Cooperative Traffic Control With Green Wave Coordination for Multiple Intersections Based on the Internet of Vehicles

Chen, Lien-Wu; Chang, Chia-Chen

doi:10.1109/tsmc.2016.2586500

Cited by 62 publications

(23 citation statements)

References 16 publications

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“…Jin et al [21] considered a cooperative UAV team formed by several distinct classes of UAVs to participate in search and tasks over a spatially extended battlefield with targets of various types. Another application of vehicles coordination is used for solving traffic jam [22], [23], such as VANET [24]. Form these approaches, vehicles coordinate with each other to select the path exploiting both the VANETs and the public transportation system.…”

Section: A Vehicles Coordinationmentioning

confidence: 99%

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Virtual Vehicle Coordination for Vehicles as Ambient Sensing Platforms

et al. 2018

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With the increasing number of in-vehicle sensors and the adoption of various communication interfaces, vehicles have become an ambient sensing platform for many applications such as traffic and weather monitoring, urban surveillance, road safety, and driver behavior analysis. Furthermore, a large number of vehicles can be coordinated to sense large-scale information precisely and efficiently. Such coordination requires enormous communication, computing, and power resources. In this paper, we propose a virtual vehicle (VV) coordination approach based on the theory of group consensus to sense environment information efficiently. Specifically, we first propose a discovery algorithm to find the optimal VV groups. Then, based on multi-group consensus theory, we devise a coordination algorithm to control VV groups to achieve multi-group coordination by adjusting the communication relationships among VVs. Finally, the precise environment information is acquired through the coordination of multiple VV groups. Extensive simulations are provided to demonstrate the effectiveness of the proposed schemes.INDEX TERMS Sensing platform, vehicle coordination, virtual vehicle, multi-group consensus.

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Section: A Vehicles Coordinationmentioning

confidence: 99%

“…We can then rewrite (24) in accordance with (23) , and it is then easy to obtain the following results.…”

Section: Appendix a Proof Of The Theoremmentioning

confidence: 99%

Virtual Vehicle Coordination for Vehicles as Ambient Sensing Platforms

et al. 2018

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“…T RAFFIC congestion has become a serious problem on the agenda of many public/private stakeholders, due to the constantly increasing urban traffic volumes, and to the lack of space and public funds to construct new transportation infrastructure. These problems are coupled with the complexity of understanding, modelling and controlling the dynamics of traffic networks [1], [2], [3]. In fact, as an indispensable part of any traffic control department, traffic signal operations play an important role in the effective functioning of urban traffic.…”

Section: Introductionmentioning

confidence: 99%

A Switching-Based Adaptive Dynamic Programming Method to Optimal Traffic Signaling

Liu

Baldi

et al. 2020

IEEE Trans. Syst. Man Cybern, Syst.

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The work presented in this paper concerns a switching-based control formulation for multi-intersection and multi-phase traffic light systems. A macroscopic traffic flow modelling approach is first presented, which is instrumental to the development of a model-based and switching-based optimization method for traffic signal operation, in the framework of Adaptive Dynamic Programming (ADP). The main advantage of the switching-based formulation is its capability to determine both 'when' to switch and 'which' mode to switch on without the need to use the cycle-based average flow approximation typical of state-of-the-art formulations. In addition, the framework can handle different cycle times across intersections without the need for synchronization constraints and, moreover, minimum dwell-time constraints can be directly enforced to comply with minimum green/red times in each phase. Simulation experiments on a multi-intersection and multi-phase traffic light systems are presented to show the effectiveness of the method.

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“…Unlike the solutions proposed in [9][10][11][12] which were only designed for an individual and isolated intersection, our solution is capable in remotely controlling and monitoring a network of multiple intersections. In our system, inspired by the research results [13][14][15], algorithms are also designed under various scenarios. For examples, in [12] a method for urban arterial roads was proposed, in [11] a case that included an emergency vehicle and the tracking of a stolen vehicle based on RFID was handled, while [15] exploited an internet of vehicles to solve traffic control in multiple intersections.…”

Section: Introductionmentioning

confidence: 99%

“…In our system, inspired by the research results [13][14][15], algorithms are also designed under various scenarios. For examples, in [12] a method for urban arterial roads was proposed, in [11] a case that included an emergency vehicle and the tracking of a stolen vehicle based on RFID was handled, while [15] exploited an internet of vehicles to solve traffic control in multiple intersections. Note that the algorithm embedded in our hardware is very suitable for real traffic situations like in Vietnam.…”

Section: Introductionmentioning

confidence: 99%

Applying the IoT platform and green wave theory to control intelligent traffic lights system for urban areas in Vietnam

2019

KSII TIIS

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This paper proposes an intelligent system performing an application with assistance of an Internet of Things (IoT) platform to control a traffic lights system. In our proposed systems, the traffic lights can be remotely controlled through the Internet. Based on IoT platform, the traffic conditions at different intersections of roads are collected and the traffic lights are controlled in a central manner. For the software part, the algorithm is designed based on the green wave theory to maximize the green bandwidth of arterial roads while addressing a challenging issue: the rapid changes of parameters including cycle time, splits, offset, non-fixed vehicles' velocities and traffic flow along arterial roads. The issue typically happens at some areas where the transportation system is not well organized like in Vietnam. For the hardware part, PLC S7-1200 are placed at the intersections for two purposes: to control traffic lights and to collect the parameters and transmit to a host machine at the operation center. For the communication part, the TCP/IP protocol can be done using a Profinet port embedded in the PLC. Some graphical user interface captures are also presented to illustrate the operation of our proposed system.

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Cooperative Traffic Control With Green Wave Coordination for Multiple Intersections Based on the Internet of Vehicles

Cited by 62 publications

References 16 publications

Virtual Vehicle Coordination for Vehicles as Ambient Sensing Platforms

Virtual Vehicle Coordination for Vehicles as Ambient Sensing Platforms

A Switching-Based Adaptive Dynamic Programming Method to Optimal Traffic Signaling

Applying the IoT platform and green wave theory to control intelligent traffic lights system for urban areas in Vietnam

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