Mobile App for Risk Based Route Planning

Mobile devices such as the iPod Touch and iPhone have spurred the “every soldier a sensor” vision into reality. Inspired by the rapid-transition success of TIGR, we built an Android App - RouteRisk - for risk-based route planning to investigate the design issues involved to support server infrastructure, Web services and soldier-sourced tactical data input requirements. httpv://www.youtube.com/watch?v=Xz9U1wc7UYM

Current path planning systems such as the US Army’s Battlespace Terrain Reasoning and Awareness – Battle Command (BTRA-BC) involve time intensive terrain analysis computations, and require an expert user with GIS experience and knowledge of terrain analysis. These systems do not provide an easy-to-use web accessible interface by the boots on the ground. As a planning and re-planning system, RouteRisk calculates risk and recommends routes based on soldier-sourced data provided through tactical intelligence and route planning systems like TIGR (Tactical Ground Reporting), DCGS-A (Distribute Common Ground System – Army), and BFT (Blue Force Tracker). And when new intelligence is discovered, like a previously unreported poppy field by a soldier on patrol or an S2, that the intelligence gets pushed out to all units, because the servers and smartphones are connected through the cloud.

RouteRisk leverages our Risk Based Route Planning web service solution developed in earlier projects. Risk-based Route Planning is a Google Maps web service application allowing the user to plan safe routes in Baghdad, Iraq by avoiding known hotspots and predicted hotspots learned from patterns of past incidents. The web service application generates a risk surface from the incident reports using a Bayesian spatial similarity approach. Our Bayesian model learns the causal relationship between attack characteristics (such as attack type, the intended target, emplacement method, explosive device characteristics, etc.) and spatial attributes (distance to proximal features such as overpasses, government facilities, police checkpoints, etc.). For a given region, we use spatial attributes (distance to nearest overpass, major religion, within 300m of district border, neighborhood) as evidence in the model and we perform inference on the data.

By selecting the “Route” tab on the main navigation, the user can easily create a new route plan. The map is launched and the user is instructed to tap points on the map to define waypoints for the route (starting, intermediate and ending locations). To drag waypoints the user would Press-and-Hold. Optionally, the user can also bookmark locations or search for locations by placename (e.g. “Camp Helmand” or “Paktika District”) or grid reference. By pressing and holding down on waypoints, the user can choose among several actions to perform, such as “move waypoint” or “define time window”. Once a pair of waypoints are defined or a new one is added, a route plan is automatically computed and shown using the current routing preferences and selected factors. The user can change the routing preferences by clicking a button that animates the corner of the map to curl up and reveal the routing preferences. The user can select preferences such as “fastest route” or “shortest distance” or “safest route”.

We are currently researching the software architecture design alternatives for adding voice control capabilities to our RouteRisk app.