Estimating Signal Phase and Timing for Traffic Actuated Intersections Based on Low Frequency Floating Car Data

The objective of this paper is the application and statistical analysis of a methodology that allows the estimation of Signal Phase and Timing (SPaT) information like cycle length and green time intervals for time-dependent fixed-time controlled or traffic actuated intersections based on low-frequency and sparse vehicular probe data, so called Floating Car Data (FCD). To infer SPaT, the applied approach exploits the effects of periodic signal control, which will occur typically in case of traffic actuated signals with high saturation levels (e.g. in peak hours) or on fixed-time controlled intersections. The paper summarizes the fundamental concepts of cycle length estimation, as well as data filtering, needed to achieve robust and reliable signal timing estimates. To prove the estimation concept and to ensure the capability of a signal timing forecast based on ex ante estimates, a micro simulation is carried out, which supplies the signal timing estimation process with simulated FCD. The simulation model takes data sparsity, low-frequency (i.e. 15 sec. sampling interval) and erroneous vehicle positions into account. Finally, a statistical analysis compares inferred estimates against simulated ground truth.