Digital Twins-Based Automated Pilot for Energy-Efficiency Assessment of Intelligent Transportation Infrastructure

Tu, Zhen; Qiao, Lei; Nowak, Robert; Lv, Haibin; Lv, Zhihan

doi:10.1109/tits.2022.3166585

Cited by 16 publications

(5 citation statements)

References 36 publications

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“…Traffic congestion in large and medium-sized cities is another stubborn problem in the transportation system. In order to solve this problem, the Long Short-Term Memory (LSTM) neural network model and DT technology are used to establish a traffic flow prediction model and traffic infrastructure evaluation model, and the data envelopment analysis method is used for verification [138]. Taking the data of Jiangsu Province as an example, Tu et al prove that these two models provide a powerful reference for investment and planning of transportation infrastructure and provide new ideas for the analysis of transportation infrastructure.…”

Section: Traffic Predictionmentioning

confidence: 99%

Digital Twin-Enabled Internet of Vehicles Applications

Gao,

Peng,

Yoshinaga

et al. 2024

Electronics

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The digital twin (DT) paradigm represents a groundbreaking shift in the Internet of Vehicles (IoV) landscape, acting as an instantaneous digital replica of physical entities. This synthesis not only refines vehicular design but also substantially augments driver support systems and streamlines traffic governance. Diverging from the prevalent research which predominantly examines DT’s technical assimilation within IoV infrastructures, this review focuses on the specific deployments and goals of DT within the IoV sphere. Through an extensive review of scholarly works from the past 5 years, this paper provides a fresh and detailed perspective on the significance of DT in the realm of IoV. The applications are methodically categorized across four pivotal sectors: industrial manufacturing, driver assistance technology, intelligent transportation networks, and resource administration. This classification sheds light on DT’s diverse capabilities to confront and adapt to the intricate challenges in contemporary vehicular networks. The intent of this comprehensive overview is to catalyze innovation within IoV by providing an essential reference for researchers who aspire to swiftly grasp the complex dynamics of this evolving domain.

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Section: Traffic Predictionmentioning

confidence: 99%

Digital Twin-Enabled Internet of Vehicles Applications

Gao,

Peng,

Yoshinaga

et al. 2024

Electronics

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“…Reference [89] establishes and compares a traffic infrastructure efficiency assessment model using data envelopment analysis based on DT and a traffic flow prediction model based on long short-term memory. The traffic flow data of a certain road section in Zhenjiang City were simulated and predicted.…”

Section: Case Studiesmentioning

confidence: 99%

A Review of Digital Twin Technology for Electric and Autonomous Vehicles

et al. 2023

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In the era of technological transformation, mobility and transportation systems are becoming more intelligent and greener. Thanks to powerful technologies and tools, electric and autonomous vehicles are spreading worldwide, substituting internal combustion engine vehicles and revolutionizing the way to drive. In this context, this paper is an extended version of the paper “Digital Twin in Intelligent Transportation Systems: a Review published in 2020 7th International Conference on Control, Decision and Information Technologies (CoDIT)”. The aim of this paper is to provide a comprehensive review of the literature from the last five years on the use of digital twin (DT) technology for Intelligent Transportation Systems (ITSs), focusing on electric and autonomous vehicles. In particular, with respect to the previous work, the focus has been expanded to include DT integration with other cutting-edge technologies, such as the Internet of Things (IoT), Big Data, artificial intelligence (AI), machine learning (ML), and 5G for ITS. Moreover, this paper presents a broad perspective on challenges in EV applications, including tracking, monitoring, battery and charge management, connectivity, security, and privacy. In addition, this paper discusses how DT can be used to effectively address the current issues in electric vehicle services, such as tracking, monitoring, battery and charge management, connectivity, security, and privacy.

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“…In the ICTS, DT is used to simulate the solution and observe the influence on each road section and area by collecting real data such as traffic flow and service request flow. For example, integrating traffic infrastructure into the DT to analyze the efficiency of traffic infrastructure by predicting the traffic flow based on AI models, thus enabling better resource scheduling [15]. Therefore, the performance of the service caching can be evaluated with the assistance of DT to avoid losses to consumers in real scenarios caused by deploying low performance service caching strategies.…”

Section: Introductionmentioning

confidence: 99%

Customer Centric Service Caching for Intelligent Cyber–Physical Transportation Systems With Cloud–Edge Computing Leveraging Digital Twins

Yan,

Xu,

Bilal

et al. 2024

IEEE Trans. Consumer Electron.

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To provide various high-quality intelligent transportation services to customers, Intelligent Cyber-Physical Transportation Systems (ICTS) with cloud-edge computing are widely commissioned. In such ICTS, service requests processed by edge servers (ES) usually have a low response latency, thus leading to a high quality of service (QoS). As a prerequisite for requests processing in the ES, service cache provides requests with storage and computing resources. But the limited resources of each ES make it impossible to cache all services, so how to generate highperformance caching strategies for ICTS is a major challenge. Besides, how to evaluate the effectiveness of the application of these strategies is also a challenge. Fortunately, thanks to the constructed digital twins (DT) for ICTS, the strategies have a digital platform to be simulated into application. With the assistance of DT, a solution to service caching problem in ICTS, named SFT-SCAR, is proposed. Firstly, a DT supported service providing framework for ICTS is designed. Then, a graph attention network (GAT) based service request flow prediction scheme and an asynchronous advantage actor-critic (A3C) based service caching scheme are presented. Besides, the generated caching strategies are simulated in the DT of ICTS to evaluate the performance of these strategies. Experimental results demonstrate that the proposed SFT-SCAR approach improves the hit rate by 1.11% -13.27%.

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Digital Twins-Based Automated Pilot for Energy-Efficiency Assessment of Intelligent Transportation Infrastructure

Cited by 16 publications

References 36 publications

Digital Twin-Enabled Internet of Vehicles Applications

Digital Twin-Enabled Internet of Vehicles Applications

A Review of Digital Twin Technology for Electric and Autonomous Vehicles

Customer Centric Service Caching for Intelligent Cyber–Physical Transportation Systems With Cloud–Edge Computing Leveraging Digital Twins

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