Personalized path generation and robust
            <i>H</i>
            <sub>∞</sub>
            output‐feedback path following control for automated vehicles considering driving styles

Chen, Yimin; Zhang, Yuanxu; Zhang, Feihu

doi:10.1049/itr2.12097

Cited by 7 publications

(8 citation statements)

References 28 publications

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“…Toolpath generation is a core task in computer numerical control (CNC) milling machine operations, directly impacting processing quality, efficiency, and tool lifespan (Chen et al, 2021). As a research area with tremendous potential, toolpath generation technology has been extensively explored by scholars worldwide.…”

Section: Abstract Cnc Milling Machine Toolpath Point Cloud Model Roug...mentioning

confidence: 99%

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Data model-based toolpath generation techniques for CNC milling machines

Liao,

Huang

2024

Front. Mech. Eng.

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Introduction: With the development of computer technology and data modeling, the use of point cloud models to generate tool paths is particularly important for improving productivity and accuracy.Methods: This study proposes a new method that first preprocesses the point cloud data using four-point denoising and octree methods to improve processing efficiency. Subsequently, roughing tool paths were analyzed using the layer slicing method and finishing paths using the residual height method.Results and Discussion: The experimental results show that the layer slicing method has a minimum error close to 10% on the roughing path generation and the computation time is reduced to 35 s, while the residual height method has an error rate of 10.17% on the finishing path and the computation time is only 11.82 s, which reflects a high trajectory smoothness and accuracy. The above results show that the study not only optimizes the tool path generation process and improves the machining efficiency and accuracy, but also demonstrates the potential application of point cloud models in the machining of complex parts.Conclusion: The novel tool roughing and finishing methods provide more reliable path planning for actual machining operations, and future research will be devoted to further improving the performance of the data processing algorithms and exploring more efficient path planning strategies to facilitate automated production.

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Section: Abstract Cnc Milling Machine Toolpath Point Cloud Model Roug...mentioning

confidence: 99%

“…The four-point denoising method uses a single scan line as a reference and calculates the spatial distances between consecutive points P i,j , P i,j+1 , P i,j−1 , P i,j+2 . The distance calculation between any two points is given by Formula (Chen et al, 2021).…”

Section: Denoising and Downsampling Of Point Cloud Modelsmentioning

confidence: 99%

Data model-based toolpath generation techniques for CNC milling machines

Liao,

Huang

2024

Front. Mech. Eng.

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“…Driving style analysis based on collectible data accounts for a large proportion of the analysis on driving micro intention. Llorca [78].…”

Section: Drivermentioning

confidence: 99%

“…Unsupervised learning [74] MLP-NN [75] Unsupervised learning [76] DNN, wavelet algorithm [77] Driving simulator design [78] H ∞ output feedback [79] Research for the purpose of designing insurance products or at least evaluating the risk of different driving styles Establishment of risk evaluation index system [80] Visualization of risk assessment indicators [81] MOPSO [82] BN [83] Fuzzy logic and total Bayesian theory [84] CNN and PSR [85] AHP…”

Section: Literaturementioning

confidence: 99%

A Comprehensive Review of Driving Style Evaluation Approaches and Product Designs Applied to Vehicle Usage-Based Insurance

Nai¹,

Yang²,

Wei³

et al. 2022

Sustainability

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Vehicle insurance is a very important source of income for insurance companies, and it is closely related to the driving style performed by driving behavior. Different driving styles can better reflect the driving risk than the number of violations, claims, and other static statistic data. Subdivide the vehicle insurance market according to the personal characteristics and driving habits of the insured vehicles, and studying the personalized vehicle insurance products, will help the insurance companies to improve their income, help the drivers to change their bad driving habits, and thus help to realize the healthy development of the vehicle insurance industry. In the past 20 to 30 years, more and more insurance companies around the world have launched vehicle usage-based insurance (UBI) products based on driving style analysis. However, up to now, there are few comprehensive reports on commercial vehicle UBI products and their core driving risk assessment methods. On the basis of literature indexing on the Web of Science and other academic platforms by using the keywords involved in vehicle UBI, over 100 relevant works of literature were screened in this paper, and a detailed and comprehensive discussion on the driving style evaluation methods and the design of commercial vehicle UBI products during the past 20 to 30 years has been made, hoping to get a full understanding of the possible factors affecting driving style and the collectible data that can reflect these factors, and to get a full grasp of the developing status, challenges and future trends in vehicle insurance branch of the Internet of Vehicles (IoV) industry.

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“…A review of research on feedback report design found most research focusing on writing/grammar (particularly learning English as a second language, e.g., [19]), math performances (e.g., [20]), and medically related activities (such as performing CPR, e.g., [21]), with most driving-specific research being related to autonomous vehicle programming (e.g., [22]). Prior studies have shown that in order to be effective, feedback reports need to be easy to use and motivate the recipient to improve [23].…”

Section: Introductionmentioning

confidence: 99%

Keep It Brief and Targeted: Driving Performance Feedback Report Features to Use with Novice Drivers

et al. 2022

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Driving evaluations aim to ensure adequate skills; however, feedback beyond pass/fail is needed for improvement. Therefore, the goal of this study was to inform driving feedback report design to ensure ease of use and understandability while motivating improvements. Participants ages 18–25 years (n = 521) were recruited from CloudResearch Prime Panels to rate one of nine report design conditions with various combinations of five key features: performance summary presence, action plan (AP) length, AP order, AP grading system, and peer comparison presence; they then completed questionnaires. Participants were more motivated to improve when a summary was present (p = 0.02); they rated reports easier to use if they had a long AP (p = 0.01), a short AP paired with a summary (p = 0.007), or an AP with a number grade (p = 0.016); and they rated reports easier to understand if they had a short AP (p = 0.002) or an AP ordered by worst-to-best performance (p = 0.05). These results suggest that feedback reports designed with a performance summary and short, targeted action plan starting with the biggest area for improvement are likely to motivate action to improve driving skills while being easy to use and understand. Future research should evaluate the effect of such a redesigned report on driving outcomes among young drivers.

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Personalized path generation and robust H _∞ output‐feedback path following control for automated vehicles considering driving styles

Cited by 7 publications

References 28 publications

Data model-based toolpath generation techniques for CNC milling machines

Data model-based toolpath generation techniques for CNC milling machines

A Comprehensive Review of Driving Style Evaluation Approaches and Product Designs Applied to Vehicle Usage-Based Insurance

Keep It Brief and Targeted: Driving Performance Feedback Report Features to Use with Novice Drivers

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Personalized path generation and robust H ∞ output‐feedback path following control for automated vehicles considering driving styles

Cited by 7 publications

References 28 publications

Data model-based toolpath generation techniques for CNC milling machines

Data model-based toolpath generation techniques for CNC milling machines

A Comprehensive Review of Driving Style Evaluation Approaches and Product Designs Applied to Vehicle Usage-Based Insurance

Keep It Brief and Targeted: Driving Performance Feedback Report Features to Use with Novice Drivers

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Product

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Personalized path generation and robust H _∞ output‐feedback path following control for automated vehicles considering driving styles