Lina Altoaimy

Weighted localization in vehicular ad hoc networks using vehicle-to-vehicle communication

 

L. Altoaimy, I. Mahgoub, and M. Rathod, “Weighted localization in vehicular ad hoc networks using vehicle-to-vehicle communication,” in Global Information Infrastructure and Networking Symposium (GIIS), 2014, Sept 2014, pp. 1–5.

Vehicular Ad Hoc Networks (VANETs) have attracted the interest of many researchers all over the world. With advances in technologies in wireless networks, vehicles will be able to communicate with each other and roadside units (RSU), to exchange road and traffic information. VANET and many other applications demand a real-time, accurate position of a vehicle; highlighting the importance of accurate localization. A number of methods and protocols have been proposed to fulfill this requirement, However, they have not attained high location accuracy required for VANET safety applications. 

We propose two new localization methods that assist vehicles in estimating their positions: 1) weighted localization (WL) using signal to interference-noise ratio (SINR) obtained from the exchange messages, and 2) weighted localization using SINR and distance between the neighboring vehicles (WLD).  Our methods expand the concept of centroid localization (CL) by assigning a weight to each of the neighboring vehicles' coordinates, based on SINR values and the distance. We develop a simulation program to evaluate our methods against CL and relative span weighted localization (RWL). Our simulation results show that WLD demonstrates a better performance with less average location errors than CL and RWL in varying of densities.  

 

OWL: optimized weighted localization for vehicular ad hoc networks

 

L. Altoaimy and I. Mahgoub, “OWL: optimized weighted localization for vehicular ad hoc networks,” in 2014 International Conference on Connected Vehicles & Expo (ICCVE), Vienna, Austria, Nov. 2014, pp. 699–704.

 

Vehicular Ad Hoc Networks (VANETs) allows the exchange of messages between neighboring vehicles or roadside units (RSU). The performance of VANET applications is subject to the ability of determining the location of the vehicles at anytime and anywhere within the network, and thus demands real-time, precise position of vehicles. Accordingly, a number of methods and protocols have been proposed to fulfill this requirement, however, the accuracy of the obtained location is not sufficient for VANET safety applications. 

We propose an enhancement to our previous localization method, weighted localization using distance information (WLD), that uses signal to interference-noise ratio (SINR) obtained from the exchange messages, and distance between the neighboring vehicles to assist vehicles in estimating their positions. Our proposed optimized weighted localization (OWL) uses the heading information shared by the neighboring vehicles in addition to the SINR and distance information.  Our proposed method is an extension to centroid localization (CL) with a weight assigned to each of the neighboring vehicles' coordinates, based on SINR values, distance and heading. We implement a simulation program to evaluate the proposed method against CL, WLD and relative span weighted localization (RWL). The results show the proposed method to have better performance and consistently less average location errors in varying densities.  

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