Freeway Traffic Speed Estimation with Single-Loop Outputs

Abstract

Traffic speed is one of the most important indicators for traffic control and management. Unfortunately, speed cannot be measured directly from single inductance loops, the most commonly used detectors. To calculate space-mean speed, a constant, g, is often adopted to convert lane occupancy to traffic density. However, as illustrated by data from the present study, such a formula consistently underestimates speed whenever a significant number of trucks or other longer vehicles are present. This is because g is actually not a constant but, rather, a function of vehicle length. To calculate the value of g suitably, one needs to know the percentage of long vehicles or the mean vehicle length in real time. However, such information is not directly available from single-loop outputs. It is shown how the occupancy variance obtained from single-loop data can be used to estimate the percentage of long vehicles and how a log-linear regression model for mean vehicle length estimation based only on single-loop outputs can be developed. The estimated mean vehicle length is used to calculate the corresponding g-value in real-time to estimate speed more accurately. The speed estimations with corrected g-values are very close to the speeds observed by the speed trap in the present study.