Intelligent Transport System in Smart Cities

Meneguette, Rodolfo I.; Grande, Robson E. De; Loureiro, Antônio A. F.

doi:10.1007/978-3-319-93332-0

Cited by 67 publications

(63 citation statements)

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“…In the future, the transportation system may be more efficient and safer due to the emergence of new modes of travel, such as autonomous ridesharing, autonomous buses, autonomous shuttles [6,7], etc. AVs can obtain road warning and traffic information in real time through the V2X technology, which improves driving safety [8]. The V2X also enables in-car online entertainment, which gives passengers a comfortable trip [4].…”

Section: Introductionmentioning

confidence: 99%

The Determinants behind the Acceptance of Autonomous Vehicles: A Systematic Review

et al. 2020

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Excessive dependence on autonomous vehicles (AVs) may exacerbate traffic congestion and increase exhaust emissions in the future. The diffusion of AVs may be significantly affected by the public’s acceptance. A few factors that may affect people’s acceptance of AVs have been researched in the existing studies, one-third of which cited behavioral theories, while the rest did not. A total of seven factors with behavior theories are screened out that significantly affect the acceptance intention, including perceived ease of use, attitude, social norm, trust, perceived usefulness, perceived risk, and compatibility. Six factors without behavior theories are summed up that affect AV acceptance, namely safety, performance-to-price value, mobility, value of travel time, symbolic value, and environmentally friendly. We found that people in Europe and Asia have substantial differences in attitudes toward AVs and that safety is one of the most concerned factors of AVs by scholars and respondents. Public acceptance of the different types of AVs and consumers’ dynamic preferences for AVs are highlighted in the review too. The quality of literature is systematically assessed based on previously established instruments and tailored for the current review. The results of the assessment show potential opportunities for future research, such as the citation of behavior theories and access to longitudinal data. Additionally, the experimental methods and the utilization of mathematical and theoretical methods could be optimized.

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Section: Introductionmentioning

confidence: 99%

The Determinants behind the Acceptance of Autonomous Vehicles: A Systematic Review

et al. 2020

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“…Smart cities have been studied by a broad of disciplines, such as urban planning, transportation, civil engineering, information science, surveying and mapping, commercial and logistics, energy, atmosphere and environment, society, tourists, governance, and industry. Many researchers have reviewed the literature related to smart cities [1][2][3][4][5][6][7][8][9][10][28][29][30][31][32][33][34][35][36][37]. It could be summarized as three important aspects, namely, infrastructure, service, and culture.…”

Section: Related Workmentioning

confidence: 99%

“…The magnificent goals of smart cities include quality of life, sustainability, and development [1], which have already attracted a great deal of attention from researchers in an array of disciplines, such as urban planning [2][3][4], transportation [5][6][7], civil engineering [8], information science [9][10][11][12][13], surveying and mapping [14,15], commercial and logistics [16], energy [17,18], atmosphere and environment [19], society [20,21], tourists [22], governance [2,23], and industry in recent years. Although the proper definition of smart cities are still lacking [2], smart cities' goals are consistent to include smart living, smart people, smart environment, smart mobility, smart economy, smart governance [24], smart services, and smart infrastructure [25].…”

Section: Introductionmentioning

confidence: 99%

People-Centric Service Intelligence for Smart Cities

Hong

Geng

2019

Smart Cities

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In the era of big data, smart cities have become a promising prospect for governments, citizens, and industrials. Many ideas and their derived systems for smart cities depend on big data for achieving a goal of data intelligence. However, there is an urgent transformation trend from data intelligence to service intelligence in the vision of smart cities due to the living requirements of citizens. People-centric service intelligence in smart cities has to support the realization of people’s needs within urban and social domains. This paper introduces a concept of people-centric service intelligence, defines the level of it and its challenges in the aspect of infrastructure, human dynamics, human understanding and prediction, and the human–machine interface. Then, this paper proposes the theoretical framework and technical frameworks of people-centric service intelligence, and the service intelligence schemas for future construction of smart cities. It will be helpful for governments and industries to design people-centric service intelligence for improving the quality of life, the capabilities of good sustainability, and better development.

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“…The bootstrapping of the vOBUs is depicted in Figure 2 on the left (orange color). Upon starting up the physical OBU, if it is the first time that the unit connects with the platform, a vOBUrequest is sent to the well-known address or domain name of the OBU manager (1). Considering that there is not a vOBU allocated for the OBU, a new one is required to OSM using its northbound interface (2).…”

Section: Deployment and Operation Of The Solutionmentioning

confidence: 99%

“…In vehicular scenarios, on-board units (OBU) have evolved from specific purpose units designed for telematic services, such as fleet management or road tolling, to generic networked nodes capable of interconnecting other in-vehicle devices, acting as mobile routers. These units can maintain connectivity with the infrastructure (Vehicle-to-Infrastructure, V2I) or other vehicles (Vehicle-to-Vehicle, V2V) using wireless communications, and the access to in-vehicle sensor data is becoming of paramount importance in Smart City scenarios, where the vehicle will be considered another (mobile) sensor [1] The arrival of 5G technologies will complement already available communication technologies, such as 4G or IEEE 802.11 running Outside the Context of a Basic Service Set (OCB), formerly known as 802.11p. Virtualization, network orchestration, and multi-access edge computing (MEC) are novel strategies that can provide great benefits for Cooperative Intelligent Transportation Systems (C-ITS) [2].…”

Section: Introductionmentioning

confidence: 99%

SURROGATES: Virtual OBUs to Foster 5G Vehicular Services

et al. 2019

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Virtualization technologies are key enablers of softwarized 5G networks, and their usage in the vehicular domain can provide flexibility and reliability in real deployments, where mobility and processing needs may be an issue. Next-generation vehicular services, such as the ones in the area of urban mobility and, in general, those interconnecting on-board sensors, require continuous data gathering and processing, but current architectures are stratified in two-tier solutions in which data is collected by on-board units (OBU) and sent to cloud servers. In this line, intermediate cache and processing layers are needed in order to cover quasi-ubiquitous data-gathering needs of vehicles in scenarios of smart cities/roads considering vehicles as moving sensors. The SURROGATES solution presented in this paper proposes to virtualize vehicle OBUs and create a novel Multi-Access Edge Computing (MEC) layer with the aim of offloading processing from the vehicle and serving data-access requests. This deals with potential disconnection periods of vehicles, saves radio resources when accessing the physical OBU and improves data processing performance. A proof of concept has been implemented using OpenStack and Open Source MANO to virtualize resources and gather data from in-vehicle sensors, and a final traffic monitoring service has been implemented to validate the proposal. Performance results reveal a speedup of more than 50% in the data request resolution, with consequently great savings of network resources in the wireless segment. Thus, this work opens a novel path regarding the virtualization of end-devices in the Intelligent Transportation Systems (ITS) ecosystem.

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Intelligent Transport System in Smart Cities

Cited by 67 publications

References 0 publications

The Determinants behind the Acceptance of Autonomous Vehicles: A Systematic Review

The Determinants behind the Acceptance of Autonomous Vehicles: A Systematic Review

People-Centric Service Intelligence for Smart Cities

SURROGATES: Virtual OBUs to Foster 5G Vehicular Services

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