Geometry-Based Localization for GPS Outage in Vehicular Cyber Physical Systems

Kaiwartya, Omprakash; Cao, Yue; Lloret, Jaime; Kumar, Sushil; Aslam, Nauman; Kharel, Rupak; Abdullah, Abdul Hanan; Shah, Rajiv Ratn

doi:10.1109/tvt.2018.2796242

Cited by 63 publications

(32 citation statements)

References 26 publications

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“…However, the actual embedded cellular technology (4G) does not allow V2X communication, yet, but only communications through the eNodeB, thus with a latency which could be critical for VRUs' safety applications [65]. When V2P communication is addressed, another important aspect to be carefully considered is positioning, since the global positioning system (GPS) accuracy and the accuracy of the combination of different sensors, even if suitable for different ranges and weather conditions, is not sufficient [66,67]. Actual cellular positioning also provides poor accuracy, but this could be (at least partially) overcome with the introduction of 5G wireless communication systems introducing MIMO systems at mmWave [68].…”

Section: Pedestrian Detectionmentioning

confidence: 99%

The Use of Meta-Surfaces in Vehicular Networks

Masini

Silva

Balador

2020

JSAN

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Mobility as a service is becoming a new paradigm in the direction of travel planning on the basis of the best service offered by the travelled roads. Hence, the environment in which people move will become smarter and more and more connected to grant services along the whole path. This opens new challenges related not only to the on board connectivity and wireless access technologies, but also on the reliability and efficiency of the surrounding environment. In this context, reconfigurable meta-surfaces play a crucial role, since they can be used to coat buildings, vehicles or any other suitable surfaces and let the environment become an active part of the communication system by opportunistically redirecting (i.e., reflecting, without generating new waves) signals to the target receivers. The objective of this paper is to highlight the limits of current wireless access technologies for vehicular scenarios and to discuss the potential impact of a smart environment made of reconfigurable meta-surfaces on some next generation vehicular use cases, such as cooperative driving and vulnerable road users (VRUs) detection. In addition, a preliminary model is presented to derive, in a simplified way, the performance of an IEEE 802.11p network in terms of collision probability. Even if analytical and based on simplified assumptions, this model has been validated through simulations and allows to compare the performance of the network with and without reconfigurable meta-surfaces.

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Section: Pedestrian Detectionmentioning

confidence: 99%

The Use of Meta-Surfaces in Vehicular Networks

Masini

Silva

Balador

2020

JSAN

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“…A geometry-based localization (GeoLV) for GPS outage scenarios was proposed by Kaiwartya et al [21]. They solved the problem of GPS outage in both short and long outage periods through the equation of a circle and the intersection between the circle and a line to estimate the vehicle’s location more accurately.…”

Section: Related Workmentioning

confidence: 99%

Cooperative Localization Improvement Using Distance Information in Vehicular Ad Hoc Networks

Lobo

Grael

Oliveira

et al. 2019

Sensors

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In vehicular ad hoc networks (VANets), a precise localization system is a crucial factor for several critical safety applications. The global positioning system (GPS) is commonly used to determine the vehicles’ position estimation. However, it has unwanted errors yet that can be worse in some areas, such as urban street canyons and indoor parking lots, making it inaccurate for most critical safety applications. In this work, we present a new position estimation method called cooperative vehicle localization improvement using distance information (CoVaLID), which improves GPS positions of nearby vehicles and minimize their errors through an extended Kalman filter to execute Data Fusion using GPS and distance information. Our solution also uses distance information to assess the position accuracy related to three different aspects: the number of vehicles, vehicle trajectory, and distance information error. For that purpose, we use a weighted average method to put more confidence in distance information given by neighbors closer to the target. We implement and evaluate the performance of CoVaLID using real-world data, as well as discuss the impact of different distance sensors in our proposed solution. Our results clearly show that CoVaLID is capable of reducing the GPS error by 63%, and 53% when compared to the state-of-the-art VANet location improve (VLOCI) algorithm.

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“…The protocol limitation also included an absence in optimize real-time vehicular traffic environment information processing. In [25], the authors proposed a geometry-based localization for GPS outage in a vehicular cyber physical system (VCPS) (GeoLV) for network level security protection only. The proposed localization technique was a GPS assisted localization which has the tendency to reduce location aware neighbor constraints in cooperative localization.…”

Section: Securing Vanets-centralized Architecturementioning

confidence: 99%

Secure Intelligent Vehicular Network Using Fog Computing

Erskine

Elleithy

2019

Electronics

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VANET (vehicular ad hoc network) has a main objective to improve driver safety and traffic efficiency. The intermittent exchange of real-time safety message delivery in VANET has become an urgent concern due to DoS (denial of service) and smart and normal intrusions (SNI) attacks. The intermittent communication of VANET generates huge amount of data which requires typical storage and intelligence infrastructure. Fog computing (FC) plays an important role in storage, computation, and communication needs. In this research, fog computing (FC) integrates with hybrid optimization algorithms (OAs) including the Cuckoo search algorithm (CSA), firefly algorithm (FA), firefly neural network, and the key distribution establishment (KDE) for authenticating both the network level and the node level against all attacks for trustworthiness in VANET. The proposed scheme is termed “Secure Intelligent Vehicular Network using fog computing” (SIVNFC). A feedforward back propagation neural network (FFBP-NN), also termed the firefly neural, is used as a classifier to distinguish between the attacking vehicles and genuine vehicles. The SIVNFC scheme is compared with the Cuckoo, the FA, and the firefly neural network to evaluate the quality of services (QoS) parameters such as jitter and throughput.

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Geometry-Based Localization for GPS Outage in Vehicular Cyber Physical Systems

Cited by 63 publications

References 26 publications

The Use of Meta-Surfaces in Vehicular Networks

The Use of Meta-Surfaces in Vehicular Networks

Cooperative Localization Improvement Using Distance Information in Vehicular Ad Hoc Networks

Secure Intelligent Vehicular Network Using Fog Computing

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