Low Delay and Seamless Connectivity-based Message Propagation Mechanism for VANET of VCPS

Zhao, Hongzhuan; Yue, Hang; Gu, Tianlong; Li, Chunhai; Zhou, Dake

doi:10.1007/s11277-021-08185-w

Cited by 16 publications

(8 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…An intelligent traffic application is one of those that are sensitive to packet delay. Equation (2) illustrates the many forms of delays, including processing delay (PD), transmission delay (TD), and propagation delay (PD) [ 20 , 21 ].

where the components of the equation are as follows:…”

Section: Methodsmentioning

confidence: 99%

Intelligent Traffic Model for Unmanned Ground Vehicles Based on DSDV-AODV Protocol

Ali

Ngadi

Al_Barazanchi

et al. 2023

Sensors

View full text Add to dashboard Cite

Traffic systems have been built as a result of recent technological advancements. In application, dependable communication technology is essential to link any system needs. VANET technology is used to communicate data about intelligent traffic lights, which are focused on infrastructure during traffic accidents and mechanisms to reduce traffic congestion. To ensure reliable data transfer in VANET, appropriate routing protocols must be used. This research aims to improve data transmission in VANETs implemented in intelligent traffic lights. This study investigates the capability of combining the DSDV routing protocol with the routing protocol AODV to boost AODV on an OMNET++ simulator utilizing the 802.11p wireless standard. According to the simulation results obtained by analyzing the delay parameters, network QoS, and throughput on each protocol, the DSDV-AODV routing protocol performs better in three scenarios compared to QoS, delay, and throughput parameters in every scenario that uses network topology adapted to the conditions on the road intersections. The topology with 50 fixed + 50 mobile nodes yields the best results, with 0.00062 s delay parameters, a network QoS of 640 bits/s, and a throughput of 629.437 bits/s. Aside from the poor results on the network QoS parameters, the addition of mobile nodes to the topology influences both the results of delay and throughput metrics.

show abstract

where the components of the equation are as follows:…”

Section: Methodsmentioning

confidence: 99%

Intelligent Traffic Model for Unmanned Ground Vehicles Based on DSDV-AODV Protocol

Ali

Ngadi

Al_Barazanchi

et al. 2023

Sensors

View full text Add to dashboard Cite

show abstract

“…With the rapid population expansion and car ownership growth, traffic congestion becomes a topic issue over the past decade. To solve this issue, various traffic models [1][2][3][4][5][6][7] have been put forward to investigate the characteristics of traffic flow. Generally, there are two kinds of traffic models, i.e., macroscopic traffic flow models [8][9][10] and microscopic traffic flow models [11][12][13].…”

Section: Introductionmentioning

confidence: 99%

A New Two-Lane Lattice Model with the Consideration of the Driver’s Self-Anticipation Current Difference Effect

Zhao

Wan

Qin

et al. 2022

Mathematical Problems in Engineering

View full text Add to dashboard Cite

To prevent traffic congestion, drivers always adjust the driving behavior with their driving information. By considering the self-anticipation effect and the optimal current difference effect on traffic flow stability, a novel two-lane lattice hydrodynamic model is proposed. Compared with Peng’s model, the linear stability analysis results reveal that the self-anticipation term can effectively enlarge the stable region on the phase diagram. Then, a reductive perturbation method is used to derive the mKdV equation describing traffic congestion near the critical point. Nonlinear analyses show that the traffic congestions can be effectively suppressed by taking the coefficient of lane-changing behaviors γ and the anticipation time τ into account. These results further indicate that the driver’s self-anticipation current difference effect can efficiently alleviate traffic jams. Furthermore, the numerical simulations with periodic boundary conditions also confirm the effectiveness of theoretical results.

show abstract

“…Kuang et al [28] proposed a novel lattice hydrodynamic model with consideration of multi-anticipative average flux effect under ITS environment. With the development of connected automated vehicle (CAV) technologies, traffic information control and utilizations have become more widely investigated like cyber-physical system (CPS) with optimal transmission reliability enhancement mechanism (OTREM) [29], seamless connectivity-based message propagation mechanism (SC-MPM) in V2X communications, [30] and so on.…”

Section: Introductionmentioning

confidence: 99%

Study on Energy Dissipation and Fuel Consumption in Lattice Hydrodynamic Model under Traffic Control

Wen

Xue

Cen

et al. 2022

Mathematical Problems in Engineering

View full text Add to dashboard Cite

A lattice hydrodynamic traffic model considering the average optimal flow of multiple grids downstream as a feedback control is proposed. The energy dissipation and fuel consumption are investigated under the feedback control based on the lattice hydrodynamic traffic model. Through linear stability analysis, the stability condition of the model is obtained. The mKdV equation and its kink-antikink density wave solution are derived by using the reduced perturbation method of nonlinear analysis. The variation trends of density wave, energy dissipation, and fuel consumption under traffic control are studied by numerical simulations. The research shows that exerting the feedback control can effectively suppress traffic congestion and improve the stability of traffic system. Meanwhile, it can also reduce the energy dissipation and fuel consumption of traffic system.

show abstract

Low Delay and Seamless Connectivity-based Message Propagation Mechanism for VANET of VCPS

Cited by 16 publications

References 23 publications

Intelligent Traffic Model for Unmanned Ground Vehicles Based on DSDV-AODV Protocol

Intelligent Traffic Model for Unmanned Ground Vehicles Based on DSDV-AODV Protocol

A New Two-Lane Lattice Model with the Consideration of the Driver’s Self-Anticipation Current Difference Effect

Study on Energy Dissipation and Fuel Consumption in Lattice Hydrodynamic Model under Traffic Control

Contact Info

Product

Resources

About