NSF Award
0349460
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. <br/><br/>The Federal Highway Administration reports that the cost of traffic congestion in 1999 came to $78 billion nationwide, including 4.5 billion hours of lost time and 6.8 billion gallons of fuel wasted. Most transportation experts estimate that the ability to quickly provide accurate traffic information as proposed in this project has many benefits: 1) for drivers to plan alternative routes, keep on their schedules, and to reduce stress, 2) for overall congestion and better road maintenance, 3) for safety and road-rage mitigation, and 4) for improved pollution control.
