bluuebunny/crossref_metadata_2025 huggingface dataset:
Fuel Economy Assessment of MPC-ACC on Powertrain Testbed
Authors: Favelli Stefano , Castellanos Molina Luis M. , Mancarella Alessandro , Marello Omar , Tramacere Eugenio , Manca Raffaele , Silvagni Mario , Tonoli Andrea , Amati Nicola
Published: October 2024

The development and testing of Advanced Driver Assistance Systems (ADAS) is one of the most active fields in the automotive industry towards Automated Driving (AD). This work presents the deployment and testing of an Adaptive Cruise Control (ACC) based on Model Predictive Control (MPC). The goal is to design and validate through the experimental campaign a computationally efficient longitudinal dynamics controller and assess its fuel economy potential. The development of the control structure as well as the definition of the testing method for energy efficiency assessment are central aspects of this work. The performance of the approach is tested on a light-duty commercial vehicle on a state-of-the-art 4-axis powertrain testbed. The findings demonstrate that the speed profile can be optimized to achieve a fuel reduction of up to $$13\%$$

13
%

while maintaining mission timing and comfort.
Driver Behaviour Characterization Using an Instrumented Steering Wheel Conscious/Unconscious Muscle Activation
Authors: Akutain Xabier Carrera , Comolli Francesco , Gobbi Massimiliano , Mastinu Giampiero , Radaelli Giovanni
Published: October 2024

The paper presents an Instrumented Steering Wheel (ISW) that measures the forces and moments that the driver applies at each hand. The ISW is equipped with two six-axis load cells and has the same inertia of a reference steering wheel fitted on normal production cars. The ISW is used to assess the conscious or unconscious application of forces at the steering wheel during a set of manoeuvres. The conscious steering actions refer both to sinusoidal steering input and handling circuit driving. A statistical analysis is performed to characterize the conscious driver behaviour. Referring to unconscious activation of muscles, a kick-plate pass-by manoeuvre is studied. Several drivers are employed for such tests. Typical behavioural patterns are found, describing how drivers apply forces and moments in conscious steering actions. The unconscious moment applied during a kick-plate manoeuvre may be even 20% of the maximum torque applied during counter-steering. The results can be used to develop new driver models, additionally, the ISW is proposed as a tool for properly defining the ADAS intervention logic to reduce the intrusiveness feeling felt by the driver and increase safety in case of unconscious steering actions.
Energetic Impact of Urban Cooperative Driving on the Example of Intersections
Authors: Sturm Axel , Flormann Maximilian , Henze Roman , Raksincharoensak Pongsathorn
Published: October 2024

The use of automated driving and connectivity can be an additional lever to reduce fuel and energy consumption in real driving and has an impact on the drive system and its dimensioning as well. In this paper we are addressing the impact urban cooperative driving on the energy consumption of electric vehicles and investigate further the impact of the drive system and their layout. To this end, a concept study is being conducted for a D-segment vehicle and two battery electric powertrains. In order to evaluate the impact, defined driving profiles from a connected intersection are used for simulation. Based upon the results the overall energetic impact of different intersection approaching strategies as well as the drive system impact are discussed. It showed that a cooperative intersection scenario leads to an energy reduction of 14% and first come first serve scenarios to an energy reduction of 7%.
Force Sensors for the Active Safety of Road Vehicles
Authors: Milivinti M. , Amadini M. , Ballo F. , Gobbi M. , Mastinu G.
Published: October 2024

Force and moment measurement within road vehicles plays a break-through role in automotive engineering. Both wheel force transducers and instrumented hub carriers are considered in the paper. Both technologies have advantages and disadvantages. Active safety systems (ABS, ESP, up to full automated driving) are expected to be impacted by the measurement of forces and moments at the wheels. Friction potential evaluation and driver model development and monitoring are major field of research. Force and moment measurement technology may also be exploited for lightweight construction purposes. Promising technologies are the ones that don’t need RF data transfer, providing low latency for data transfer and are resiliency against cyber-attacks.
Towards Automated Driving: Findings and Comparison with ADAS
Authors: Donà Riccardo , Mattas Konstantinos , Albano Giovanni , Váss Sandor , Ciuffo Biagio
Published: October 2024

The present contribution provides preliminary empirical findings concerning the first-in-literature independent experimental characterization of a commercially viable automated driving system in Europe. In particular, the paper reports on the testing campaign involving a type-approved Automated Lane Keeping System (ALKS) equipped vehicle and its comparison with the comparable driving assistance feature technology from the same vehicle: the Adaptive Cruise Control (ACC) system. The results suggest that the ALKS shows substantially enhanced performances with respect to ACC. In particular, both the string stability metrics and the reaction time show remarkable improvements. Additionally, the increased stability is not obtained via resorting to a significantly higher time gap which further motivates that string stable car-following is indeed feasible.
Speed Control in the Presence of Road Obstacles: A Comparison of Model Predictive Control and Reinforcement Learning
Authors: Mandl P. , Jaumann F. , Unterreiner M. , Gräber T. , Klinger F. , Edelmann J. , Plöchl M.
Published: October 2024

The paper compares two optimal control methods — Reinforcement Learning and Model Predictive Control — for adaptive speed control in the presence of road obstacles to enhance ride comfort. Both methods use a model for training or prediction and a reward or cost function to achieve a desired control objective. Using the same quarter-car model and objective function for both methods, differences in planned speed profiles, optimality of the control objective, and differences in computational time are analysed through simulations over a series of cosine-shaped road bumps.
Road Friction Adaptive Lateral Control of Automated Vehicles with Differential Braking
Authors: Iatropoulos Jannes , Ahrenhold Tim , Salzwedel Leon , Henze Roman
Published: October 2024

Differential braking offers a promising approach to ensure lateral control of automated vehicles in the event of steering actuator failure. Braking interventions induce longitudinal forces on the wheel, which influence the vehicle’s yaw motion and thus enable lateral control along a given trajectory. Within the scope of this paper, a road friction adaptive system for lateral vehicle control by differential braking on a dry, wet, snow- and ice-covered road is derived simulatively. The investigated friction coefficient adaption is implemented by a variable path planning and calculated on the basis of an estimated road friction coefficient. The driving situation considered is based on the severe lane-change maneuver according to ISO 3888-2 for the investigation of vehicle dynamics and road-holding ability. The limitation of the trajectory results from the maximum yaw rate and expands the trajectory’s length for the different road friction coefficients.
Study on Accident-Avoidance Mechanism in Driver-Vehicle System When Activating Level-2 ADAS
Authors: Arai Norika , Kamimura Jinnosuke , Fujinami Yohei , Zhang Xingguo , Raksincharoensak Pongsathorn , Uechi Masaaki , Inoue Shintaro , Sugaya Fumio , Nogi Kazunori , Okita Toshinori , Hayashi Hideaki , Niki Keitaro
Published: October 2024

Advanced Driver Assistance Systems (ADAS) in passenger cars, such as Adaptive Cruise Control (ACC) and Lane Keeping Assist (LKA), have recently been widely deployed. However, these systems are not designed for high-risk situations, yet some drivers over trust the system and engage in secondary tasks. These behaviours may lead to serious accidents. On the other hand, it has been reported that the use of ACC reduced approximately half of the collision rate on highways based on public road data. This study aims to clarify the mechanism how ADAS affects driver behaviour and enhances accident prevention performance. Specifically, the focus is on the forward collision risk and the driver’s brake operating behaviour. Through the analysis using a driving simulator, this study compared driver behaviour in high collision risk situations in the case with and without ACC. The analysis of subject drivers’ internal parameters confirmed the driver behaviour that avoided a collision by using ADAS to take over control and brake earlier.
Accuracy Requirements of Camera-Based Depth Estimation for Urban Automated Driving
Authors: Westendorf M. , Thal S. , Ahrenhold T. , Henze R.
Published: October 2024

For autonomous driving in urban areas higher accuracy requirements for localization of surrounding traffic participants become apparent. The use of cost-efficient camera sensors shows potential for a performant depth estimation and can supplement perception systems to achieve redundancy. Current research focuses on improving the algorithms towards better performance whereas the application-oriented analysis of present estimation errors in relation to urban traffic scenarios is often neglected. Based on stereo and mono camera images, a benchmark analysis of rule- and deep learning-based depth estimation approaches is conducted in this work. The error-prone estimation results are then analyzed against braking distances of urban traffic scenarios simulated by a two-track model to analyze the criticality of different depth estimation approaches. The application-oriented evaluation shows that current approaches could already be used in real automated driving systems and enable the definition of requirements.
Determination of the Loss Behavior of Wheel Bearings Under Real Driving Conditions
Authors: Hartmann Lukas , Ohms Leon , Rebesberger Ron , Brandes Gerrit , Henze Roman
Published: October 2024

The characterization of component losses is typically conducted on dedicated test benches with the objective of enhancing component efficiency. Nevertheless, obtaining precise measurements of the actual loss contributions of components during real-world vehicle operations is often challenging. This challenge particularly pertains to wheel bearings, whose loss characteristics are efficiently delineated through the generation of efficiency maps on test benches at the Institute of Automotive Engineering. This submission presents a methodology for establishing these efficiency maps and introduces a developed methodology that enables the transfer of loss behavior from the component test into real-world driving conditions. Subsequently, the power losses are quantified across distinct driving domains, including urban, rural, and highway conditions. The outcomes of this methodology are contrasted with the losses observed on the test benches in order to identify potential avenues for reducing the losses of wheel bearings. Furthermore, the methodology is applied to homologation-relevant vehicle test benches with the objective of comparing the power losses under these conditions with real-world vehicle operations.
Time-Optimal Learning-Based LTV-MPC for Autonomous Racing
Authors: Guo Zijun , Yu Huilong , Xi Junqiang
Published: October 2024

Autonomous racing is a time- and accuracy-critical application of vehicle motion planning and control techniques. Despite being promising for its ability to handle constraints, model predictive control (MPC) for autonomous racing is limited by the relatively low computational speed and the problem of model mismatch. In this work, we present a time-optimal linear-time-variant-MPC (LTV-MPC) that incorporates a min-time objective function, the friction ellipse constraint, and the successive linearization over the prediction horizon to improve computational speed and prediction accuracy. To tackle model mismatch, the proposed LTV-MPC is further combined with Gaussian process regression to learn the lateral tire force error. Compensation for the error is implemented over the prediction horizon and on the friction ellipse constraint. This work presents simulation validation on the racing track of Formula Student Autonomous China (FSAC) and experimental validation on a self-designed track. We show that compared with nonlinear MPC, the proposed LTV-MPC reduces the average computation time from 66 ms to 2.5 ms with a 0.6% increase in lap time. With learned tire force error, a 2% reduction in lap time can be achieved.
Speed Profile Definition for GLOSA Implementation on Buses Based on Statistical Analysis of Experimental Data
Authors: Vignarca Daniele , Arrigoni Stefano , Sabbioni Edoardo , Cheli Federico
Published: October 2024

The latest advancements in vehicle automation have revealed significant potential for enhancing traffic management via Advanced Driver Assist Systems (ADAS), benefiting both safety and environmental considerations. Green Light Optimal Speed Advisory (GLOSA) systems represent a significant application in the Cooperative-Intelligent Transportation System (C-ITS) field adopting Vehicle-to-Everything (V2X) communication technology. The literature nowadays addresses quite extensively the GLOSA, and C-ITS in general, for conventional vehicles like cars. At the same time, there is emerging research starting to involve also the public transportation vehicles within this framework. The focus for buses is typically posed either on the comfort and regularity of the service for passengers or on the energy consumption which is reduced by adopting suitable speed profiles for the vehicle, thus avoiding unnecessary stops. This work presents a statistical analysis based on experimental data collected in real-world urban scenarios over one entire year. The outcome of this analysis allows the design of speed profiles typical for a public transportation vehicle, accounting for features such as the bus stop station for getting passengers off and on.
Effect of Driving Force Control that Imitates the Function of Tire Lateral Force on Vehicle Dynamics
Authors: Katsuyama Etsuo
Published: October 2024

Various control methods have been proposed that aim to improve steering response, disturbance stability, and stabilize steering characteristics by distributing drive force to each wheel. Conventionally, controls have been constructed by combining those control methods and tuning gains for each control. However, such control design methods require a huge amount of man-hours, and besides, it is not clear which states are optimal. Therefore, in this paper, we first focused on the mechanism of tire lateral force. In general, vehicles can run stably against disturbances without implementing any feedback control. It was clarified that this is because the tire lateral force plays the role of a skyhook damper installed horizontally on the side of the vehicle. Therefore, we proposed a control method that brings out the maximum potential of tires based on the idea that tire longitudinal force should have the same function as tire lateral force.
Drifting Maneuver Investigation via Phase Plane Analysis of Experimental Data
Authors: Righetti Giovanni , dell’Annunziata Guido Napolitano , Farroni Flavio , Massaro Matteo , Lenzo Basilio
Published: October 2024

This paper presents a comprehensive analysis of experimental data on drifting maneuvers, using vehicle data collected by Stanford University with a professional driver. Vehicle dynamics during drifting, characterised by high sideslip angles and countersteering, are examined. By using a nonlinear single track model with nonlinear tires, this study compares real-car data to simulated models within a phase-plane framework. It also explores the application of saddle-node bifurcation theory to understand the abrupt changes in vehicle behaviour during drifting.
Black Ice Detection Based on Tire Friction Coefficient Estimation of Vehicle Longitudinal Model
Authors: Lee Seung-Yong , Lee Ho-Jong , Kim Gi-Woo
Published: October 2024

Black ice is a deadly hazard on the road because it is visually transparent and difficult to identify by driver’s naked eye while driving. Because tire friction on a black icy road surface is obviously smaller than normal road, the braking distance significantly increases and leads to severe traffic accidents. Road hazard detection such as black ice has been actively attempted so far, usually focusing on methodology using intelligent vision systems (e. g., cameras). However, current image-based methods are prone to reduced low accuracy due to their susceptibility to vibrations transmitted from road surfaces to vehicles. In addition, incorporating cameras and light detection and ranging sensors increases the complexity and computational burden, especially when extending their functionality to include road surface classification. Therefore, we investigate the potential of new road surface classification based on vehicle longitudinal velocity and tire effective radius estimation from vehicle longitudinal model. This study explores a sensor-fusion type indirect road surface classification algorithm based on Kalman filtering.
Experimental Evaluation on Effects of Torque Vectoring Using Four In-Wheel Motor Independent Torque Control
Authors: Homma Yota , Yamakaji Yoshihiro , Kajitani Koji , Ford Richard , Furukawa Yoshimi
Published: October 2024

This paper explores the effects of Direct Yaw Control (DYC) on driver’s maneuverability feeling and vehicle dynamics. DYC is implemented in the experimental vehicle equipped with four-wheel independent controlled In-Wheel Motors (IWMs). The effects on vehicle dynamics are validated through open-loop testing. Subsequently, the closed-loop test is conducted to confirm the correlation between subjective evaluation and Vehicle dynamics data.
A Novel Torque Vectoring Approach to Enhance Driving Experience
Authors: Paparone Marco , Pino Alessandro , Giacomel Filippo , Bussalai Giovanni , Macaluso Andrea , Lamps Antoine , Mavroudakis Basileios
Published: October 2024

The current state of Direct Yaw Control literature has reached an advanced level, yielding compelling results in stabilizing vehicle behavior, and enhancing overall performance. However, conventional approaches exhibit limitations in addressing highly transient lateral dynamics, particularly during conditions of rapidly increasing vehicle sideslip angles, leading to poor controllability and reduced intuition for the driver. This paper introduces a novel extension to the established yaw rate tracking technique, integrating the trivial yaw rate feedback control with a less conventional model-based feedforward term, complemented by an innovative sideslip rate tracking loop. The primary objective of this term is to smoothen vehicle cornering response, effectively dampening oscillations in the vehicle’s behavior without compromising time delays to driver inputs. The intended outcome is not only enhancing safety but also delivering a more intuitive and enjoyable driving experience. The effectiveness of the approach is demonstrated by the results obtained through detailed Driver-in-Motion (DiM) sessions.
Basic Study on the Effect of Driver Condition on Steering Burden
Authors: Uchino Daigo , Kintou Ri , Kobayashi Ikkei , Kuroda Jumpei , Ogawa Kazuki , Ikeda Keigo , Kato Taro , Endo Ayato , Kato Hideaki , Narita Takayoshi
Published: October 2024

With the widespread use of steer-by-wire in automobiles, research is being conducted on high steering gear ratio systems that reduce the burden on the driver, which enables steering with high sensitivity. However, this decreases the resolution during steering and worsens operability, making steering operation more difficult. In addition, if the amount of steering operation and the magnitude of steering reaction torque are not appropriate for the driver, it may cause operation errors. In a highly sensitive steering system, a small change in steering reaction torque has a large potential to affect the driver. The driver’s steering burden varies depending on conditions, so it is not always possible to reduce the steering burden. Therefore, we evaluated the driver’s steering burden on different days and examined the effect of steering reaction force torque on the steering burden. The results confirmed that the deviation of the burden increases as the load increases.
Design and Analysis of Traction Control Strategies for Icy Road Conditions
Authors: Mihalkov M. , Caponio C. , Hankovszki Z. , Sorniotti A. , Montanaro U. , Gruber P.
Published: October 2024

Traction control (TC) plays a key role in improving vehicle safety, especially for driving scenarios involving extremely low levels of tyre-road friction. In this paper a novel deep reinforcement learning (DRL) based TC strategy is formulated and its performance is compared against a nonlinear model predictive control (NMPC) solution for a simulated straight-line acceleration manoeuvre on icy road conditions. The paper explores the design and assessment of the proposed controllers using a vehicle model experimentally validated on ice. The simulation results show that the DRL solution outperforms the NMPC strategy by reducing the wheel slip ratio peaks and oscillations at the start of an acceleration manoeuvre. Additionally, it converges more quickly to the reference slip and is more computationally efficient.
Design and Verification of an Adaptive State-Tuned Power Management System for Series Hybrid Electric Tracked Vehicles
Authors: Çeliksöz Dersu , Göçer İsmail , Gülseren Kerim Arda
Published: October 2024

The accelerated shift towards electrification in the tracked vehicle industry, particularly concerning off-road and military vehicles, poses challenges due to their intensive power consumption and limited charging infrastructures. Addressing these challenges, this paper focuses on the development of an adaptive state-tuned power management system for a series hybrid electric tracked vehicle. The vehicle's architecture includes an electric traction unit and a hybrid powerpack. The core of this research involves designing a dynamic power allocation system that adjusts the power sharing between the battery and a generator set under varying operational conditions. Through a systematic approach, a power management algorithm featuring a hierarchical controller structure to manage the power flow is designed. Simulation tests, both Driver-in-the-Loop (DIL) and Model-in-the-Loop (MIL), were employed to verify the system’s performance. Results indicate that the algorithm coordinates power distribution, ensuring optimal performance while adhering to the system's constraints and adapting to immediate power demands, demonstrating its potential for enhancing hybrid vehicle operations in demanding maneuvers.
Using a Smartwatch to Evaluate Subjective Ratings of Driving Functions
Authors: Anna Panzer , Hendryk Lausch , Jannes Iatropoulos , Roman Henze
Published: October 2024

Automating the driving task fundamentally changes the user's driving experience. The driving function now dictates the driving style, previously a product of individual decisions by the driver. Consequently, understanding what constitutes a comfortable driving style becomes essential for ensuring the optimal design of driving functions. This knowledge can be acquired through user studies. As self-reports are often distorted, physiological data can help provide a more objective insight into the emotions and feelings of the test subjects. Smartwatches serve as a convenient and uncomplicated measuring device in this context. The aim of this paper is to investigate whether the accuracy of a smartwatch is sufficient to infer user perceptions and subjective ratings. To achieve this, a subject study is conducted using a driving simulator.
Dynamical Behaviours of the Nose Landing Gear with Freeplay and Stochastic Disturbance
Authors: Du Xiaolei , Xu Yong
Published: October 2024

Shimmy dynamics of a dual wheel nose landing gear system with torsional freeplay under stochastic lateral disturbances is studied. Dynamic characteristics of the deterministic case are numerically analyzed, especially the shimmy of the landing gear through bifurcation analysis. Meanwhile, the influences of the freeplay nonlinearity on shimmy behaviours are examined in detail. Impacts of stochastic lateral disturbances on the shimmy of the landing gear system are performed via time history and recurrence plots. Our results show that the interaction between the freeplay nonlinearity and the random load induces a significant reduction in the critical shimmy velocity, which has an adverse impact on the stability of the nose landing gear of an aircraft.
Regenerative Brake Blending in Electric Hypercars: Benchmarking and Implementation
Authors: Senofieni Rodrigo , Bassi Federico , Corno Matteo , Savaresi Sergio Matteo , Savaia Gianluca
Published: October 2024

This paper presents a novel Regenerative Brake Blending (RBB) strategy for an electric hypercar, framing it as a multi-objective problem. These include thermal and lifespan management of various components plus maximizing energy recovery. We begin by mathematically modelling each subsystem of the RBB layout. Then, we define an acausal offline optimal control problem to establish a benchmark solution; subsequently we propose a causal real-time control strategy inspired by the Equivalent Consumption Minimization Strategy (ECMS). The proposed real-time strategy shows a performance loss of 1.6% compared to the benchmark underscoring the efficacy of the proposed RBB strategy in maximizing energy recuperation while considering for brake temperatures.
Indoor Tyre Tread Wear Testing Driven by Outdoor Data Clustering
Authors: Maglia Lorenzo , Fantin Davide , Pontoglio Stefano , Stella Matteo , Sabbioni Edoardo
Published: October 2024

Wear is becoming a topic of major attention for tyres, affecting also other performances. Therefore, its estimation is of utter importance under several points of view, such as predictive maintenance and vehicle dynamics controllers. Indoor testing is emerging as an alternative way for predicting wear compared to on-road outdoor tests, which nowadays represent the standard methodology. Indoor tests, in fact, are performed in a more controllable environment, reducing testing time and costs. However, several challenges must be faced to reproduce indoor the same wear rate/shape obtained in real on-road working conditions. The present paper focuses one of the critical aspects for indoor testing: the definition of the load cycle to be applied to a tyre, i.e. the time history of forces, slip and angles to be provided as an input to the wear machine. Specifically, a clustering approach able to extract from outdoor data a limited set of manoeuvres representative of a given outdoor wear track is proposed.
Trailer Reversing Supported by Steer-by-Wire
Authors: Liu Chang , Roempke Jakob , Klomp Matthijs , Drugge Lars
Published: October 2024

Backing up a trailer can be a daunting task, even for experienced drivers. The main challenge being the unstable property of car-trailer kinematics when reversing. With steer-by-wire systems, the mechanical connection between the steering wheel and the road wheels is replaced by an electrical connection. This means that road wheels no longer have to be directly connected to the steering wheel input. The aim of this paper is to help the driver to steer the trailer directly by stabilising the car-trailer kinematics during reversal. This is achieved by developing a steer-by-wire system coupled with a closed-loop trailer reversal control using the necessary feedback. How to obtain this feedback is further investigated in this paper as well as how to use the steering wheel input and torque feedback to interact with the backup assist function. The developed control and user interaction is subjectively and objectively evaluated using computer simulation and a physical prototype of a vehicle equipped with steer-by-wire.

The results from the simulation experiments demonstrate that drivers with and without experience of driving a trailer can do the wanted manoeuvres with higher accuracy as well as within a short time span with the controller that is developed in this work. The results from the real life experiments also appears to indicate that the system can remove stress from the driver and move the trailer in an accurate way during a parking manoeuvre.
Optimal Braking and Steering Control Under Split Friction on Curved Roads
Authors: Karyotakis Ektor , Yang Derong , Jonasson Mats , Sjöberg Jonas
Published: October 2024

This paper aims to maximize deceleration on split friction roads by combining steering and individual wheel braking. For this, a previously tested optimization problem is adapted to curved roads. The optimal brake force and steering allocation is investigated as a function of the split friction asymmetry. Results show that low friction is more detrimental to maximum braking on the inner side of the curve due to load transfer. Finally, the paper showcases a control strategy for braking on split friction, which enhances safety and manoeuvrability in critical split friction scenarios.
A Fallback Approach for In-Lane Stop on Curved Roads Using Differential Braking
Authors: Sung Jihoon , Choi Seungwon , Huh Kunsoo
Published: October 2024

Due to the importance of safety in the development of Automated Driving Systems (ADS), research is ongoing on fallback functions for ADS. Scenarios involving steering actuator failures during curved road driving are particularly dangerous, with limited available fallback options. This paper proposes a method for achieving a safer in-lane stop using differential braking when steering actuator failure occurs. Lateral motion is induced by the difference in longitudinal forces between the left and right sides, facilitating an in-lane stop maneuver. The vehicle’s lateral behavior under differential braking and changes in front-wheel steering angle are modeled. A model-based estimator using a Kalman filter estimates the vehicle’s state and steering angle. Based on these estimations and lane information, a controller employing a linear quadratic regulator (LQR) is developed. The effectiveness of the differential braking in-lane stop system is validated through simulation.
Study on Continuous Road Friction Measurement Under Various Environmental Conditions
Authors: Kageyama Ichiro , Watanabe Atsushi , Kuriyagawa Yukiyo , Haraguchi Tetsunori , Kaneko Tetsuya , Nishio Minoru
Published: October 2024

This paper deals with a study to construct a road friction characteristic database as the first step in building a system to estimate road friction characteristics ahead, which is one of the major issues in traffic safety. To achieve this goal, we proposed a new method that can continuously measure the peak μ in the μ-s characteristic and showed the measurement results on different road surfaces. Based on these results, in this paper we measure the friction characteristics of snow and ice surfaces at a well-maintained test site and present the continuous μ-s characteristics on the surfaces and the peak μ regions on each surface. Furthermore, measurements are also performed on ordinary roads under snowy conditions, and a comparison with the results from the proving ground, it is shown that we need to examine the dynamics of the μ-s characteristics.
Physics-Informed Neural Network for Mining Truck Suspension Parameters Identification
Authors: Wu Mingyu , Wang Yafei , Zhang Yichen , Li Zexing
Published: October 2024

Mining truck suspensions are prone to performance degradation under complex external excitation of the mining area, leading to high safety risks and maintenance costs. However, the lack of unsprung kinematic information and harsh operating environments lead to inadequate accuracy of current physical models. On the other hand, data-driven methods partially address the issue of incomplete information, but suffer from the absence of interpretability and generalization. To address these challenges, this paper introduces a Physics-Informed Neural Network (PINN) for precise suspension characteristic identification of mining trucks. Specifically, the physical model of the longitudinal-vertical dynamics of the mining truck is established. Then, based on the model, baseline values of suspension parameters are regressed through the instrumental variable method. Therefore, the hybrid modeling architecture is established to precisely identify suspension parameters by utilizing a recurrent neural network. Under this architecture, the states of the mining truck can be effectively updated. Real truck experiments demonstrate the proposed hybrid model outperforms traditional physical and data-driven models in estimating suspension nonlinear parameters and truck dynamic characteristics under typical longitudinal motions.
A Way Beyond Drifting: Cornering at the Unexploited Region of Dynamics
Authors: Lu Hangyu , Wu Xiaodong , Yan Liang
Published: October 2024

Linear range considerations in the tire-road contact restrict the potential of dynamic control designs of passenger vehicles, while strong nonlinear dynamics such as drifting are intrinsically dangerous. In this paper, based on the chassis with independent wheel drive/brake torque control, we propose a model-based strategy to exploit the potentials of all four tires in combined slips to elevate the cornering performance in critical maneuvers. The model-inversed results indicate that the maximal achievable steady-state (SS) yawing is larger than the widely-used boundary for control system design. Nonlinear dynamics around the created stable motions are further analyzed by plotting phase planes. With feedback control incorporated, the proposed strategy is verified in simulations for both local and global dynamics. The method also shows a distinctive availability of tuning different vehicles into desired driving characteristics and elevating their performance levels through independent powertrains.
Higher-order-operator corrections to phase-transition parameters in dimensional reduction
Authors: Chala Mikael , Criado Juan Carlos , Gil Luis , Miras Javier López
Published: October 2024

Abstract

The dynamics of phase transitions (PT) in quantum field theories at finite temperature is most accurately described within the framework of dimensional reduction. In this framework, thermodynamic quantities are computed within the 3-dimensional effective field theory (EFT) that results from integrating out the high-temperature Matsubara modes. However, strong-enough PTs, observable in gravitational wave (GW) detectors, occur often nearby the limit of validity of the EFT, where effective operators can no longer be neglected. Here, we perform a quantitative analysis of the impact of these interactions on the determination of PT parameters. We find that they allow for strong PTs in a wider region of parameter space, and that both the peak frequency and the amplitude of the resulting GW power spectrum can change by more than one order of magnitude when they are included. As a byproduct of this work, we derive equations for computing the bounce solution in the presence of higher-derivative terms, consistently with the EFT power counting.
Weyl-Lewis-Papapetrou coordinates, self-dual Yang-Mills equations and the single copy
Authors: Cardoso Gabriel Lopes , Mahapatra Swapna , Nagy Silvia
Published: October 2024

Abstract

We consider the dimensional reduction to two dimensions of certain gravitational theories in D ≥ 4 dimensions at the two-derivative level. It is known that the resulting field equations describe an integrable system in two dimensions which can also be obtained by a dimensional reduction of the self-dual Yang-Mills equations in four dimensions. We use this relation to construct a single copy prescription for classes of gravitational solutions in Weyl-Lewis-Papapetrou coordinates. In contrast with previous proposals, we find that the gauge group of the Yang-Mills single copy carries non-trivial information about the gravitational solution. We illustrate our single copy prescription with various examples that include the extremal Reissner-Nordstrom solution, the Kaluza-Klein rotating attractor solution, the Einstein-Rosen wave solution and the self-dual Kleinian Taub-NUT solution.
A holographic model of magnetohydrodynamics with fortuitous SO(3) symmetry
Authors: Wang Yanqi , Hu Peng-Ju , Pang Yi
Published: October 2024

Abstract

We study magnetohydrodynamics using holography. The gravity model is closely related to the STU supergravity in five dimensions and admits an analytical black brane solution carrying the conserved charge dual to the magnetic 1-form symmetry of the magnetohydrodynamic system. The black brane solution features a fortuitous SO(3) symmetry, providing a new symmetry principle for describing the magnetohydrodynamics. Since the bulk theory contains multiple 2-form gauge fields, the resistivity becomes matrix-valued. We find that the antisymmetric part of the resistivity matrix exhibits novel features depending on the UV cut-off of the theory. We also compute the shear and bulk viscosities and find that the bulk viscosity is proportional to the shear viscosity. Remarkably, the proportionality constant is exactly what is required for conformality, despite the zeroth-order energy-momentum tensor not being trace-free.
The double scaling limit of randomly coupled Pauli XY spins
Authors: Watanabe Ryota
Published: October 2024

Abstract

We consider the double scaling limit of a model of Pauli spin operators recently studied in Hanada et al. [1] and evaluate the moments of the Hamiltonian by the chord diagrams. We find that they coincide with those of the double scaled SYK model, which makes it more likely that this model may play an important role in the study of holography. We compare the model with another previously studied model. We also speculate on the form of the Hamiltonian in the double scaling limit.
On Extensions of Set-Valued Homomorphisms “modulo K”
Authors: Jabłońska Eliza , Jabłoński Wojciech
Published: October 2024

Let X be a group, Y be a monoid, K be a submonoid of Y and $$n(Y):=2^Y\setminus \{\emptyset \}$$

n

(
Y
)

:
=

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Y

\

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∅
}

. In the paper we prove that under some additional assumptions set-valued K-homomorphism $$G:S\rightarrow n(Y)$$

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:
S
→
n
(
Y
)

defined on a subgroup S of X can be extended to a set-valued K-homomorphism $$F:X\rightarrow n(Y)$$

F
:
X
→
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(
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.
A method for temperature sensor and model selection for machine tool thermal error modelling using ANFIS and ANN
Authors: Ariaga Nemwel , Longstaff Andrew , Fletcher Simon
Published: October 2024

Thermal errors account for a significant part of the dimensional errors of components produced by precision machine tools. These errors are commonly compensated using predictions from temperature-based empirical models. The accuracy and robustness of these predictions are affected by the locations of temperature sensors used to obtain the model’s input data. Methods for sensor selection found in literature are often difficult to replicate and automate because they require tuning of several hyperparameters. This work presents a sensor and model selection approach that uses proper orthogonal decomposition (POD) and QR pivoting to select a subset of sensors that have been preinstalled in the machine tool as possible model inputs. These sensors are then sorted according to their correlation with the thermal error being modelled. The final set of inputs and thermal error model structure is chosen using Bayesian Information Criterion (BIC) to limit model overfitting. The approach was tested by modelling the Y-axis thermal error measured from air-cutting experiments performed under different spindle speeds and feed rates. This enabled determination of the structure and the choice inputs for Adaptive Neuro Fuzzy Inference System (ANFIS) and Artificial Neural Network (ANN) thermal error models. The accuracy of these models was compared to that of models trained using inputs selected by conventional approaches: the least absolute shrinkage and selection operator (LASSO), fuzzy c-means clustering (FCM), and principal component regression (PCR). The presented approach had better or comparable results to the conventional approaches while using fewer inputs. The presented approach is also well suited for automation compared to conventional approaches that require expert input.
Linkage of Pfister forms over semi-global fields
Authors: Daans Nicolas
Published: October 2024

We study linkage of $$(d+1)$$

(
d
+
1
)

-fold quadratic Pfister forms over function fields in one variable over a henselian valued field of 2-cohomological dimension d. Specifically, we characterise this property in terms of linkage of quadratic Pfister forms over function fields over the residue field of the henselian valued field; in full generality in characteristic different from 2, and for most complete discretely valued fields in characteristic 2. As an application, we obtain a proof that $$(d+2)$$

(
d
+
2
)

-fold quadratic Pfister forms over function fields in one variable over a d-dimensional higher local field are linked.
HLA-G neo-expression modifies genetic programs governing tumor cell lines
Authors: Tronik-Le Roux Diana , Daouya Marina , Poras Isabelle , Desgrandchamps François , Carosella Edgardo D.
Published: October 2024

The development of immunotherapies has proved to be clinically encouraging to re-establish the immune function modified by the expression of immune inhibitory molecules in tumors. However, there are still patients with poor survival rates following treatment. The elucidation of molecular mechanisms triggered by the neo-expression of particular IC in tumors would constitute a major step toward better understanding tumor evolution and would help to design future clinical protocols. To this end, we investigate the modifications triggered by the neo-expression of the immune checkpoints HLA-G in ccRCC tumor cells. We demonstrate, for the first time, that HLA-G modifies key genes implicated mainly in tumor development, angiogenesis, calcium flow and mitochondria dynamics. The involvement of HLA-G on the expression of genes belonging to these pathways such as ADAM-12, NCAM1 and NRP1 was confirmed by the CRISPR/Cas9-mediated edition of HLA-G. The data reveal multifaceted roles of HLA-G in tumor cells which are far beyond the well-known function of HLA-G in the immune anti-tumor response. This warrants further investigation of HLA-G and these new partners in tumors of different origin so as to propose future new treatments to improve health patient’s outcome.
Development and validation of a new tool to estimate early mortality in patients with advanced cancer treated with immunotherapy
Authors: De Giglio Andrea , Leonetti Alessandro , Comito Francesca , Filippini Daria Maria , Mollica Veronica , Rihawi Karim , Peroni Marianna , Mazzaschi Giulia , Ricciotti Ilaria , Carosi Francesca , Marchetti Andrea , Rosellini Matteo , Gagliano Ambrogio , Favorito Valentina , Nobili Elisabetta , Gelsomino Francesco , Melotti Barbara , Marchese Paola Valeria , Sperandi Francesca , Di Federico Alessandro , Buti Sebastiano , Perrone Fabiana , Massari Francesco , Pantaleo Maria Abbondanza , Tiseo Marcello , Ardizzoni Andrea
Published: October 2024

Background

Immune checkpoint inhibitors (ICIs) are standard treatments for advanced solid cancers. Resistance to ICIs, both primary and secondary, poses challenges, with early mortality (EM) within 30–90 days indicating a lack of benefit. Prognostic factors for EM, including the lung immune prognostic index (LIPI), remain underexplored.

Methods

We performed a retrospective, observational study including patients affected by advanced solid tumors, treated with ICI as single agent or combined with other agents. Logistic regression models identified factors associated with EM and 90-day progression risks. A nomogram for predicting 90-day mortality was built and validated within an external cohort.

Results

In total, 637 patients received ICIs (single agent or in combination with other drugs) for advanced solid tumors. Most patients were male (61.9%), with NSCLC as the prevalent tumor (61.8%). Within the cohort, 21.3% died within 90 days, 8.4% died within 30 days, and 34.5% experienced early progression. Factors independently associated with 90-day mortality included ECOG PS 2 and a high/intermediate LIPI score. For 30-day mortality, lung metastasis and a high/intermediate LIPI score were independent risk factors. Regarding early progression, high/intermediate LIPI score was independently associated. A predictive nomogram for 90-day mortality combining LIPI and ECOG PS achieved an AUC of 0.76 (95% CI 0.71–0.81). The discrimination ability of the nomogram was confirmed in the external validation cohort (n = 255) (AUC 0.72, 95% CI 0.64–0.80).

Conclusion

LIPI and ECOG PS independently were able to estimate 90-day mortality, with LIPI also demonstrating prognostic validity for 30-day mortality and early progression.
The impact of non-structured PSA testing on prostate cancer-specific mortality on New Zealand Māori men
Authors: Matti Bashar , Nguyen Cindy H. , Lyndon Mataroria P. , Zargar-Shoshtari Kamran
Published: October 2024

Objectives

To assess the impact of differences in Prostate-Specific Antigen (PSA) testing rates on prostate cancer (PCa) diagnosis and PCa-specific mortality among Māori men in a New Zealand (NZ) population.

Patients and Methods

Māori men aged 40 years or older, without a history of PCa, with a PSA test between 2006 and 2018 were included. The cohort was divided into two groups; the “screened group” (ScG) consisting of men who had at least one PSA test every four years or less, and the “non-screened group” (non-SG). We measured the rate of cancer diagnoses and used competing risk analysis to assess survival.

Results

The study cohort included 63,939 Māori men, with 37,048 (58%) in the ScG. PCa was more frequently diagnosed in the ScG (3.7% vs. 3.0%, P < 0.001). A higher proportion of high-grade cancers were found in the non-SG (32.7% vs. 25.6%, P = 0.001). The 10-year cancer-specific survival was significantly higher in the ScG (99.4% vs. 98.5%, P < 0.001). In a multivariable risk model, PSA testing frequency was an independent predictor of PCa mortality. (HR 2.43, [95% CI 1.97–3.01], P < 0.001).

Conclusions

In a cohort of only Māori men, lower PSA testing rates were associated with a higher risk of PCa-related death. Therefore, regular PSA testing for Māori could improve cancer-specific survival among Māori men. Regular PSA testing should be considered a priority area for improving PCa survival in this population.
Tumor hypoxia unveiled: insights into microenvironment, detection tools and emerging therapies
Authors: Ciepła Joanna , Smolarczyk Ryszard
Published: October 2024

Hypoxia is one of the defining characteristics of the tumor microenvironment (TME) in solid cancers. It has a major impact on the growth and spread of malignant cells as well as their resistance to common treatments like radiation and chemotherapy. Here, we explore the complex functions of hypoxia in the TME and investigate its effects on angiogenesis, immunological evasion, and cancer cell metabolism. For prognostic and therapeutic reasons, hypoxia identification is critical, and recent developments in imaging and molecular methods have enhanced our capacity to precisely locate underoxygenated areas inside tumors. Furthermore, targeted therapies that take advantage of hypoxia provide a potential new direction in the treatment of cancer. Therapeutic approaches that specifically target hypoxic conditions in tumors without causing adverse effects are being led by hypoxia-targeted nanocarriers and hypoxia-activated prodrugs (HAPs). This review provides an extensive overview of this dynamic and clinically significant area of oncology research by synthesizing current knowledge about the mechanisms of hypoxia in cancer, highlighting state-of-the-art detection methodologies, and assessing the potential and efficacy of hypoxia-targeted therapies.