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The Signal Phase and Timing (SPaT) message is an important input for research and applications of Connected Vehicles (CVs). However, the actuated signal controllers are not able to directly give the SPaT information since the SPaT is influenced by both signal control logic and real-time traffic demand. This study elaborates an estimation method which is proposed according to the idea that an actuated signal controller would provide similar signal timing for similar traffic states. Thus, the quantitative description of traffic states is important. The traffic flow at each approaching lane has been compared to fluids. The state of fluids can be indicated by state parameters, e.g. speed or height, and its energy, which includes kinetic energy and potential energy. Similar to the fluids, this paper has proposed an energy model for traffic flow, and it has also added the queue length as an additional state parameter. Based on that, the traffic state of intersections can be descripted. Then, a pattern recognition algorithm was developed to identify the most similar historical states and also their corresponding SPaTs, whose average is the estimated SPaT of this second. The result shows that the average error is 3.1 seconds.

Estimating Signal Timing of Actuated Signal Control Using Pattern Recognition under Connected Vehicle Environment