Transit Priority Signal Control Scheme Considering the Coordinated Phase for Single-Ring Sequential Phasing Under Connected Vehicle Environment

Abstract

Real-time transit signal priority (TSP) controls is affected by coordination phase and deprive non-transit traffic benefits. In this paper, fully considering the migration states of coordinated phases and queuing states of non-transit vehicles, a transit signal priority controlling method is proposed for the single-ring sequential phasing under the connected vehicle (CV) environment. The queue length of the non-transit phase is estimated using real-time parking position of the probe vehicles in CV environment, and then the compression capability of phase can be confirmed. Under the premise of not destroying the green waveband of the intersection group, three models are proposed, including the green time extension, red time truncation, and phase insertion models. In the proposed model, the maximum priority effect and the minimum time deviations for the non-transit phase are taken as the optimization object. The maximum/minimum green time, total cycle length, and the backward/forward migration time of coordinated phases are taken as the constraints. Through the analysis of experimental results with examples, the transit priority control model proposed in this paper effectively improves the transit priority efficiency, and minimizes the impact on the non-transit traffic benefits while considering the coordinated phase state and not destroying the coordination effect. INDEX TERMS Coordinated phase, connected vehicle, single-ring sequential phasing, travelling benefits, TSP.

OD-Based Partition Technique to Improve Arterial Signal Coordination Using Connected Vehicle Data

“…In 2011, AASHTO presented its view that connected vehicle technology, combined with on-board equipment, roadside network service, and in-vehicle systems, provided a wide range of opportunities in adaptive signal control, traffic signal prioritization, and arterial network signal coordination ( 21 ). By leveraging connected vehicle data, existing studies were conducted to estimate traffic volumes ( 22 ), detect queue spillback ( 23 ), optimize intersection offsets by extracting arrival profiles ( 24 ), perform adaptive signal control ( 25 , 26 ), design network-level signal coordination ( 27 ), and benefit transit signal priority control ( 28 ) under the low penetration rate of the connected vehicle data. Argote-Cabanero et al developed estimation methods for various measures of effectiveness (MOEs) and proposed a methodology to determine the minimum connected vehicle penetration rate for accurate MOE estimation.…”

Signalised intersection control in a connected vehicle environment: User throughput maximisation strategy

“…In a recent study, Wu et al [44] investigated the effect of PTSP on moving bottleneck at signalised intersections in connected car and bus environment. Additionally, a real-time PTSP has been proposed by considering the migration states of coordinated phases and queuing states of non-public transport vehicles for the single-ring sequential phasing in [45]. A cooperative PTSP using vehicle to vehicle and vehicle to infrastructure communication has been also developed and investigated by Abdelhalim and Abbas [46], which could reduce 61% of public transport network delay compared to the base scenario.…”

Progression Control Model to Enhance Performance of Transit Signal Priority

“…Generally, active priority enables TSP by 2 installing telecommunication roadside equipment and sensors to detect bus arrivals at an intersection. After installing infrastructure based on single intersection points, the TSP is provided to produce an early green or green extension signal based on bus-detection information [22,23,24].…”