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A fundamental challenge in car-following modeling lies in accurately representing the multi-scale complexity of driving behaviors, particularly the intra-driver heterogeneity where a single driver's actions fluctuate dynamically under…

Machine Learning · Computer Science 2025-06-09 Shirui Zhou , Jiying Yan , Junfang Tian , Tao Wang , Yongfu Li , Shiquan Zhong

Parameter tuning for vehicle controllers remains a costly and time-intensive challenge in automotive development. Traditional approaches rely on extensive real-world testing, making the process inefficient. We propose a multi-fidelity…

Systems and Control · Electrical Eng. & Systems 2025-06-11 Yongpeng Zhao , Maik Pfefferkorn , Maximilian Templer , Rolf Findeisen

Automated vehicles are deemed to be the key element for the intelligent transportation system in the future. Many studies have been made to improve the Automated vehicles' ability of environment recognition and vehicle control, while the…

Artificial Intelligence · Computer Science 2018-04-18 Yingjun Ye , Xiaohui Zhang , Jian Sun

High-fidelity physics simulations are powerful tools in the design and optimization of charged particle accelerators. However, the computational burden of these simulations often limits their use in practice for design optimization and…

Accelerator Physics · Physics 2020-04-15 Auralee Edelen , Nicole Neveu , Yannick Huber , Mattias Frey , Christopher Mayes , Andreas Adelmann

Multi-fidelity Kriging model is a promising technique in surrogate-based design as it can balance the model accuracy and cost of sample preparation by fusing low- and high-fidelity data. However, the cost for building a multi-fidelity…

Machine Learning · Computer Science 2023-01-03 Youwei He , Jinliang Luo

Aerodynamic shape optimization in industry still faces challenges related to robustness and scalability. This aspect becomes crucial for advanced optimizations that rely on expensive high-fidelity flow solvers, where computational budget…

Fluid Dynamics · Physics 2025-05-26 Marc Schouler , Anca Belme , Paola Cinnella

We propose a multifidelity dimension reduction method to identify a low-dimensional structure present in many engineering models. The structure of interest arises when functions vary primarily on a low-dimensional subspace of the…

Numerical Analysis · Mathematics 2020-01-08 Rémi Lam , Olivier Zahm , Youssef Marzouk , Karen Willcox

Highly accurate datasets from numerical or physical experiments are often expensive and time-consuming to acquire, posing a significant challenge for applications that require precise evaluations, potentially across multiple scenarios and…

Machine Learning · Computer Science 2026-02-06 Paolo Conti , Mengwu Guo , Attilio Frangi , Andrea Manzoni

High-fidelity numerical simulations of partial differential equations (PDEs) given a restricted computational budget can significantly limit the number of parameter configurations considered and/or time window evaluated for modeling a given…

Machine Learning · Computer Science 2023-09-04 Paolo Conti , Mengwu Guo , Andrea Manzoni , Attilio Frangi , Steven L. Brunton , J. Nathan Kutz

Multibody dynamics simulations are currently widely accepted as valuable means for dynamic performance analysis of mechanical systems. The evolution of theoretical and computational aspects of the multibody dynamics discipline make it…

Chaotic Dynamics · Physics 2014-10-31 Yitao Zhu , Daniel Dopico , Corina Sandu , Adrian Sandu

Winter conditions, characterized by the presence of ice and snow on the ground, are more likely to lead to road accidents. This paper presents an experimental proof of concept, with a 1/5th scale car platform, of a maneuver selection scheme…

Robotics · Computer Science 2024-05-24 Olivier Lecompte , William Therrien , Alexandre Girard

Crashworthiness assessment is a critical aspect of automotive design, traditionally relying on high-fidelity finite element (FE) simulations that are computationally expensive and time-consuming. This work presents an exploratory…

Machine Learning · Computer Science 2025-11-04 Mohammad Amin Nabian , Sudeep Chavare , Deepak Akhare , Rishikesh Ranade , Ram Cherukuri , Srinivas Tadepalli

Multi-fidelity machine learning methods address the accuracy-efficiency trade-off by integrating scarce, resource-intensive high-fidelity data with abundant but less accurate low-fidelity data. We propose a practical multi-fidelity strategy…

Machine Learning · Computer Science 2025-03-26 Jiaxiang Yi , Ji Cheng , Miguel A. Bessa

This study evaluates a suspension design of a passenger car to obtain maximum rider's comfort when the vehicle is subjected to different road profile or road surface condition. The challenge will be on finding a balance between the rider's…

Systems and Control · Electrical Eng. & Systems 2021-02-01 Srikanth Raju Mudduluru , Mahmoud Chizari

Finite Element Analysis (FEA) is a powerful but computationally intensive method for simulating physical phenomena. Recent advancements in machine learning have led to surrogate models capable of accelerating FEA. Yet there are still…

Machine Learning · Computer Science 2025-02-18 Georgios Triantafyllou , Panagiotis G. Kalozoumis , George Dimas , Dimitris K. Iakovidis

Improving algorithms via predictions is a very active research topic in recent years. This paper initiates the systematic study of mechanism design in this model. In a number of well-studied mechanism design settings, we make use of…

Computer Science and Game Theory · Computer Science 2023-01-13 Chenyang Xu , Pinyan Lu

A common goal throughout science and engineering is to solve optimization problems constrained by computational models. However, in many cases a high-fidelity numerical emulation of systems cannot be optimized due to code complexity and…

Numerical Analysis · Mathematics 2023-05-31 Joseph Hart , Bart van Bloemen Waanders

Models that balance accuracy against computational costs are advantageous when designing wind turbines with optimization studies, as several hundred predictive function evaluations might be necessary to identify the optimal solution. We…

Systems and Control · Electrical Eng. & Systems 2025-05-21 Athul K. Sundarrajan , Daniel R. Herber

Multibody dynamics simulations have become widely used tools for vehicle systems analysis and design. As this approach evolves, it becomes able to provide additional information for various types of analyses. One very important direction is…

Computational Engineering, Finance, and Science · Computer Science 2014-11-05 Yitao Zhu , Corina Sandu , Daniel Dopico , Adrian Sandu

Active suspension systems are critical for enhancing vehicle comfort, safety, and stability, yet their performance is often limited by fixed hardware designs and control strategies that cannot adapt to uncertain and dynamic operating…

Robotics · Computer Science 2025-12-04 Ying-Kuan Tsai , Yi-Ping Chen , Vispi Karkaria , Wei Chen