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.
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