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

Abstract

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.

Enhancing Traffic Sustainability: An Analysis of Isolation Intersection Effectiveness through Fixed Time and Logic Control Design Using VisVAP Algorithm

“…Another approach is ATSC strategy, where the phases of the signaling plan are activated upon the detection of vehicles by detectors on the road [14]. So, for the enhancement of positive effects on intersection performance, strategies such as ATSC have begun to be implemented, due to the advantages it brings in comparison to FTSC [15]. The main effect related the fact that the operation according to ATSC is associated with the ability to update parameters in response to the arrivals of vehicles at the intersection entrance.…”

Signal timing parameters inference method at intersections using license plate recognition data

“…The general methodology in trajectory-based studies can be summarised as three steps: (1) map matching, match the trajectory to the intersection, to know the correct entrance lane where the vehicle is located; (2) infer the time of passing through the stop line according to the delay, travel time or speed; (3) infer the specific parameters such as cycle length and phase duration. In addition, with the development of vehicle detection technology, a growing number of data sources are beginning to be utilised in the signal timing parameters inference work, such as connected vehicle data [19][20][21], mobile navigation data [22], mobile sensing data [23], loop detector data [24,25], magnetic vehicle detector data [26] and even simulation data [19,27]. The estimation method of multi-source data has achieved good results.…”

“…From the methodology aspect, most existing works develop statistical analysis [4], probabilistic analysis [26,38] and pattern recognition [21] to estimate signal timing parameters. These approaches, however, rely on high-quality data.…”

Design of an Efficient Vehicle-Actuated Signal Control Logic for Signalized Intersections

“…And, the studies have continued today to improve their performances [19][20][21]. Since the last quarter of the 20th century, it has been also aimed to make these systems more effective for high traffic demands at signalized intersections and thus it has been aimed to increase the operational efficiency further [22][23][24][25][26]. Especially in recent years, there has been a significant increase in the number of studies on the signal management systems and control algorithms that take the instantaneous traffic flows into account.…”

“…Vehicle-actuated management systems determine the green and red signal timings according to the current dynamics of vehicle arrivals and queuing information obtained by detectors placed on the lanes at intersection approaches [28]. Because vehicle-actuated signal management systems generally have positive effects on the intersection performance, many researchers have worked on this issue [26]. Some of these studies can be summarized as follows:…”