Vehicular Traffic Management Based on Traffic Engineering for Vehicular Ad Hoc Networks

Guidoni, Daniel L.; Maia, Guilherme; Souza, Fernanda Sumika Hojo de; Villas, Leandro A.; Loureiro, Antônio A. F.

doi:10.1109/access.2020.2978700

Cited by 53 publications

(22 citation statements)

References 38 publications

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“…Nesta seção, descrevemos os principais trabalhos relacionados sobre mobilidade urbana, ITS e estratégias de TM. Várias soluções existentes focam exclusivamente em informações de tráfego urbano, como as referências [7][8][9][10][11]. Por outro lado, existem soluções que incorporam parâmetros de rede à estratégia de TM, por exemplo, as propostas apresentadas nas referências [5,12].…”

Section: Trabalhos Relacionadosunclassified

“…Guidoni et al [7] apresentam uma solução de TM com base nas informações sobre a densidade de veículos nas estradas e o modelo macroscópico de engenharia de tráfego densidade-fluxo. Essas informações auxiliam na modelagem da identificação de rotas congestionadas e, consequentemente, na redução do tempo de viagem dos veículos.…”

Section: Trabalhos Relacionadosunclassified

“…Adicionalmente, ao longo dos anos, o número de dispositivos conectados às redes LTE aumentou, devido ao acréscimo da alta densidade de veículos em vias congestionadas e aos pedestres concentrados nas ruas ou dentro dos veículos [7]. Este massivo número de conexões e seu volume de tráfego em torres LTE, tendem a esgotar os recursos da rede, comprometendo a QoS do ITS.…”

Section: Introductionunclassified

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DINO: Roteamento Dinâmico para ITS Considerando Recursos da Rede

Araújo¹,

Silveira²,

Gomes³

2021

Anais Do XII Computer on the Beach - COTB '21

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Intelligent Transport Systems (ITS) arose as a modern solution to traffic jams and vehicle accidents in the urban environment. A key part of the ITS is Traffic Management (TM), which concerns the planning and route definition of the vehicle. Existing TM solution focuses specifically on urban traffic information, ignoring the issues related to the network infrastructure and the applications at the top of it. Within this context, this paper presents a vehicle routing and re-routing strategy, called DINO, that considers both travel time of vehicles on the roads and the active network flows in the network, aiming to dynamically bring a suitable balance between travel time and packet delivery through a heuristic. The experiments performed suggest that DINO improves the packet delivery of the applications while reduces the average travel time of vehicles.

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Section: Trabalhos Relacionadosunclassified

Section: Introductionunclassified

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DINO: Roteamento Dinâmico para ITS Considerando Recursos da Rede

Araújo¹,

Silveira²,

Gomes³

2021

Anais Do XII Computer on the Beach - COTB '21

View full text Add to dashboard Cite

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“…Intersections or traffic lights can be optimized for efficient traffic flow, as vehicles can safely and optimally transverse through without the need for stopping [ 31 , 32 ]. Broadcasting of GPS information can also be used for re-routing traffic to avoid highly congested areas promoting efficient traffic flow [ 33 , 34 ]. Broadcasting information from neighboring motorway lanes will also have the effect of improving traffic flow and efficiency, as vehicles can change or merge into lanes to promote optimal driving conditions [ 35 , 36 ].…”

Section: Introductionmentioning

confidence: 99%

Regulatory and Technical Constraints: An Overview of the Technical Possibilities and Regulatory Limitations of Vehicle Telematic Data

McDonnell

Murphy

Sheehan

et al. 2021

Sensors

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A telematics device is a vehicle instrument that comes preinstalled by the vehicle manufacturer or can be added later. The device records information about driving behavior, including speed, acceleration, and turning force. When connected to vehicle computers, the device can also provide additional information regarding the mechanical usage and condition of the vehicle. All of this information can be transmitted to a central database via mobile networks. The information provided has led to new services such as Usage Based Insurance (UBI). A range of consultants, industry commentators and academics have produced an abundance of projections on how telematics information will allow the introduction of services from personalized insurance, bespoke entertainment and advertise and vehicle energy optimization, particularly for Electric Vehicles (EVs). In this paper we examine these potential services against a backdrop of nascent regulatory limitations and against the technical capacity of the devices. Using a case study approach, we examine three applications that can use telematics information. We find that the expectations of service providers will be significantly tempered by regulatory and technical hurdles. In our discussion we detail these limitations and suggest a more realistic rollout of ancillary services.

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“…An important method to infer the correlations between topology and function is the detection of network structure [3]. Since the traffic management should consider the following tasks [4]: traffic monitoring, congestion detection, and routing suggestion, monitoring the real-time data is a prerequisite for subsequent operations, especially under variable traffic loads scenarios. A traditional management system using different sensing solutions (such as a sensor network, induction loops, and cameras) to obtain real-time traffic information has many drawbacks due to its intermittent connectivity and coarse-grained data affected by environmental conditions.…”

Section: Introductionmentioning

confidence: 99%

A Coordination Algorithm for Signalized Multi-Intersection to Maximize Green Wave Band in V2X Network

Shi

Han

et al. 2020

IEEE Access

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The signal control system for multi-intersection traffic management is an extensive complex nonlinear and non-equilibrium system and usually leads to a weak control strategy. Existing studies of traffic dynamics mainly focus on the applications to the single network, whereas how the structure of multiple intersections affects the dynamical behaviors is unclear. Connected vehicles in recent studies have shown the potential to eliminate traffic communication barriers and balance the traffic load. For this consideration, we propose a new multi-intersection model based on Vehicle-to-Everything (V2X) network to capture the features of traffic flow, which employs vehicular communication to obtain real-time traffic information and share it among the adjacent intersections. Focus on smoothing traffic flow without stopand-go driving and improving the coordination of multiple traffic lights, we develop a multi-intersection coordination algorithm based on V2X (MICA-V for short) to maximize the green waveband in the arterial road. Due to the establishment of registration list yielding the average saturated headway time, our method is of high efficiency-the distributed process of data makes the convergence to be very fast with nearly linear time. Simulation results via MATLAB with Simulation of Urban Mobility (SUMO) showed the effectiveness of the proposed MICA-V in improving traffic capacity, reducing the number of stop behaviors, and improve the average speed of vehicles moving on the arterial road.

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Vehicular Traffic Management Based on Traffic Engineering for Vehicular Ad Hoc Networks

Cited by 53 publications

References 38 publications

DINO: Roteamento Dinâmico para ITS Considerando Recursos da Rede

DINO: Roteamento Dinâmico para ITS Considerando Recursos da Rede

Regulatory and Technical Constraints: An Overview of the Technical Possibilities and Regulatory Limitations of Vehicle Telematic Data

A Coordination Algorithm for Signalized Multi-Intersection to Maximize Green Wave Band in V2X Network

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