bluuebunny/crossref_metadata_2025_split huggingface dataset:
Energy and Time Optimal Control of Autonomous Vehicles by Using Frenet Frame Modelling and over-Actuation
Authors: Zhang Wenliang , Drugge Lars , Nybacka Mikael , Jerrelind Jenny , Yang Derong , Reiter Rudolf , Frey Jonathan , Trigell Annika Stensson 
Published: October 2024

AbstractAutonomous driving and electrification make over-actuation technologies more feasible and advantageous. Integrating autonomous driving with over-actuation allows for the effective use of their respective strengths, e.g., for studying energy and time optimal control. To model AVs, several vehicle coordinate systems have been used, e.g., Cartesian, Frenet and spatial coordinates. The present study aims to achieve energy and time optimal control of autonomous vehicles by using Frenet frame modelling and over-actuation. This study enhances the existing Frenet-based modeling by incorporating double-track dynamic vehicle models and torque vectoring. The problem is formulated in an optimal control framework, with carefully designed cost function terms and constraints. Two control strategies are examined, one for minimising travel time and the other for jointly optimising energy consumption and travel time. The results indicate that by considering both energy and time in the formulation, the energy consumption can be apparently reduced while the travel time is merely slightly increased.
Robust 3D On-Road Object Detection and Distance Estimation for Active Vehicle Control Systems Based on Monocular Camera Image Data
Authors: Zhang Xingguo , Ikami Daiki , Raksincharoensak Pongsathorn 
Published: October 2024

Abstract3D object detection from monocular camera videos constitutes a critical research domain. Achieving robust 3D object detection in databases lacking annotated information poses a highly challenging task. This paper proposes a simple yet effective transfer learning approach, integrating data alignment, 3D object detection, and dynamic result correction. Vanishing point detection is employed to infer camera angles in diverse scenes, and preprocessing of new data is conducted by considering the camera's pitch angle and vanishing point position. Subsequently, MonoDETR are applied for depth estimation and 3D object detection in monocular videos. Building upon the detection results, dynamic correction is achieved through inter-frame assistance, culminating in the final 3D object information. Validation on the TUAT Near-Miss Incident Database demonstrates the efficacy of the proposed approach. The results indicate a substantial reduction in the cost of annotating new domain data while simultaneously enhancing detection accuracy and robustness. Integration with onboard diagnostics (OBD) data allows the reconstruction of information about various traffic participants in hazardous scenarios, providing valuable insights for in-depth analysis of accident causes.
Self-tuning of the Virtual-Bike Control for a Human-Powered Electric Bike with Series Architecture
Authors: Radrizzani Stefano , Panzani Giulio , Savaresi Sergio Matteo 
Published: October 2024

AbstractMotivated by environmental awareness, electric bikes (e-Bikes) diffusion as a means of transport has significantly increased in cities, thanks to their low emission and footprint. Among the different alternatives, series-parallel e-Bike architectures are interesting because they merge the advantages of the most common parallel bikes and the series ones, which can be exploited to improve the user experience. When an e-Bike is operating in series mode, a specific control action is needed to handle the absence of a mechanical transmission and so the chain-less nature of series or series-parallel e-Bikes. To this aim, the virtual-chain control law has been proposed and recently extended to a virtual-bike approach, respectively aiming at emulating the experience of the chain or an entire bike, whose parameters are user-chosen. In this work, a self-tuning strategy for the control parameters in the virtual-bike approach is formulated, making it independent of the specific bike and rider. Experimental results showed the advantages and limitations of the proposed solution.
Enhancing Steer-by-Wire Systems with an Integrated E-Motor and MR-Brake Actuator – Feedback Control Strategy
Authors: Niegl Matthias , Hendewerk Johannes , Becker Matthias , Battlogg Stefan , Pfeffer Peter 
Published: October 2024

AbstractThis study introduces an innovative control strategy for a steer-by-wire (SbW) force feedback actuator, tailored for automotive use. The actuator integrates a direct drive electric motor and a magnetorheological brake (MR-brake) within a streamlined, compact design. This electric motor delivers torque essential for the desired steering feel and ensures swift responsiveness. Concurrently, the MR-brake, noted for its compactness and energy efficiency, contributes passive damping and robust end-stop torque capabilities. The synergistic use of these components allows for a smaller and more resource-efficient electric motor design. A critical aspect of this strategy is the implementation of a torque splitter, essential for replicating the steering feel associated with Electric Power Steering (EPS) systems. This splitter distributes the required feedback torque between MR-brake torque and e-motor torque, ensuring high fidelity and consistent stability across a range of vehicular dynamics and maneuvers. Notably, maintaining a subjectively satisfying steering feel under conditions where torque proportions vary between actuators presents a significant challenge. The proposed actuator design, with its focus on performance, safety, and reliability, is particularly well-suited for advanced SbW systems demanding high standards in these areas.
On the Stability of the Closed-Loop Teleoperated Vehicle and Teledriver System
Authors: Hossain Ypti , Metzler Mathias , Edelmann Johannes , Plöchl Manfred 
Published: October 2024

AbstractTeleoperated vehicles are gaining importance during the transition to fully automated vehicles since at the current state of development automated vehicles are not capable of operating in all conditions and environments. Despite the high potential of the concept of teleoperated vehicles, there are still challenges to be dealt with. As the teledriver is physically not present in the vehicle during teleoperation, the communication between the teledriver and the vehicle takes place via internet. That could lead to a delayed transmission of the telemetry and visual signals. Additionally, the teledriver’s perception of the vehicle motion is reduced. This study demonstrates the differences between teledriving and normal driving from a theoretical perspective and how the stability of the vehicle-teledriver system is affected by the communication delay and the reduced perception of the vehicle motion. To increase the driver’s perception and the ease of control of the teleoperated vehicle, a simple structured and tunable steering wheel torque emulation concept is introduced.
A Method for Obtaining Reference Friction Values for Validation of Road Friction Estimation Algorithms
Authors: Hjort Mattias , Bruzelius Fredrik , Kharrazi Sogol , Yang Derong 
Published: October 2024

AbstractData-driven development of friction estimators for passenger vehicles is becoming popular. They rely mainly on training data to obtain an accurate estimate of the current road conditions. However, reference or training data for natural conditions containing available friction is sparse. This limits the development of data-driven approaches for friction estimation. The current paper presents progress in a project devoted to developing a method to use standard equipment for road monitoring to acquire reference data for friction estimation, relevant to specific tyres and operating conditions. Results show how a mapping between existing test equipment readings and the real experienced coefficient of friction of a car tyre can be made.
A Learning-Based Model Predictive Contouring Control for Vehicle Evasive Manoeuvres
Authors: Bertipaglia Alberto , Alirezaei Mohsen , Happee Riender , Shyrokau Barys 
Published: October 2024

AbstractThis paper presents a novel Learning-based Model Predictive Contouring Control (L-MPCC) algorithm for evasive manoeuvres at the limit of handling. The algorithm uses the Student-t Process (STP) to minimise model mismatches and uncertainties online. The proposed STP captures the mismatches between the prediction model and the measured lateral tyre forces and yaw rate. The mismatches correspond to the posterior means provided to the prediction model to improve its accuracy. Simultaneously, the posterior covariances are propagated to the vehicle lateral velocity and yaw rate along the prediction horizon. The STP posterior covariance directly depends on the variance of observed data, so its variance is more significant when the online measurements differ from the recorded ones in the training set and smaller in the opposite case. Thus, these covariances can be utilised in the L-MPCC’s cost function to minimise the vehicle state uncertainties. In a high-fidelity simulation environment, we demonstrate that the proposed L-MPCC can successfully avoid obstacles, keeping the vehicle stable while driving a double lane change manoeuvre at a higher velocity than an MPCC without STP. Furthermore, the proposed controller yields a significantly lower peak sideslip angle, improving the vehicle’s manoeuvrability compared to an L-MPCC with a Gaussian Process.
Computing the Lateral Compliance of the Racing Line Using Trajectory Optimization
Authors: Aggarwal R. K. , Gerdes J. C. 
Published: October 2024

AbstractWhile race car drivers speak often on racing lines, data reveals they do not follow consistent paths lap over lap. Furthermore, autonomous racing controllers designed to track optimal paths fail to keep pace with the best professional drivers. In this paper, we assess the importance of the racing line from an optimization perspective by evaluating its dynamic sensitivity to lateral perturbations. After applying the method to the Laguna Seca Raceway, we find that there is in fact a family of trajectories that are significantly different in path but similar in lap time. This finding is consistent with prior experimental work and indicates that extracting the peak dynamic performance from a vehicle may require reasoning through this whole family of solutions—instead of tracking a single line—to operate the vehicle at its true limits.
Observer Design for Estimating Road Elevations at All Tire Contact Patches Using Only an Inertial Sensor
Authors: Choi Hosik , Gim Juhui 
Published: October 2024

AbstractThis paper designs an observer for estimating road elevations at all tire contact patches using only an inertial sensor with high accuracy, comparable to that of laser scanning. The observer is constructed within the framework of the unknown input Kalman filter to estimate road elevations, which act as disturbances to vehicle dynamics. The model for the observer is based on vertical-pitch-roll dynamics, encompassing road elevations at all tire contact patches. The introduction of virtual measurements for all tires ensures the observability of the model in the inertial sensor-based observer without requiring both additional sensors and model simplification. Additionally, a bias model is added to compensate for sensor installation errors for practical realization. Experimental validation demonstrates that the proposed observer can estimate road elevation with high accuracy, regardless of vehicle speed and dynamics, even when utilizing only an inertial sensor, making it suitable for rapid and robust road maintenance.
Generalized symmetry in dynamical gravity
Authors: Cheung Clifford , Derda Maria , Kim Joon-Hwi , Nevoa Vinicius , Rothstein Ira , Shah Nabha 
Published: October 2024

Abstract
We explore generalized symmetry in the context of nonlinear dynamical gravity. Our basic strategy is to transcribe known results from Yang-Mills theory directly to gravity via the tetrad formalism, which recasts general relativity as a gauge theory of the local Lorentz group. By analogy, we deduce that gravity exhibits a one-form symmetry implemented by an operator Uα labeled by a center element α of the Lorentz group and associated with a certain area measured in Planck units. The corresponding charged line operator Wρ is the holonomy in a spin representation ρ, which is the gravitational analog of a Wilson loop. The topological linking of Uα and Wρ has an elegant physical interpretation from classical gravitation: the former materializes an exotic chiral cosmic string defect whose quantized conical deficit angle is measured by the latter. We verify this claim explicitly in an AdS-Schwarzschild black hole background. Notably, our conclusions imply that the standard model exhibits a new symmetry of nature at scales below the lightest neutrino mass. More generally, the absence of global symmetries in quantum gravity suggests that the gravitational one-form symmetry is either gauged or explicitly broken. The latter mandates the existence of fermions. Finally, we comment on generalizations to magnetic higher-form or higher-group gravitational symmetries.
Illuminating the dark: mono-γ signals at NA62
Authors: Barducci D. , Bertuzzo E. , Taoso M. , Ternes C. A. , Toni C. 
Published: October 2024

Abstract
Dipole interactions between dark sector states or between a Standard Model particle and a dark state can efficiently be searched for via high-intensity fixed-target facilities. We propose to look for the associated mono-γ signature at the NA62 experiment running in beam dump mode. Focusing on models of dipole inelastic Dark Matter and active-sterile neutrino dipole interactions, we compute the corresponding expected sensitivities finding promising prospects for discovery already with ~ 1017 proton-on-target, corresponding to the present accumulated dataset.
Froggatt-Nielsen meets the SMEFT
Authors: Loisa Eetu , Talbert Jim 
Published: October 2024

Abstract
We study the matching of Froggatt-Nielsen theories of flavour onto the Standard Model Effective Field Theory (SMEFT), upon integrating out a heavy Beyond-the-Standard-Model (BSM) scalar ‘flavon’ whose vacuum expectation value breaks an Abelian flavour symmetry at energies ΛFN well above the electroweak scale, ΛFN> ΛSM. We include matching contributions to the infrared dSM = 6 (Warsaw basis) SMEFT sourced from ultraviolet contact terms suppressed up to order 1/$$ {\Lambda}_{\textrm{UV}}^2 $$

Λ
UV
2

in the Froggatt-Nielsen Lagrangian, where ΛUV> ΛFN is an arbitrary ultraviolet scale where further unspecified BSM particles are dynamical. This includes tree-level (one-loop) ultraviolet diagrams with dFN = 6 (5) effective vertices. We first do so with a toy model, but then generalize our findings to arbitrary Frogatt-Nielsen charges. Our results indicate a rich and non-trivial signature of Froggatt-Nielsen theories on the (otherwise) model-independent operators of the SMEFT, and we briefly speculate on extending our analysis to broader classes of BSM flavour models, e.g. non-Abelian and/or gauged theories. We thus take an important step towards determining how to use rapidly developing theoretical and experimental SMEFT technologies to gain unambiguous insight into the SM’s longstanding fermion flavour puzzle.
Enhanced monochromatic photon emission from millicharged co-interacting dark matter
Authors: Du Mingxuan , Liu Jia , Wang Xiao-Ping , Wu Tianhao 
Published: October 2024

Abstract
We study a millicharged co-interacting dark matter scenario, where the primary dark matter constituent is the dark photon A′ and the secondary component is the fermion χ. In this model, χ interacts with A′ via a U(1)′ interaction while being millicharged with respect to normal photons. Our investigation focuses on the oscillation of A′ dark matter into photons within the background of χ particles, revealing that the A′ − χ scattering rate benefits from a Bose enhancement of the A′ final state. As the oscillation production rate is directly linked to the scattering rate, the conversion of A′ dark matter into monochromatic photons experiences significant amplification owing to this Bose enhancement, especially when the scattering rate Γsca approaches the dark photon mass $$ {m}_{A^{\prime }} $$

m

A
′

. These converted monochromatic photons are detectable through radio telescopes and can induce distortions in the Cosmic Microwave Background (CMB) spectrum. We find that the sensitivity of radio telescopes and the constraints imposed by CMB distortion on the kinetic mixing parameter are notably heightened compared to scenarios without the subdominant millicharged dark matter.
Real-time chiral dynamics at finite temperature from quantum simulation
Authors: Ikeda Kazuki , Kang Zhong-Bo , Kharzeev Dmitri E. , Qian Wenyang , Zhao Fanyi 
Published: October 2024

Abstract
In this study, we explore the real-time dynamics of the chiral magnetic effect (CME) at a finite temperature in the (1+1)-dimensional QED, the massive Schwinger model. By introducing a chiral chemical potential μ5 through a quench process, we drive the system out of equilibrium and analyze the induced vector currents and their evolution over time. The Hamiltonian is modified to include the time-dependent chiral chemical potential, thus allowing the investigation of the CME within a quantum computing framework. We employ the quantum imaginary time evolution (QITE) algorithm to study the thermal states, and utilize the Suzuki-Trotter decomposition for the real-time evolution. This study provides insights into the quantum simulation capabilities for modeling the CME and offers a pathway for studying chiral dynamics in low-dimensional quantum field theories.
Application of 3D scanning and computer simulation techniques to assess the shape accuracy of welded components
Authors: Jędrych Marianna , Gorzkiewicz Damian , Deja Mariusz , Chodnicki Marek 
Published: October 2024

AbstractWhile traditional measurement methods prove to be insufficient when facing more complex shapes and intricate challenges, increasingly efficient solutions are emerging in their place. 3D scanners in particular exhibit versatility. They clearly represent a useful tool in many fields with diverse requirements; thus, it is advisable to explore further areas of their potential applications, e.g., in quality control or reverse engineering. During our research, measurements were carried out on 40 welded elements using a caliper and on 11 other elements using the HandySCAN 700 Elite device by Creaform. The research was conducted at different stages of production, between subsequent operations. In addition, in the absence of interoperative nominal dimensions, a welding process simulation was performed in the Simufact Welding software. The simulation results were compared with actual deformations measured using a 3D scanner. The research enabled identification of the causes of excessive deformations and provided the basis for comparing the caliper with a modern laser device. A particular advantage of the scanner was demonstrated for complex issues requiring high flexibility and precise documentation of full geometry. The caliper proved to be more efficient only for quick execution of single, simple measurements at specific places. Incorporating the simulation in the Simufact Welding software into the analysis, allowed for a more precise validation of the planned technology. This solution presents a promising alternative to nominal models, particularly valuable when measurements are conducted between subsequent operations. Further research in this area is also recommended to enhance proposed methodology.
Optimizing Over Serial Dictatorships
Authors: Caragiannis Ioannis , Rathi Nidhi 
Published: October 2024

AbstractMotivated by the success of the serial dictatorship mechanism in social choice settings, we explore its usefulness in tackling various combinatorial optimization problems. We do so by considering an abstract model, in which a set of agents are asked to act in a particular ordering, called the action sequence. Each agent acts in a way that gives her the maximum possible value, given the actions of the agents who preceded her in the action sequence. Our goal is to compute action sequences that yield approximately optimal total value to the agents (a.k.a., social welfare). We assume query access to the value $$v_i(S)$$

v
i

(
S
)

that the agent i gets when she acts after the agents in the ordered set S. We establish tight bounds on the social welfare that can be achieved using polynomially many queries. Even though these bounds show a marginally sublinear approximation of optimal social welfare in general, excellent approximations can be obtained when the valuations stem from an underlying combinatorial domain. Indicatively, when the valuations are defined using bipartite matchings, arborescences in directed graphs, and satisfiability of Boolean expressions, simple query-efficient algorithms yield 2-approximations. We discuss issues related to truthfulness and show how some of our algorithms can be implemented truthfully using VCG-like payments. Finally, we introduce and study the price of serial dictatorship, a notion that provides an optimistic measure of the quality of combinatorial optimization solutions generated by action sequences.
PD-1 blockade does not improve efficacy of EpCAM-directed CAR T-cell in lung cancer brain metastasis
Authors: Blobner Jens , Dengler Laura , Eberle Constantin , Herold Julika J. , Xu Tao , Beck Alexander , Mühlbauer Anton , Müller Katharina J. , Teske Nico , Karschnia Philipp , van den Heuvel Dominic , Schallerer Ferdinand , Ishikawa-Ankerhold Hellen , Thon Niklas , Tonn Joerg-Christian , Subklewe Marion , Kobold Sebastian , Harter Patrick N. , Buchholz Veit R. , von Baumgarten Louisa 
Published: October 2024

Abstract
Background
Lung cancer brain metastasis has a devastating prognosis, necessitating innovative treatment strategies. While chimeric antigen receptor (CAR) T-cell show promise in hematologic malignancies, their efficacy in solid tumors, including brain metastasis, is limited by the immunosuppressive tumor environment. The PD-L1/PD-1 pathway inhibits CAR T-cell activity in the tumor microenvironment, presenting a potential target to enhance therapeutic efficacy. This study aims to evaluate the impact of anti-PD-1 antibodies on CAR T-cell in treating lung cancer brain metastasis.

Methods
We utilized a murine immunocompetent, syngeneic orthotopic cerebral metastasis model for repetitive intracerebral two-photon laser scanning microscopy, enabling in vivo characterization of red fluorescent tumor cells and CAR T-cell at a single-cell level over time. Red fluorescent EpCAM-transduced Lewis lung carcinoma cells (EpCAM/tdtLL/2 cells) were implanted intracranially. Following the formation of brain metastasis, EpCAM-directed CAR T-cell were injected into adjacent brain tissue, and animals received either anti-PD-1 or an isotype control.

Results
Compared to controls receiving T-cell lacking a CAR, mice receiving EpCAM-directed CAR T-cell showed higher intratumoral CAR T-cell densities in the beginning after intraparenchymal injection. This finding was accompanied with reduced tumor growth and translated into a survival benefit. Additional anti-PD-1 treatment, however, did not affect intratumoral CAR T-cell persistence nor tumor growth and thereby did not provide an additional therapeutic effect.

Conclusion
CAR T-cell therapy for brain malignancies appears promising. However, additional anti-PD-1 treatment did not enhance intratumoral CAR T-cell persistence or effector function, highlighting the need for novel strategies to improve CAR T-cell therapy in solid tumors.