scholarly journals A Cooperative Localization Method based on V2I Communication and Distance Information in Vehicular Networks

2021 ◽  
Vol 13 (6) ◽  
pp. 53-71
Author(s):  
Walaa Afifi ◽  
Hesham A. Hefny ◽  
Nagy R. Darwish
Keyword(s):  
Vehicular Networks ◽  
Position Vector ◽  
Cooperative Localization ◽  
Research Papers ◽  
Distance Information ◽  
Localization Method ◽  
Nonlinear Localization ◽  
Roadside Unit ◽  
Kalman Filter Algorithm ◽  
Adaptive Noise

Relative positions are recent solutions to overcome the limited accuracy of GPS in urban environment. Vehicle positions obtained using V2I communication are more accurate because the known roadside unit (RSU) locations help predict errors in measurements over time. The accuracy of vehicle positions depends more on the number of RSUs; however, the high installation cost limits the use of this approach. It also depends on nonlinear localization nature. They were neglected in several research papers. In these studies, the accumulated errors increased with time due to the linearity localization problem. In the present study, a cooperative localization method based on V2I communication and distance information in vehicular networks is proposed for improving the estimates of vehicles’ initial positions. This method assumes that the virtual RSUs based on mobility measurements help reduce installation costs and facilitate in handling fault environments. The extended Kalman filter algorithm is a well-known estimator in nonlinear problem, but it requires well initial vehicle position vector and adaptive noise in measurements. Using the proposed method, vehicles’ initial positions can be estimated accurately. The experimental results confirm that the proposed method has superior accuracy than existing methods, giving a root mean square error of approximately 1 m. In addition, it is shown that virtual RSUs can assist in estimating initial positions in fault environments.

Single Beacon Indoor Localization System Based on Counter-Synchronized Compass and RSSI

2014 ◽  
Vol 627 ◽  
pp. 217-222
Author(s):  
Kok Seng Eu ◽  
Kian Meng Yap ◽  
Tiam Hee Tee
Keyword(s):  
Indoor Localization ◽  
Target Item ◽  
Optimal Solution ◽  
Research Area ◽  
Target Object ◽  
Localization Algorithm ◽  
Distance Information ◽  
Localization Method ◽  
Localization System ◽  
Lost And Found

Indoor localization system has been a popular research area in recent decades and many of them are based on multiple beacons localization method. However, there are some special applications to which the multiple beacons method is not an optimal solution due to its overdesign and cost of redundancy. Multiple beacons method uses at least three transducers and each transducer’s location must be known to find the location of a target object by using either Triangulation or Trilateration calculation. When the multiple beacons method is applied in an items lost and found system, the precise Cartesian coordinates of a target item can be found, but it is definitely overdesign and incurring redundant cost. It is due to the fact that the target item requires only two simple information i.e. Clock orientation and distance information; therefore, single beacon is enough for the task. In this paper, we propose a single beacon localization method to optimize the solution in the items lost and found system by utilizing clock orientation and estimated distance information. The proposed single beacon localization algorithm has been demonstrated and proven that it can be one of the optimal solutions for items lost and found system.

scholarly journals A Distributed Cooperative Localization Strategy in Vehicular-to-Vehicular Networks

Sensors ◽  
2020 ◽  
Vol 20 (5) ◽  
pp. 1413 ◽  
Author(s):  
Minji Kim ◽  
Hong Ki Kim ◽  
Sang Hyun Lee
Keyword(s):  
Message Passing ◽  
Vehicular Networks ◽  
Initial Position ◽  
Design Parameters ◽  
Measurement Information ◽  
Cooperative Localization ◽  
Angle Of Arrival ◽  
Position Information ◽  
Localization Strategy ◽  
Vehicle Networks

This work develops a distributed message-passing approach to cooperative localization for autonomous mobile vehicles that communicate via mm-wave wireless connection in vehicle-to-vehicle networks. Vehicles in the network obtain the measurement information about the relative distance and the angle of arrival from the mm-wave connections made with each other. Some vehicles may obtain knowledge about their absolute position information of different quality, for example, via additional localization feature. The main objective is to estimate the locations of all vehicles using reciprocal exchanges of simple information called a message in a distributed and autonomous way. A simulation is developed to examine the performance of the localization and navigation of vehicles under various network configurations. The results show that it does provide better positioning results in most cases and there are also several cases where the use of the cooperative technique adapts to design parameters such as accuracies of measurement equipment, and initial position estimates, that can affect the localization performance.

A Roadside Unit-Based Localization Scheme to Improve Positioning for Vehicular Networks

2016 ◽  
Author(s):  
Frances A. Santos ◽  
Ademar T. Akabane ◽  
Roberto S. Yokoyama ◽  
Antonio A. F. Loureiro ◽  
Leandro A. Villas
Keyword(s):  
Vehicular Networks ◽  
Localization Scheme ◽  
Roadside Unit

scholarly journals Applications of intelligent computing in vehicular networks

2018 ◽  
Vol 1 (2) ◽  
pp. 66-76
Author(s):  
Daxin Tian ◽  
Weiqiang Gong ◽  
Wenhao Liu ◽  
Xuting Duan ◽  
Yukai Zhu ◽  
...  
Keyword(s):  
Vehicular Networks ◽  
Routing Algorithm ◽  
Cooperative Localization ◽  
Localization Algorithm ◽  
Algorithm Optimization ◽  
Content Type ◽  
Intelligent Computing ◽  
Network Platform ◽  
Vehicle Positioning ◽  
Vehicle Networking

Purpose This paper aims to introduce vehicular network platform, routing and broadcasting methods and vehicular positioning enhancement technology, which are three aspects of the applications of intelligent computing in vehicular networks. From this paper, the role of intelligent algorithm in the field of transportation and the vehicular networks can be understood. Design/methodology/approach In this paper, the authors introduce three different methods in three layers of vehicle networking, which are data cleaning based on machine learning, routing algorithm based on epidemic model and cooperative localization algorithm based on the connect vehicles. Findings In Section 2, a novel classification-based framework is proposed to efficiently assess the data quality and screen out the abnormal vehicles in database. In Section 3, the authors can find when traffic conditions varied from free flow to congestion, the number of message copies increased dramatically and the reachability also improved. The error of vehicle positioning is reduced by 35.39% based on the CV-IMM-EKF in Section 4. Finally, it can be concluded that the intelligent computing in the vehicle network system is effective, and it will improve the development of the car networking system. Originality/value This paper reviews the research of intelligent algorithms in three related areas of vehicle networking. In the field of vehicle networking, these research results are conducive to promoting data processing and algorithm optimization, and it may lay the foundation for the new methods.

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