AI enabled applications towards intelligent transportation

Iyer, Lakshmi

doi:10.1016/j.treng.2021.100083

Cited by 122 publications

(57 citation statements)

References 28 publications

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“…Now, intelligent transportation systems can enable vehicles to avoid traffic congestion [184], reduce energy and land consumption [182], improve driving control, safety, and security [185], act as a distributed energy resources to provide a balance between electricity demand and supply [186] and reduce cost (or, increase benefit) for the vehicle owner [187], and improve environmental sustainability [188]. Disrupting technologies and innovating tools that are contributing to revolutionizing the transport system for a safer and greener future include in-vehicle sensor technology [189], in-roadway sensors [190] and over-highway sensor technologies [191], IoT and cloud services [192], tools for big data analysis [193], artificial intelligence [194], traffic sensing technologies [195], distributed ledger technology for transportations [185], and vehicle-to-vehicle communication and network [196].…”

Section: ) Intelligent Transportation Systemsmentioning

confidence: 99%

A Survey of Cyber-Physical Systems From a Game-Theoretic Perspective

et al. 2023

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With the emergence of the Internet-of-Things (IoT), artificial intelligence, and communication technologies, cyber-physical systems (CPS) have revolutionized the engineering paradigm with profound applications in many aspects of society including homes, energy, agriculture, health-care, transportation, business, and manufacturing. A CPS uses suitable computational techniques such as game theory to enable different entities to interact with one another for taking necessary actions to obtain selected objectives. Recent literature on CPS has extensively used game theory to approach a variety of technical challenges. In order to make these contributions more accessible to a broader audience, there is a need for studies that can provide readers with a comprehensive understanding of different types of CPS and their attributes, then clearly outline why game theory is relevant for modeling different aspects of CPS, and also discuss how game theory has been used in relevant literature to date. This paper bridges this gap by 1) providing a general discussion of different types of CPS and their characteristics; 2) giving an overview of different types of game-theoretic approaches; 3) explaining why game theory is appropriate for modeling different types of CPS; and 4) finally, studying how game theory has been used in different CPS types to address their challenges. Further, we also identify some key research challenges for future investigation where game theory could be applied as a potential solution.

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Section: ) Intelligent Transportation Systemsmentioning

confidence: 99%

A Survey of Cyber-Physical Systems From a Game-Theoretic Perspective

et al. 2023

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“…AI is defined in many ways with various approaches and perspectives. Iyer (2021) has summarized and defined AI as the ability of machines to have similar human cognition such as learning, reasoning, identifying, and solving problems. From the start of the concept, AI has been developing rapidly and has become a wide spectrum discipline that has various applications in different domains (Hariri et al, 2019;.…”

Section: Artificial Intelligence and Information Sharingmentioning

confidence: 99%

“…(2) to allow companies to automatically make an impactful real-time decision; and (3) to allow mistakes, improvements to be documented for future improvements (Hariri et al, 2019;Cheng & Yu, 2019;. This new generation of AI has the potential to completely change the way business has been sharing information for decades and could trigger innovation in the way companies integrates their supply chain to be more competitive in the marketplace (Poola, 2017;Ding et al, 2020;Iyer, 2021).…”

Section: Artificial Intelligence and Information Sharingmentioning

confidence: 99%

AI-enabled Integration in the Supply Chain

Kieu¹,

Nayak²,

Akbari³

2022

JRE

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Artificial Intelligence (AI) is getting increased attention from various manufacturing industries, including fashion and textiles, due to its ability to work effectively, similar to human intelligence. This Systematic Literature Review (SLR) paper proposes potential future research directions that emphasize the impacts of AI on supply chain integration (SCI) efforts through information sharing (IS). A structured literature review of articles in the 2010-2021 period, addressing geographic location, journals, publishers, authors, research designs, and applied theories, has been used to prepare this paper. The additional discussion of AI incorporates information from the structured review to conclude the findings and suggest future research directions. The authors have used the Scopus database and prestigious peer-reviewed journals to search for relevant papers using suitable keywords. This paper concluded that the Asian region has the highest concentration of publications and that AI adoption positively affects the IS-SCI relationship. Empirical quantitative research design and resource-based view theory are prominent among the reviewed publications. This SLR paper is limited by not having the impacts of AI discussed at the subset level.

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“…Workers in intelligent transportation companies are mainly responsible for planning, construction, and problem solving related to traffic management, such as implementing roadside traffic flow detection systems. In particular, highway service patrols, advanced vehicle location systems, and some elements of employee transit pass programs have embedded feedback mechanisms to measure the results of solutions relevant to the transportation industry in which each process has different problems that need to be solved creatively ( Khattak et al, 2006 ; Iyer, 2021 ).…”

Section: Introductionmentioning

confidence: 99%

The Effects of Employees’ Perceived Intrinsic Motivation on Knowledge Sharing and Creative Self-Efficacy

Jiang

2022

Front. Psychol.

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Knowledge sharing is the major driving force to maintain enterprises’ competitiveness. This study extends the current knowledge-sharing research by considering knowledge sharing as comprising four types: automatic response, rational reflection, ridiculed reflection, and deprived reflection, based on Kahneman’s (2011) types of system thinking. Drawing on the motivation-action-outcome model, this study explored how individuals’ intrinsic motivation can guide the action of knowledge sharing and reflect the outcome of creative self-efficacy in intelligent transportation jobs. By snowball sampling in intelligent transportation companies, a total of 232 effective questionnaires were collected, and confirmatory factor analysis with structural equation modeling was performed. The research results showed that: intrinsic motivation was positively related to the four types of knowledge sharing tendencies; automatic response was not significantly related to creative self-efficacy; rational reflection was positively associated with creative self-efficacy; but ridiculed and deprived reflection were negatively related to creative self-efficacy. These results can be applied to encourage employees to practice rational reflection in knowledge sharing to enhance their creative self-efficacy in intelligent transportation jobs.

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AI enabled applications towards intelligent transportation

Cited by 122 publications

References 28 publications

A Survey of Cyber-Physical Systems From a Game-Theoretic Perspective

A Survey of Cyber-Physical Systems From a Game-Theoretic Perspective

AI-enabled Integration in the Supply Chain

The Effects of Employees’ Perceived Intrinsic Motivation on Knowledge Sharing and Creative Self-Efficacy

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