Reliable Vehicle-to-Vehicle Weighted Localization in Vehicular Networks

Vehicular Ad Hoc Network (VANET) supports wireless communication among vehicles using vehicle-to-vehicle (V2V) communication and between vehicles and infrastructure using vehicle-to-infrastructure (V2I) communication. This communication can be utilized to allow the distribution of safety and non-safety messages in the network. VANET supports a wide range of applications which rely on the messages exchanged within the network. Such applications will enhance the drivers' consciousness and improve their driving experience. However, the efficiency of these applications depends on the availability of vehicles real-time location information. A number of methods have been proposed to fulfill this requirement. However, designing a V2V-based localization method is challenged by the high mobility and dynamic topology of VANET and the interference noise due to objects and buildings. Currently, vehicle localization is based on GPS technology, which is not always reliable. Therefore, utilizing V2V communication in VANET can enhance the GPS positioning. With V2V-based localization, vehicles can determine their locations by exchanging mobility data among neighboring vehicles. In this research work, we address the above challenges and design a realistic V2V-based localization method that extends the centroid localization (CL) by assigning a weight value to each neighboring vehicle. This weight value is obtained using a weighting function that utilizes the following factors: 1) link quality distance between the neighboring vehicles 2) heading information and 3) map information. We also use fuzzy logic to model neighboring vehicles' weight values. Due to the sensitivity and importance of the exchanged information, it is very critical to ensure its integrity and reliability. Therefore, in this work, we present the design and the integration of a mobility data verification component into the proposed localization method, so that only verified data from trusted neighboring vehicles are considered. We also use subjective logic to design a trust management system to evaluate the trustworthiness of neighboring vehicles based on the formulated subjective opinions. Extensive experimental work is conducted using simulation programs to evaluate the performance of the proposed methods. The results show improvement on the location accuracy for varying vehicle densities and transmission ranges as well as in the presence of malicious/untrusted neighboring vehicles.