Detector-Free Optimization of Traffic Signal Offsets with Connected Vehicle Data

Day, Christopher M.; Li, Howell; Richardson, Lucy; Howard, James F.; Platte, Tom; Sturdevant, James R; Bullock, Darcy M.

doi:10.3141/2620-06

Cited by 53 publications

(44 citation statements)

References 7 publications

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“…Compared with the existing works (2,(12)(13)(14)(15)(16)(17)(18)(19)(20)(21)(22), more practical and emerged variables are covered in the proposed Bi-PCD. In addition, a new probabilistic surrogate quantification combined with an offset optimization is proposed to improve coordination performances.…”

Section: Methodsmentioning

confidence: 99%

“…This is because the arrival events could be affected by a vehicle queue that grows beyond the fixed detector location, thus causing visualization bias which cannot detect arrivals (15). (2,12). The CV technology has emerged as a significant data source for complementing and even replacing the traditional fixed detector-based event data (2,12,15).…”

Section: System Uncertaintiesmentioning

confidence: 99%

See 1 more Smart Citation

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

Qiu

Seraj

et al. 2019

Transportation Research Record

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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.

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Section: Methodsmentioning

confidence: 99%

Section: System Uncertaintiesmentioning

confidence: 99%

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

Qiu

Seraj

et al. 2019

Transportation Research Record

View full text Add to dashboard Cite

show abstract

“…A delay estimation based on Kalman filtering was proposed in [22], and congestion control was performed accordingly to improve the system throughput. Different bandwidth estimation methods based on Kalman filtering were proposed and applied to different scenarios in [23][24][25][26][27][28][29][30][31][32][33][34][35], however, these algorithms were all based on linear systems, while most of the actual networks were nonlinear systems.…”

Section: Research Background and Related Workmentioning

confidence: 99%

Research of Wireless Congestion Control Algorithm Based on EKF

Wang¹,

Tang²,

Hong³

2020

Symmetry

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The random variation of bandwidth in wireless networks causes some significant challenges to the congestion control protocols based on bandwidth estimation. In this paper, a wireless congestion control scheme based on extended Kalman filtering and bandwidth (CSEKB) is proposed. The CSEKB can effectively perceive the bandwidth oscillation of wireless networks and distinguish the type of packet loss by establishing a noise perception factor. According to the congestion factor, the congestion control parameters are adjusted to correspondingly improve the performance of the wireless network. Moreover, the variation trend of the size of the congestion window presents a law of similar normal distribution curve, which has a certain degree of local symmetry. The CSEKB was implemented in Network simulator 3 (NS3) and compared with TCP Westwood (TCPW), CUBIC, and extended Kalman filtering-based bandwidth estimation (EBE). Through extensive simulation studies, the proposed CSEKB demonstrated the significant performance in wireless networks. First, the CSEKB can achieve congestion control based on the accurate prediction of available bandwidth, and improve average throughput and link utilization. In addition, the CSEKB has good fairness and friendliness compared with several other well-known congestion control methods.

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“…Aziz and Ukkusuri (2016) Fair queuing algorithm for signal control accounting for user level fairness in terms of trip delay Uses a modified expectation maximization approach with Kalman filtering on a customized state-space model. Day et al (2017) Detector-free approach to signal coordination by optimizing offsets using CV data ''Virtual Detection'' generates arrival profiles of vehicles using CV data that can be used to optimize offsets for signal coordination. Beak, Head, and Feng (2017) Adaptive coordination-based signal control to provide progression to vehicles Bi-level optimization approach.…”

Section: Simulation Framework To Evaluate Benefitsmentioning

confidence: 99%

Strategic and Tactical Guidance for the Connected and Autonomous Vehicle Future

Ukkusuri¹,

Sagir²,

Mahajan³

et al. 2019

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JOINT TRANSPORTATION RESEARCH PROGRAMThe Joint Transportation Research Program serves as a vehicle for INDOT collaboration with higher education institutions and industry in Indiana to facilitate innovation that results in continuous improvement in the planning, design, construction, operation, management and economic efficiency of the Indiana transportation infrastructure. Abstract Autonomous vehicle (AV) and connected vehicle (CV) technologies are rapidly maturing and the timeline for their wider deployment is currently uncertain. These technologies are expected to have a number of significant societal benefits: traffic safety, improved mobility, improved road efficiency, reduced cost of congestion, reduced energy use, and reduced fuel emissions. State and local transportation agencies need to understand what this means for them and what they need to do now and in the next few years to prepare for the AV/CV future. In this context, the objectives of this research are as follows:1. Synthesize the existing state of practice and how other state agencies are addressing the pending transition to AV/CV environment 2. Estimate the impacts of AV/CV environment within the context of (a) traffic operations-impact of headway distribution and traffic signal coordination; (b) traffic control devices; (c) roadway safety in terms of intersection crashes 3. Provide a strategic roadmap for INDOT in preparing for and responding to potential issues This research is divided into two parts. The first part is a synthesis study of existing state of practice in the AV/CV context by conducting an extensive literature review and interviews with other transportation agencies. Based on this, we develop a roadmap for INDOT and similar agencies clearly delineating how they should invest in AV/CV technologies in the short, medium, and long term. The second part assesses the impacts of AV/CVs on mobility and safety via modeling in microsimulation software Vissim. 17.

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Detector-Free Optimization of Traffic Signal Offsets with Connected Vehicle Data

Cited by 53 publications

References 7 publications

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

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

Research of Wireless Congestion Control Algorithm Based on EKF

Strategic and Tactical Guidance for the Connected and Autonomous Vehicle Future

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