Human–Machine Interaction in Intelligent and Connected Vehicles: A Review of Status Quo, Issues, and Opportunities

Tan, Zhengyu; Dai, Ningyi; Su, Yating; Zhang, Ruifo; Li, Yijun; Wu, Di; Li, Shutao

doi:10.1109/tits.2021.3127217

Cited by 55 publications

(18 citation statements)

References 175 publications

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“…Additionally, the design should incorporate a suitable HMI that augments human capabilities within the ICPS. Tan et al [73] systematically review the challenges and opportunities surrounding HMIs for intelligent vehicular applications. They highlight the complexity and heterogeneity of human intentions as a significant challenge for predictive HMI systems, and suggest that recognition performance must be improved to enable more advanced HMIs.…”

Section: Design Considerations For Intelligent Vehicular Embedded Sys...mentioning

confidence: 99%

Intelligent Embedded Systems Platform for Vehicular Cyber-Physical Systems

2023

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Intelligent vehicular cyber-physical systems (ICPSs) increase the reliability, efficiency and adaptability of urban mobility systems. Notably, ICPSs enable autonomous transportation in smart cities, exemplified by the emerging fields of self-driving cars and advanced air mobility. Nonetheless, the deployment of ICPSs raises legitimate concerns surrounding safety assurance, cybersecurity threats, communication reliability, and data management. Addressing these issues often necessitates specialised platforms to cater to the heterogeneity and complexity of ICPSs. To address this challenge, this paper presents a comprehensive CPS to explore, develop and test ICPSs and intelligent vehicular algorithms. A customisable embedded system is realised using a field programmable gate array, which is connected to a supervisory computer to enable networked operations and support advanced multi-agent algorithms. The platform remains compatible with multiple vehicular sensors, communication protocols and human–machine interfaces, essential for a vehicle to perceive its surroundings, communicate with collaborative systems, and interact with its occupants. The proposed CPS thereby offers a practical resource to advance ICPS development, comprehension, and experimentation in both educational and research settings. By bridging the gap between theory and practice, this tool empowers users to overcome the complexities of ICPSs and contribute to the emerging fields of autonomous transportation and intelligent vehicular systems.

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Section: Design Considerations For Intelligent Vehicular Embedded Sys...mentioning

confidence: 99%

Intelligent Embedded Systems Platform for Vehicular Cyber-Physical Systems

2023

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“…Significant breakthroughs in several aspects such as recognition accuracy, response time, computational memory consumption, user availability have contributed to this. According to one report [282], speech control is expected to become the second most popular interface, and 80% of automobile man-machine interfaces will adopt speech control in the near future. Speech recognition has played a role in several applications such as automatic navigation, speech search, command input, and speech assistant.…”

Section: B Ddt In Personalized Human-machine Interfacementioning

confidence: 99%

Review and Perspectives on Driver Digital Twin and Its Enabling Technologies for Intelligent Vehicles

Lou

Xing

et al. 2022

IEEE Trans. Intell. Veh.

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Digital Twin (DT) is an emerging technology and has been introduced into intelligent driving and transportation systems to digitize and synergize connected automated vehicles. However, existing studies focus on the design of the automated vehicle, whereas the digitization of the human driver, who plays an important role in driving, is largely ignored. Furthermore, previous driver-related tasks are limited to specific scenarios and have limited applicability. Thus, a novel concept of a driver digital twin (DDT) is proposed in this study to bridge the gap between existing automated driving systems and fully digitized ones and aid in the development of a complete driving human cyber-physical system (H-CPS). This concept is essential for constructing a harmonious human-centric intelligent driving system that considers the proactivity and sensitivity of the human driver. The primary characteristics of the DDT include multimodal state fusion, personalized modeling, and time variance. Compared with the original DT, the proposed DDT emphasizes on internal personality and capability with respect to the external physiological-level state. This study systematically illustrates the DDT and outlines its key enabling aspects. The related technologies are comprehensively reviewed and discussed with a view to improving them by leveraging the DDT. In addition, the potential applications and unsettled challenges are considered. This study aims to provide fundamental theoretical support to researchers in determining the future scope of the DDT system.

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“…This has led to a very different route for developing smart technologies than traditional technology. The human-vehicle interaction model has changed from product use to human–machine codriving ( Tan et al, 2021 ). In the past, users cared about only using the product, whether it was good or not, and whether it could achieve the expected function.…”

Section: Introductionmentioning

confidence: 99%

Motivation to interaction media: The impact of automation trust and self-determination theory on intention to use the new interaction technology in autonomous vehicles

Xie

Zhou²,

Chan³

et al. 2023

Front. Psychol.

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IntroductionThis research investigated the effects of three psychological needs (competence, autonomy, and relatedness) of self-determination theory (SDT) and automation trust on the intention of users to employ new interaction technology brought by autonomous vehicles (AVs), especially interaction mode and virtual image.MethodThis study focuses on the discussion from the perspective of psychological motivation theory applied to AV interaction technology. With the use of a structured questionnaire, participants completed self-report measures related to these two interaction technologies; a total of 155 drivers’ responses were analyzed.ResultThe results indicated that users’ intentions were directly predicted by their perceived competence, autonomy, and relatedness of SDT and automation trust, which jointly explained at least 66% of the variance in behavioral intention. In addition to these results, the contribution of predictive components to behavioral intention is influenced by the type of interaction technology. Relatedness and competence significantly impacted the behavioral intention to use the interaction mode but not the virtual image.DiscussionThese findings are essential in that they support the necessity of distinguishing between types of AV interaction technology when predicting users’ intentions to use.

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Human–Machine Interaction in Intelligent and Connected Vehicles: A Review of Status Quo, Issues, and Opportunities

Cited by 55 publications

References 175 publications

Intelligent Embedded Systems Platform for Vehicular Cyber-Physical Systems

Intelligent Embedded Systems Platform for Vehicular Cyber-Physical Systems

Review and Perspectives on Driver Digital Twin and Its Enabling Technologies for Intelligent Vehicles

Motivation to interaction media: The impact of automation trust and self-determination theory on intention to use the new interaction technology in autonomous vehicles

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