SBIR-STTR Award

This Small Business Innovation Research (SBIR) Phase I project will provide practical tools for visualizing real-time road traffic data and computer-generated traffic simulations using 2D and 3D animation for broadcast and the Internet. Except for weather forecasts, data-driven animations are rarely produced in real-time from live data. Traffic visualization contains more challenges than weather visualization. The objective of this project is to determine the feasibility of building practical, fully functional tools to access data in a timely fashion and produce a compelling animation within seconds. This tool must model traffic incidents and flow in a timely and accurate fashion. The anticipated result includes animation and video-production tools that will be converted to a commercial product during Phase II.Potential applications include TV broadcasts, traffic control centers, police dispatch centers, and visualization tools for transportation studies and planning. In addition, the animation principles derived from this project could be applicable to visualizing other real-time data in an animation. The first application is broadcast television, for morning traffic segments. Further applications include traffic control centers, dispatches, and tools for transportation planning. A third domain of application is information dissemination on small-screen displays (PDA, etc) when the bandwidth and market materialize.

This Small Business Innovation Research (SBIR) Phase II project aims at 2D/3D visualization of real-time traffic/traveler data (incidents, speed/density, public events) and computer traffic simulations. The rapid production of data-driven, information-rich animations has previously proved very difficult. With the notable exception of weather forecast animations, requiring highly expensive complex multi-computer systems, quality animations are routinely produced weeks ahead of time for television documentaries. Traffic/traveler data represents particular challenges such as the fact that data changes very frequently and becomes stale in minutes. Much of this data is in textual form, as reported on-scene by police or emergency crews. Reliability and utility to the traveler are concerns. Consequently, the four major weather broadcast companies have scarcely addressed the traffic market. This project will develop traveler data processing algorithms for predicting travel time, mining large databases of traffic information, and intelligent text- processing. It will also develop traffic micro-simulations, automating data-driven animation, and exploiting programmable graphics hardware for broadcast-quality real-time informative animations. The expected results of this project are: 1) algorithms providing useful information to travelers/commuters from raw real-time police reports and sensor data; and 2) a product animating real-time traffic/traveler information for TV broadcast and the Internet, exploiting gradual improvements of raw data, as departments of transportation equip highways with speed/density sensors, and enforcement agencies open their servers.