An Ontology for Collaborative Navigation Among Autonomous Cars, Drivers, and Pedestrians in Smart Cities

Syzdykbayev, Meirman; Hajari, Hadi; Karimi, Hassan A.

doi:10.23919/splitech.2019.8783045

Cited by 9 publications

(4 citation statements)

References 10 publications

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“…Benevolo, Dameri, and D’auria (2016) analyze the smart mobility initiatives like part of a larger smart city initiative portfolio and investigate about the role of ICT in supporting smart mobility actions, influencing their impact on the citizens’ quality of life and on the public value created for the city as a whole. Ontologies on smart mobility reported in the literature are very specific and focus on topics such as knowledge for collaboration among travelers and the surrounding infrastructure using advanced navigation systems (Syzdykbayev, Hajari, and Karimi 2019) and management of semantic locations and trajectories (Ilarri, Stojanovic, and Ray 2015).…”

Section: Discussionmentioning

confidence: 99%

Systematic Literature Review on Smart Mobility: A Framework for Future “Quantitative” Developments

Francini

Chieffallo

Palermo

et al. 2021

Journal of Planning Literature

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This work aims to reorganize theoretical and empirical research on smart mobility through the systematic literature review approach. The research goal is to reach an extended and shared definition of smart mobility using the cluster analysis. The article provides a summary of the state of the art that can have broader impacts in determining new angles for approaching research. In particular, the results will be a reference for future quantitative developments for the authors who are working on the construction of a territorial measurement model of the smartness degree, helping them in identifying performance indicators consistent with the definition proposed.

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Section: Discussionmentioning

confidence: 99%

Systematic Literature Review on Smart Mobility: A Framework for Future “Quantitative” Developments

Francini

Chieffallo

Palermo

et al. 2021

Journal of Planning Literature

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show abstract

“…Syzdykbayev et al [13] presented an ontology specifically tailored for collaborative navigation within the context of autonomous cars, drivers, and pedestrians in smart cities. This ontology served as a comprehensive representation of the pertinent concepts, relationships, and rules associated with navigation in a collaborative setting.…”

Section: Traffic Ontologies In Smart City Domainmentioning

confidence: 99%

An Ontological Model to Enhance Traffic Conditions in Smart City Domain

Saafi,

Dhouib

2024

Spec. Eng. Man. Sci.

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The rising trend of the increasing interconnection of city services refers to the growing integration and interconnectedness of various urban systems and services through the utilization of technology and data. One of the primary objectives of smart city initiatives is to establish more efficient and sustainable urban environments by optimizing resource utilization and infrastructure. In this paper, we introduce a traffic ontology named "TrafCsOnto," which encompasses a comprehensive range of traffic concepts. The primary aim of this ontology is to address traffic congestion issues within the smart city context. The formalization of this ontology has been carried out using the OWL language and the protégé tool. We endeavor to illustrate the practical application of the traffic ontology through the manipulation of real-world instances and inferences.

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“…Among the various ontologies to which we referred, we considered those made available by the Automotive Ontology Community Group, the W3C working group and a group of domain experts of University of Salerno. Other reference ontologies taken into consideration were those present in the research in [50][51][52]. Once the context was identified, it was necessary to define the taxonomy of a car to identify the characteristics of the system and the identification of the parameters to be monitored.…”

Section: Case Of Studymentioning

confidence: 99%

Cybersecurity in Automotive: An Intrusion Detection System in Connected Vehicles

2021

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Today’s modern vehicles are connected to a network and are considered smart objects of IoT, thanks to the capability to send and receive data from the network. One of the greatest challenges in the automotive sector is to make the vehicle secure and reliable. In fact, there are more connected instruments on a vehicle, such as the infotainment system and/or data interchange systems. Indeed, with the advent of new paradigms, such as Smart City and Smart Road, the vision of Internet of Things has evolved substantially. Today, we talk about the V2X systems in which the vehicle is strongly connected with the rest of the world. In this scenario, the main aim of all connected vehicles vendors is to provide a secure system to guarantee the safety of the drive and persons against a possible cyber-attack. So, in this paper, an embedded Intrusion Detection System (IDS) for the automotive sector is introduced. It works by adopting a two-step algorithm that provides detection of a possible cyber-attack. In the first step, the methodology provides a filter of all the messages on the Controller Area Network (CAN-Bus) thanks to the use of a spatial and temporal analysis; if a set of messages are possibly malicious, these are analyzed by a Bayesian network, which gives the probability that a given event can be classified as an attack. To evaluate the efficiency and effectiveness of our method, an experimental campaign was conducted to evaluate them, according to the classic evaluation parameters for a test’s accuracy. These results were compared with a common data set on cyber-attacks present in the literature. The first experimental results, obtained in a test scenario, seem to be interesting. The results show that our method has good correspondence in the presence of the most common cyber-attacks (DDoS, Fuzzy, Impersonating), obtaining a good score relative to the classic evaluation parameters for a test’s accuracy. These results have decreased performance when we test the system on a Free State Attack.

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An Ontology for Collaborative Navigation Among Autonomous Cars, Drivers, and Pedestrians in Smart Cities

Cited by 9 publications

References 10 publications

Systematic Literature Review on Smart Mobility: A Framework for Future “Quantitative” Developments

Systematic Literature Review on Smart Mobility: A Framework for Future “Quantitative” Developments

An Ontological Model to Enhance Traffic Conditions in Smart City Domain

Cybersecurity in Automotive: An Intrusion Detection System in Connected Vehicles

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