Existing freeway and signalized arterial street incident detection algorithms were investigaled lo determine their merit for use on urban arterial streets. Based on this investigalion, a Kalman filtering algorithm was modified to recursively filter and update aggregate traffic flow and speed data to estimate true values. A test using measured arterial street data at a signalized intersection shows good tracking ability on these trafiic variables over time. A test using data from an incident on an arterial street also confirmed that this algorithm has good potential for arterial street incident detection.