locations. Users provide the constraints and obstacles in the form of polygons which identify impassable areas in the real world. The A* pathfinding algorithm is used to guide Google's Directions Service around obstacles.