Analysis of Queue Estimation Process at Signalized Intersections Under Low Connected Vehicle Penetration Rates

This study investigates the factors affecting estimation accuracy of queue length at signalized intersections under low penetration of connected vehicles. A shockwave-based algorithm is proposed to estimate the maximum queue length and residual queue on a cycle-by-cycle basis. Simulation data collected from three consecutive signalized intersections were used to extract trajectories of CVs under five different market penetration rates and two different traffic conditions (under-saturated and moderate). The results confirm that the queue length estimation process is probabilistic and affected by the stochastic changes in traffic conditions. This probabilistic nature is defined by a queue formation coverage index (QI) that proved to significantly affect the queue length estimation accuracy. Overall, the results show that the queue estimates accuracy is acceptable when a QI value of at least 50% is achieved. In such limited data environments, the QI showed the potential to help as an assessment tool to evaluate the obtained queue estimates.