Path Planning for First Responders in the Presence of Moving Obstacles With Uncertain Boundaries

In this paper, we study path planning for first responders in the presence of uncertain moving obstacles. To support the path planning, in our research we use hazard simulation to provide the predicted information of moving obstacles. A major problem in using hazard simulation is that the simulation results may involve uncertainty due to model errors or noise in the real measurements. To address this problem, we provide an approach to handle the uncertainty in the information of moving obstacles, and apply it to the case of toxic plumes. Our contribution consists of two parts: 1) a spatial data model that supports the representation of uncertain obstacles from hazard simulations and their influence on the road network and 2) a modified A* algorithm that can deal with the uncertainty and generate fast and safe routes passing though the obstacles. The experimental results show the routing capability of our approach and its potential for the application to real disasters.

[1]  Bhavani M. Thuraisingham,et al.  Emergency Response Applications: Dynamic Plume Modeling and Real-Time Routing , 2008, IEEE Internet Computing.

[2]  Maxim Likhachevy,et al.  Planning with approximate preferences and its application to disambiguating human intentions in navigation , 2013, 2013 IEEE International Conference on Robotics and Automation.

[3]  Anthony Stentz,et al.  Planning with uncertainty in position an optimal and efficient planner , 2005, 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[4]  Maxim Likhachev,et al.  Anytime Safe Interval Path Planning for dynamic environments , 2012, 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[5]  A.K. Mahmood,et al.  Feasible Route Determination Using Ant Colony Optimization in Evacuation Planning , 2007, 2007 5th Student Conference on Research and Development.

[6]  Maxim Likhachev,et al.  SIPP: Safe interval path planning for dynamic environments , 2011, 2011 IEEE International Conference on Robotics and Automation.

[7]  Kushal Mukherjee,et al.  Language measure-theoretic path planning in the presence of dynamic obstacles , 2013, 2013 American Control Conference.

[8]  Xiaolin Hu,et al.  Data assimilation using sequential monte carlo methods in wildfire spread simulation , 2012, TOMC.

[9]  Juan Carlos García-Díaz,et al.  Uncertainty and sensitive analysis of environmental model for risk assessments: An industrial case study , 2012, Reliab. Eng. Syst. Saf..

[10]  Michael Glemser,et al.  HYBRID MODELLING AND ANALYSIS OF UNCERTAIN DATA , 2000 .

[11]  Nils J. Nilsson,et al.  A Formal Basis for the Heuristic Determination of Minimum Cost Paths , 1968, IEEE Trans. Syst. Sci. Cybern..

[12]  Michinori Hatayama An adaptive evacuation route algorithm under flood disaster , 2006 .

[13]  Sisi Zlatanova,et al.  Multi-agent Infrastructure Assisting Navigation for First Responders , 2013, IWCTS '13.

[14]  François Anton,et al.  On-line Street Network Analysis for Flood Evacuation Planning , 2008 .

[15]  Anthony Stentz,et al.  Anytime policy planning in large dynamic environments with interactive uncertainty , 2012, 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[16]  Frank Dellaert,et al.  Path planning with uncertainty: Voronoi Uncertainty Fields , 2013, 2013 IEEE International Conference on Robotics and Automation.

[17]  Sisi Zlatanova,et al.  Taxonomy of Navigation for First Responders , 2013, Progress in Location-Based Services.

[18]  I. Visser Route determination in disaster areas: Using predictions and introducing the option to wait to improve routing results , 2009 .

[19]  Francisco Orozco,et al.  Ant Colony Optimization Model for Tsunamis Evacuation Routes , 2014, Comput. Aided Civ. Infrastructure Eng..

[20]  Ranjani Wasantha Kulawardhana Remote sensing and GIS technologies for monitoring and prediction of disasters , 2012, Int. J. Digit. Earth.

[21]  Sisi Zlatanova,et al.  A data model for route planning in the case of forest fires , 2014, Comput. Geosci..

[22]  Maxim Likhachev,et al.  Using state dominance for path planning in dynamic environments with moving obstacles , 2012, 2012 IEEE International Conference on Robotics and Automation.

[23]  Peter Nijkamp,et al.  Urban traffic incident management in a digital society. An actor-network approach in information technology use in urban Europe , 2014 .

[24]  Mark H. Overmars,et al.  Roadmap-based motion planning in dynamic environments , 2005, IEEE Trans. Robotics.