Platoon Priority Visualization Modeling and Optimization for Signal Coordination in the Connected Vehicle Environment

Abstract

Although connected vehicle (CV)-based signal coordination has some proposed prototypes and has been investigated by several different strategies, the existing works have issues that require attention, including additional CV-based system uncertainties and platoon priority request considerations. Thus, a generalized framework consisting of a platoon-based bicyclic coordination diagram (Bi-PCD), a new probabilistic surrogate quantification, and a platoon priority-based offset optimization in the CV environment is proposed to improve the coordination performance. The proposed Bi-PCD extends the scope of the current Purdue coordination diagram (PCD) and its variants by covering extra practical and emerged variables. A prototype and field tests in a CV test pilot for general scenarios were implemented in a typical arterial road to verify performances of the proposed Bi-PCD and the offset optimization method. Field results demonstrated that using Bi-PCD could obtain explicit platoon features in both limited and full CV penetration conditions. The comprehensive analysis showed that the proposed Bi-PCD and the platoon priority-based offset optimization could further improve performances of the signal coordination.

Effects of Connectivity and Traffic Observability on an Adaptive Traffic Signal Control System

“…In contrast with previous studies that only used loop detector or probe data, Beak et al ( 29 ) compared the progression quality of a CV-based signal system under different strategies, namely free and coordinated operations. Li et al ( 30 ) demonstrated the use of progression quality for optimizing platoon priority-based offset optimization in a CV environment. Day et al ( 31 ) also examined the feasibility of offset optimization using CV data at different penetration rates based on travel time reliability.…”

Real‐time predictive coordination based on vehicle‐triggered platoon dispersion in a low penetration connected vehicle environment

“…Then, arrival profiles created by virtual detections were used to obtain signal offset optimization for signal coordination. Furthermore, Beak et al in 2018 [25] proposed a modified Purdue coordination diagram (PCD) utilizing CV data, labelled as CV-PCD, in order to quantitatively evaluate the smooth progression along a corridor [8]. Li et al in 2019 [8] presented an extended offset optimization that targets platoon priority with better signal coordination in a CV environment.…”

“…As shown in Figure 6, a signalized intersection located at 109 St. and 23 Ave. in the ACTIVE testbed [8] was selected to evaluate the proposed method. Figure 6a demonstrates the geometric layout and the phase diagram of the target intersection.…”

“…The emerging CV technology provides two potential benefits for signal control systems, which are fine-grained spatial and temporal vehicle and infrastructure data, and real-time data transmission via high-frequency vehicle-to-infrastructure (V2I) communication [1,5]. Based on these features, various CVbased signal coordination approaches are divided into two categories: offline offset optimization, and online control [8].…”

“…Thus, CV-based signal coordination systems offer huge potential utilizing the real-time spatial and temporal data advantage when addressing many traffic-related issues, and accordingly, have shown promising benefits to performance over the existing typical signal control systems [1,5]. Consequently, many CV-based signal coordination approaches have been introduced in the past decade from both offline offset optimization using large trajectory data and online control utilizing the real-time CV data perspectives [8]. The former offline offset optimization can provide good offset values in low-CVpenetration conditions by aggregating large CV trajectories.…”