A survey on context-aware vehicular network applications

Vahdat-Nejad, Hamed; Ramazani, Azam; Mohammadi, Tahereh; Mansoor, Wathiq

doi:10.1016/j.vehcom.2016.01.002

Cited by 92 publications

(63 citation statements)

References 27 publications

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“…The context is understood as "any information that can be used to characterize the situation of an entity. An entity is a person, place or object that is considered relevant to the interaction between a user and an application, including the user and the applications themselves" [32]. These systems are able to adapt, exploiting the knowledge acquired through sensors, other nodes or through the infrastructure available on the route.…”

Section: Context-aware Systemsmentioning

confidence: 99%

“…In vehicular environments, context-aware systems focus mainly on the area of service recognition and location on the route [34,35]. In [32], the authors describe various approaches that have used context-aware systems for the detection of specific events, for example in security, entertainment, and traffic management applications. To the best of our knowledge, there is only one work that has addressed the problem of disseminating information of accidents based on warning messages considering the information of the vehicular context [36]; however, the scheme does not consider the traffic of the communications network in the context definition.…”

Section: Context-aware Systemsmentioning

confidence: 99%

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A baseline for context-aware system for safety messages dissemination in VANETs

Yáñez

Céspedes

Rubio‐Loyola

2019

Rev.Fac.Ing.Univ.Antioquia

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Vehicular ad-hoc networks (VANETs) are mobile networks with highly dynamic contexts of operation. The design and application of context-aware systems could be critical to enhance the performance of protocols deployed in VANETs, which depend on both network and traffic conditions, to detect hostile communication environments, as well as to offer a novel way to make decisions in real-time. In this paper, we present a baseline study for the design of a context-aware system for dissemination of safety messages in VANETs. We model a realistic vehicular intersection and perform extensive simulations to evaluate two well-known dissemination mechanisms, namely the Slotted 1-persistence and the Traffic Adaptive Data Dissemination (TrAD) Protocol, with a set of parameters according to different operation scenarios. We show how the dissemination mechanisms’ performance could be improved, or worsened, by choosing a different set of parameter values. By characterizing the operation scenarios, it is possible to adequate the parameters of the dissemination mechanism with the values that work best in a given context, improving in this way the general performance of the dissemination mechanisms under study.

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Section: Context-aware Systemsmentioning

confidence: 99%

Section: Context-aware Systemsmentioning

confidence: 99%

A baseline for context-aware system for safety messages dissemination in VANETs

Yáñez

Céspedes

Rubio‐Loyola

2019

Rev.Fac.Ing.Univ.Antioquia

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“…However, autonomous vehicles will need to determine their real-time moving strategy and decisions depending on the dynamic surroundings, for which sensors installed on board are of utmost necessity, especially -yet not uniquely-for safety reasons. Indeed, a growing body of literature has emphasized the crucial role of vehicular sensors for the pre-collision detection of obstacles [2] and platooning, among many other applications [3], [4]. In this context, a vehicular sensor system is usually composed by light detection and ranging (LiDAR), radar, GPS, odometry, and computer vision devices.…”

Section: Introductionmentioning

confidence: 99%

Beyond WYSIWYG: Sharing contextual sensing data through mmWave V2V communications

Perfecto

Ser

Bennis

et al. 2017

2017 European Conference on Networks and Communications (EuCNC)

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Abstract-In vehicular scenarios context awareness is a key enabler for road safety. However, the amount of contextual information that can be collected by a vehicle is stringently limited by the sensor technology itself (e.g., line-of-sight, coverage, weather robustness) and by the low bandwidths offered by current wireless vehicular technologies such as DSRC/802.11p. Motivated by the upsurge of research around millimeter-wave vehicle-to-anything (V2X) communications, in this work we propose a distributed vehicle-to-vehicle (V2V) association scheme that considers a quantitative measure of the potential value of the shared contextual information in the pairing process. First, we properly define the utility function of every vehicle balancing classical channel state and queuing state information (CSI/QSI) with context information i.e., sensing content resolution, timeliness and enhanced range of the sensing. Next we solve the problem via a distributed many-to-one matching game in a junction scenario with realistic vehicular mobility traces. It is shown that when receivers are able to leverage information from different sources, the average volume of collected extended sensed information under our proposed scheme is up to 71% more than that of distance and minimum delay-based matching baselines.

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“…These accidents are also the main cause of traffic congestion, which in turn has a great impact on the economy [3,4], and billions of dollars are lost due to the treatment of injuries, loss of property, lost working hours, and high fuel consumption [5]. Several studies reveal that more than 95% of accidents are attributed to human error that can be avoided if the drivers had been warned half a second beforehand [6]. Vehicular ad hoc networks (VANETs) have emerged, mainly to reduce those accidents, improve road safety and traffic efficiency, and provide user comfort [7].…”

mentioning

confidence: 99%

“…These applications have a huge potential to save tens of thousands of lives and billions of dollars each year [16]. An extensive review of VANET applications can be found in References [6,17]. With such applications, vehicle automation will become a reality, such that human error will be minimized, and the vehicles can navigate safely even under hazardous and dangerous traffic conditions such as fog, black ice, and accidents.…”

mentioning

confidence: 99%

Ensemble-Based Hybrid Context-Aware Misbehavior Detection Model for Vehicular Ad Hoc Network

et al. 2019

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Life-saving decisions in vehicular ad hoc networks (VANETs) depend on the availability of highly accurate, up-to-date, and reliable data exchanged by neighboring vehicles. However, spreading inaccurate, unreliable, and false data by intruders create traffic illusions that may cause loss of lives and assets. Although several solutions for misbehavior detection have been proposed to address these issues, those solutions lack adequate representation and the adaptability to vehicular context. The use of predefined static thresholds and lack of comprehensive context representation have rendered the existing solutions limited to specific scenarios and attack types, which impedes their generalizability. This paper addresses these limitations by proposing an ensemble-based hybrid context-aware misbehavior detection system (EHCA-MDS) model. EHCA-MDS has been developed in four phases, as follows. The static thresholds have been replaced by dynamic ones created on the fly by analyzing the spatial and temporal properties of the mobility information collected from neighboring vehicles. Kalman filter-based algorithms were used to collect the mobility information of neighboring vehicles. Three sets of features were then derived, each of which has a different perspective, namely data consistency, data plausibility, and vehicle behavior. These features were used to construct a dynamic context reference using the Hampel filter. The Hampel-based z-score was used to evaluate the vehicles based on their behavioral activities, data consistency, and plausibility. For comprehensive features representation, multifaceted, non-parametric-based statistical classifiers were constructed and updated online using a Hampel filter-based algorithm. For accurate representation, the output of the statistical classifiers, vehicles' scores, context reference parameters, and the derived features were used as input to an ensemble learning-based algorithm. Such representation helps to identify the misbehaving vehicles more effectively. The proposed EHCA-MDS model was evaluated in the presence of different types of misbehaving vehicles under different context scenarios through extensive simulations, utilizing a real-world traffic dataset. The results show that the accuracy and robustness of the proposed EHCA-MDS under different vehicular dynamic context scenarios were higher than existing solutions, which confirms its feasibility and effectiveness to improve the performance of VANET critical applications. IntroductionRoad collisions are increasing, and they are being expected to be the fifth leading cause of death by 2030 [1,2]. Annually, millions of people lose their lives on roads worldwide due to traffic accidents [1], with 40 times more suffering from injuries. These accidents are also the main cause of traffic congestion, which in turn has a great impact on the economy [3,4], and billions of dollars are lost due to the treatment of injuries, loss of property, lost working hours, and high fuel consumption [5]. Several studies reveal that more than 95%...

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A survey on context-aware vehicular network applications

Cited by 92 publications

References 27 publications

A baseline for context-aware system for safety messages dissemination in VANETs

A baseline for context-aware system for safety messages dissemination in VANETs

Beyond WYSIWYG: Sharing contextual sensing data through mmWave V2V communications

Ensemble-Based Hybrid Context-Aware Misbehavior Detection Model for Vehicular Ad Hoc Network

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