Project Summary
Estimating traffic density is of critical importance to understand current traffic conditions. An algorithm for estimating traffic density using data from automobile sensors has a pivotal role in improving the accuracy of road congestion prediction technologies. Traditionally traffic density has been generalized at the link level. But the densities of individual lanes on a link vary when a road become congested, meaning that the congestion level has a correlation with density variations among individual lanes.
This research will:
– Develop a traffic density estimation algorithm for use with automobile sensor data
– Analyze its effectiveness by using a microscopic simulation approach
– Analyze lane-by-lane traffic variations according to congestion levels