Vehicular networks on two Madrid highways

Recent advances in vehicular networks have enforced researchers to focus on various information dissemination techniques. Exchanging information among the vehicles is imperative due to the ever-changing network topology in vehicular networks. However, random transmitter selection in traditional CSMA based channel access mechanism limits the delay performance. Data, such as state information, is often time critical, and hence, efficient information dissemination techniques to improve delay performance are essential. In this work, we aim to minimize the average system age which is the mean number of time slots old a vehicle's information is at all other vehicles in the network. To achieve this, we explore the benefits of simultaneous transmission along with piggybacking of information for multi-hop communication. While allowing simultaneous transmission guarantees faster dissemination of information, piggybacking facilitates dissemination of more information per transmission, thereby keeping the network more updated. We have also analysed the relationship between piggybacked information and number of vehicles in the network. Simulation results show improvement in network performance. Our analytical results are in good agreement with the simulation results.

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“…Results are obtained using a discrete event simulator averaged over 1000 simulation runs. The simulation parameters are shown in Table 2 [5,30].…”

Section: Simulation Results and Discussionmentioning

confidence: 99%

On minimizing the system information age in vehicular ad-hoc networks via efficient scheduling and piggybacking

2015

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“…Constrained-SOM, conventional SOM, and DLEA were used to estimate vehicle locations by using the GPS fixes and the alternative inter-vehicular distances. 41,42 Considering factors such as safety requirement and lane change, the accuracy and speed of vehicle positioning method in the automatic driving system are high. 36,37 The GPS errors were generated by a zero mean Gaussian distribution with 15 m variance.…”

Section: Simulation Settingsmentioning

confidence: 99%

Improving positioning accuracy based on self‐organizing map (SOM) and inter‐vehicular communication

Lee

2019

Trans Emerging Tel Tech

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Low‐cost global positioning system (GPS) receivers installed in most vehicles and smart devices typically display tens of meters of error in their location data. A large amount of research effort has been made to increase the positioning accuracy of GPS receivers mostly by reducing errors with the help of auxiliary devices and/or methodologies such as differential GPSs, assisted GPSs, real‐time kinematic positioning, computer vision, etc, which result in a certain amount of cost increase. In this paper, we propose a new cooperative vehicular localization scheme based on vehicle‐to‐vehicle communication. The proposed scheme first estimates the distances between neighboring vehicles using the weighted least square of double difference scheme and uses a novel machine learning technique called constrained self‐organizing map (C‐SOM) with a set of adjusted GPS fixes to generate the final estimates of GPS locations with considerably lower errors. We also propose a new method of presenting training samples to address the issue of convergence failure that arises from the constraints imposed on the inter‐vehicular distances. We present simulation results that demonstrate the superior performance of the proposed scheme over both the conventional SOM and the distributed location estimate algorithm.

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“…One was the time complexity of querying functions; the other was time complexity between the proposed model and the absolute method in ArcGIS Geodatabase. This study used a dataset (Gramaglia et al, 2014) of vehicle trajectories on two highways around Madrid, Spain. The detailed information in these trajectories contained five fields (time, ID, X position (m), Y position (m) and speed (m/s)).…”

Section: Performance Testingmentioning

confidence: 99%

Relative space-based GIS data model to analyze the group dynamics of moving objects

Feng

Shaw

Fang

et al. 2019

ISPRS Journal of Photogrammetry and Remote Sensing

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The relative motion of moving objects is an essential research topic in geographical information science (GIScience), which supports the innovation of geodatabases, spatial indexing, and geospatial services. This analysis is very popular in the domains of urban governance, transportation engineering, logistics and geospatial information services for individuals or industrials. Importantly, data models of moving objects are one of the most crucial approaches to support the analysis for dynamic relative motion between moving objects, even in the age of big data and cloud computing. Traditional geographic information systems (GIS) usually organize moving objects as point objects in absolute coordinated space. The derivation of relative motions among moving objects is not efficient because of the additional geo-computation of transformation between absolute space and relative space. Therefore, current GISs require an innovative approach to directly store, analyze and interpret the relative relationships of moving objects to support their efficient analysis. This paper proposes a relative space-based GIS data model of moving objects (RSMO) to construct, operate and analyze moving objects' relationships and introduces two algorithms (relationship querying and relative relationship dynamic pattern matching) to derive and analyze the dynamic relationships of moving objects. Three scenarios (epidemic spreading, tracker finding, and motion-trend derivation of nearby crowds) are implemented to demonstrate the feasibility of the proposed model. The experimental results indicates the execution times of the proposed model are approximately 5-50% those of the absolute GIS method for the same function of these three scenarios. It's better computational performance of the proposed model when analyzing the relative relationships of moving objects than the absolute methods in a famous commercial GIS software based on this experimental results. The proposed approach fills the gap of traditional GIS and shows promise for relative space-based geo-computation, analysis and service.

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Vehicular networks on two Madrid highways

Cited by 44 publications

References 25 publications

On minimizing the system information age in vehicular ad-hoc networks via efficient scheduling and piggybacking

On minimizing the system information age in vehicular ad-hoc networks via efficient scheduling and piggybacking

Improving positioning accuracy based on self‐organizing map (SOM) and inter‐vehicular communication

Relative space-based GIS data model to analyze the group dynamics of moving objects

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