Intention-Based Lane Changing and Lane Keeping Haptic Guidance Steering System

Yan, Zhanhong; Yang, Kaiming; Wang, Zheng; Yang, Bo; Kaizuka, Tsutomu; Nakano, Kimihiko

doi:10.1109/tiv.2020.3044180

Cited by 33 publications

(16 citation statements)

References 33 publications

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“…The player employs the WebVR 7 JavaScript library. Youtube-dl 8 is used for downloading the dataset, while the videos preprocessing was done via FFmpeg 9 .…”

Section: A Prototyping Environmentmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…Scent is invisible and can travel through obstacles and therefore could provide otherwise unknown information. Moreover, adding certain scents or tactile information could help neutralizing other unpleasant smells[7] and haptics, such as disturbing shaking when driving[8], thus they can be used for training of law enforcement, military or firefighters, and some manufacturers are already producing scents and odors for this purpose.Regarding the use of human senses in audiovisual distribution, the main focus of past research was to increase the Quality of Experience (QoE) by enhancing the quality of visual and audio content, and not focusing on other senses, such as touch and smell. In recent years, the adoption of XR technologies has seen both an increase in the quality of video representation and added interactivity.…”

mentioning

confidence: 99%

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A CNN-Based Framework for Enhancing 360° VR Experiences With Multisensorial Effects

Szabó

Simiscuka

Masneri

et al. 2023

IEEE Trans. Multimedia

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Improving user experience during the delivery of immersive content is crucial for its success for both the content creators and audience. Creators can express themselves better with multisensory stimulation, while the audience can experience a higher level of involvement. The rapid development of mulsemedia devices provides better access for stimuli such as olfaction and haptics. Nevertheless, due to the required manual annotation process of adding mulsemedia effects, the amount of content available with sensorial effects is still limited. This work introduces an innovative mulsemedia-enhancement solution capable of automatically generating olfactory and haptic content based on 360°video content, with the use of neural networks. Two parallel neural networks are responsible for automatically adding scents to 360°videos: a scene detection network (responsible for static, global content) and an action detection network (responsible for dynamic, local content). A 360°video dataset with scent labels is also created and used for evaluating the robustness of the proposed solution. The solution achieves a 69.19% olfactory accuracy and 72.26% haptics accuracy during evaluation using two different datasets.

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“…The player employs the WebVR 7 JavaScript library. Youtube-dl 8 is used for downloading the dataset, while the videos preprocessing was done via FFmpeg 9 .…”

Section: A Prototyping Environmentmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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A CNN-Based Framework for Enhancing 360° VR Experiences With Multisensorial Effects

Szabó

Simiscuka

Masneri

et al. 2023

IEEE Trans. Multimedia

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“…The multimodal data includes human data, dynamic in-cabin scenario data, and extra-cabin scenario data. The human behavior and state detection stage are mainly to identify human emotions, fatigue [22], distraction [23], intention [24], and other behaviors and states [25]. The corresponding intelligent cockpit can also predict human emotion, fatigue, distraction, intention, and other states.…”

Section: ) Intelligent Cockpit Perceptionmentioning

confidence: 99%

Intelligent Cockpit for Intelligent Vehicle in Metaverse: A Case Study of Empathetic Auditory Regulation of Human Emotion

Xue

et al. 2023

IEEE Trans. Syst. Man Cybern, Syst.

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Advances in technologies, such as intelligent connected vehicles and the metaverse are driving the rapid development of automotive intelligent cockpits. From the perspective of the cyber-physical-social system (CPSS), this study proposed the intelligent cockpit composition framework which includes three layers of perception, cognition and decision, and interaction. Meanwhile, we also describe the relationship between the intelligent cockpit framework and the outside environment. The framework can dynamically perceive and understand humans, and provide feedback on the understanding results, which is beneficial to provide a safe, efficient, and enjoyable experience for humans in the intelligent cockpit. In the cognition and decision layers of the proposed framework, we design a case study of active empathetic auditory regulation of driver anger, focusing on improving road traffic safety. We conducted an in-depth interview experiment and designed two auditory regulation materials of active empathy speech and text-to-speech (TTS) speech. Next, 30 participants were recruited, and they completed a total of 240 anger-regulated driving experiments in the straight and obstacle avoidance scenarios. Finally, we quantitatively analyzed and compared the participants' subjective feelings, physiological changes, driving behaviors, and driving risks, as well as validated the driver anger regulation quality of AES and TTS. The proposed research methods results are beneficial to the design of future intelligent cockpit emotion regulation systems, toward a better intelligent cockpit.

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“…One classic function of an ADAS is the Lane-Keeping Assist System (LKAS), which can prevent unintentional lane departure by alert or vibration [ 5 , 6 ]. Some researchers also explored its application in assisting drivers to keep or change lanes [ 7 , 8 ].…”

Section: Introductionmentioning

confidence: 99%

A Predictive Model of a Driver’s Target Trajectory Based on Estimated Driving Behaviors

Yan

Yang

Wang

et al. 2023

Sensors

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With the development of automated driving, inferring a driver’s behavior can be a key element for designing an Advanced Driver Assistance System (ADAS). Current research is focused on describing and predicting a driver’s behaviors as labels, e.g., lane shifting, lane keeping, etc., during driving. In our work, we consider that predicting a driver’s behavior can be described as predicting a trajectory the driver may follow in the near future. The target trajectory can be calculated through certain polynomial functions. Via the data set collected by a Driving Simulator experiment covering nine volunteers, we proposed a model based on a deep learning network which is capable of predicting the corresponding coefficients of polynomial functions and then generating the trajectories in the next few seconds. The results also discussed and analyzed some possible factors affecting the prediction error. In conclusion, the model proved to be effective in predicting the target trajectory of a driver.

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Intention-Based Lane Changing and Lane Keeping Haptic Guidance Steering System

Cited by 33 publications

References 33 publications

A CNN-Based Framework for Enhancing 360° VR Experiences With Multisensorial Effects

A CNN-Based Framework for Enhancing 360° VR Experiences With Multisensorial Effects

Intelligent Cockpit for Intelligent Vehicle in Metaverse: A Case Study of Empathetic Auditory Regulation of Human Emotion

A Predictive Model of a Driver’s Target Trajectory Based on Estimated Driving Behaviors

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