A Dynamic Data Driven Application System for Vehicle Tracking

Abstract Tracking the movement of vehicles in urban environments using fixed position sensors, mobile sensors, and crowd-sourced data is a challenging but important problem in applications such as law enforcement and defense. A dynamic data driven application system (DDDAS) is described to track a vehicle's movements by repeatedly identifying the vehicle under investigation from live image and video data, predicting probable future locations, and repositioning sensors or retargeting requests for information in order to reacquire the vehicle. An overview of the envisioned system is described that includes image processing algorithms to detect and recapture the vehicle from live image data, a computational framework to predict probable vehicle locations at future points in time, and a power aware data distribution management system to disseminate data and requests for information over ad hoc wireless communication networks. A testbed under development in the midtown area of Atlanta, Georgia in the United States is briefly described.

[1]  Lei Yang,et al.  Accurate online power estimation and automatic battery behavior based power model generation for smartphones , 2010, 2010 IEEE/ACM/IFIP International Conference on Hardware/Software Codesign and System Synthesis (CODES+ISSS).

[2]  Michael Hunter,et al.  Ad hoc distributed simulation for transportation system monitoring and near-term prediction , 2014, Simul. Model. Pract. Theory.

[3]  Mohan M. Trivedi,et al.  A General Active-Learning Framework for On-Road Vehicle Recognition and Tracking , 2010, IEEE Transactions on Intelligent Transportation Systems.

[4]  Rassul Ayani,et al.  Using On-line Simulation for Adaptive Path Planning of UAVs , 2007, 11th IEEE International Symposium on Distributed Simulation and Real-Time Applications (DS-RT'07).

[5]  S. Rak,et al.  Evaluation of Grid-Based Relevance Filtering for Multicast Group Assignment , 1996 .

[6]  Yalchin Efendiev,et al.  DDDAS Approaches to Wildland Fire Modeling and Contaminant Tracking , 2006, Proceedings of the 2006 Winter Simulation Conference.

[7]  Klaus Wehrle,et al.  Modeling and Tools for Network Simulation , 2010, Modeling and Tools for Network Simulation.

[8]  Jonathan D. Beezley,et al.  Assimilation of Perimeter Data and Coupling with Fuel Moisture in a Wildland Fire-Atmosphere DDDAS , 2012, ICCS.

[9]  Kari Laasonen.  Route prediction from cellular data , 2005 .

[10]  Douglas D. Wood.  Implementation of DDM in the MAK High Performance RTI , 2002 .

[11]  Leonidas J. Guibas,et al.  Towards a Dynamic Data Driven System for Structural and Material Health Monitoring , 2006, International Conference on Computational Science.

[12]  Guan Qin,et al.  Towards a Dynamic Data Driven Application System for Wildfire Simulation , 2005, International Conference on Computational Science.

[13]  Frederica Darema,et al.  Dynamic Data Driven Applications Systems: A New Paradigm for Application Simulations and Measurements , 2004, International Conference on Computational Science.

[14]  Puneet Singla,et al.  International Conference on Computational Science, ICCS 2012 , 2012, ICCS.

[15]  T. Rossman,et al.  Evaluation of Fluid-Thermal Systems by Dynamic Data Driven Application Systems , 2006, International Conference on Computational Science.

[16]  Christian Poellabauer,et al.  Applying DDDAS Principles to Command, Control and Mission Planning for UAV Swarms , 2012, ICCS.

[17]  Li-Chen Fu,et al.  Vehicle Detection under Various Lighting Conditions by Incorporating Particle Filter , 2007, 2007 IEEE Intelligent Transportation Systems Conference.

[18]  Gabrielle Allen.  Building a Dynamic Data Driven Application System for Hurricane Forecasting , 2007, International Conference on Computational Science.

[19]  Alok Chaturvedi,et al.  DDDAS for Fire and Agent Evacuation Modeling of the Rhode Island Nightclub Fire , 2006, International Conference on Computational Science.

[20]  John Krumm,et al.  Real Time Destination Prediction Based On Efficient Routes , 2006 .

[21]  George F. Riley,et al.  The ns-3 Network Simulator , 2010, Modeling and Tools for Network Simulation.

[22]  T. Rossman,et al.  Evaluation of Fluid-Thermal Systems by Dynamic Data Driven Application Systems - Part II , 2007, International Conference on Computational Science.

[23]  Michael Hunter,et al.  Ad Hoc Distributed Simulations , 2007, 21st International Workshop on Principles of Advanced and Distributed Simulation (PADS'07).

[24]  David Roberts,et al.  Effect of Navigation Task on Recalling Content: The Case of Occasional Users in Restricted, Cave like Virtual Environment , 2007, 11th IEEE International Symposium on Distributed Simulation and Real-Time Applications (DS-RT'07).

[25]  Liang Xu,et al.  An agent-based DDM for High Level Architecture , 2001, Proceedings 15th Workshop on Parallel and Distributed Simulation.

[26]  Leonidas J. Guibas,et al.  Compressed Sensing and Time-Parallel Reduced-Order Modeling for Structural Health Monitoring Using a DDDAS , 2007, International Conference on Computational Science.

[27]  Stephen John Turner,et al.  An agent-based approach for managing symbiotic simulation of semiconductor assembly and test operation , 2005, AAMAS '05.

[28]  Paul A. Viola,et al.  Robust Real-Time Face Detection , 2001, International Journal of Computer Vision.

[29]  R.M. Fujimoto,et al.  Parallel and distributed simulation systems , 2001, Proceeding of the 2001 Winter Simulation Conference (Cat. No.01CH37304).

[30]  Murat Yuksel,et al.  Large-Scale Network Parameter Configuration Using an On-Line Simulation Framework , 2008, IEEE/ACM Transactions on Networking.

[31]  Nitesh V. Chawla,et al.  Enhanced Situational Awareness: Application of DDDAS Concepts to Emergency and Disaster Management , 2007, International Conference on Computational Science.

[32]  Carlos Brun,et al.  Coupling Wind Dynamics into a DDDAS Forest Fire Propagation Prediction System , 2012, ICCS.

[33]  Albert-László Barabási,et al.  WIPER: The Integrated Wireless Phone Based Emergency Response System , 2006, International Conference on Computational Science.