Michele Vignati

Network latency remains a fundamental bottleneck in vehicle teleoperation, inducing instability and performance degradation in conventional control methods, while predictive techniques like the Smith Predictor offer a theoretical solution, their efficacy is often compromised by unmodelled dynamics and real-world disturbances. This paper presents the first experimental validation of the Successive Reference-Pose Tracking (SRPT) architecture. By streaming future reference poses rather than direct steering commands, SRPT leverages an onboard Nonlinear Model Predictive Controller to compute optimal vehicle actions while inherently accounting for dynamic constraints and network delays. Real-world human-in-the-loop experiments were conducted with four drivers on a test track featuring cornering, double lane-change, and slalom manoeuvres. Quantitative comparisons at 10 km/h across four modes—manual driving, direct teleoperation, a Smith Predictor, and SRPT—demonstrate that SRPT significantly outperforms other teleoperation methods, reducing cross-track error by up to 66% and yielding smoother, more stable control inputs. Furthermore, SRPT uniquely maintained stability during a proof-of-concept trial at 13 km/h, where it proactively moderated vehicle speed to respect actuator limits—a critical safety behavior absent in other modes. This work provides the first tangible evidence that SRPT is a robust and superior framework for delay-resilient vehicle teleoperation in real-world conditions.

The transition to battery electric vehicles (BEVs) is enabling the significant redesign of key subsystems, including braking systems. This work presents a physics-based optimization framework for the preliminary design of a distributed electro-hydraulic brake-by-wire (DEHB) system tailored for electric vehicles. The DEHB system is modeled as a two-phase actuation process captured through a coupled electro-mechanical and hydraulic model: initial pad–disc clearance closure and subsequent pressure buildup. Sensitivity analysis is employed to identify critical design parameters, and a multi-objective genetic algorithm is used to minimize electrical power consumption, peak current, and maximum torque while satisfying performance constraints. The optimized configuration is benchmarked against commercially available solutions and validated against a multiphysics simulation, showing deviations below 8% for current and power. A dynamic analysis incorporating vehicle-level ABS logic demonstrates the improved performance and energy efficiency of the DEHB system during emergency braking, with a reduction of 50% in required power if compared to a non-optimized system. The results confirm the effectiveness of the proposed method for early-stage sizing and highlight the potential of DEHB architectures in future electric vehicle platforms.

The integration of advanced technologies in agriculture, known as Agriculture 4.0, aims to optimize practices, enhance productivity, and improve sustainability. Despite significant advancements in precision agriculture, ploughing operations have seen limited technological growth, even though they are among the most power-demanding and widely used soil preparation methods. Traditional on-field ploughing tests are irreversible, time-consuming, and costly, highlighting the need for a comprehensive virtual model of ploughing operations within a simulated environment. This study presents the development of a high-fidelity analytical model for ploughing, implemented in a real-time multibody simulation platform, both in software and Human-In-The-Loop (Hu-IL) configurations. The simulation environment incorporates a tractor model rigidly connected to the plough model, receiving contact forces from the field model. The model outputs vehicle dynamics information and ploughing operation data, allowing for operator inputs or simulated inputs. The model is used to perform a sensitivity analysis on ploughing parameters, including tractor speed, soil hardness, ploughing depth, and the number of furrows, to evaluate their impact on energy consumption and operational efficiency. In literature each component (tractor, plough, soil, etc.) is generally analyzed separately form the other; this paper aims to combine all the key factors that contribute to overall fuel consumption instead, considering the non-linearities of each subsystem.

This paper provides a comprehensive overview of the state of the art non-destructive methods for detecting plant biochemical traits through spectral imaging of leafy greens. It offers insights into the various detection techniques and their effectiveness. The review emphasizes the algorithms used for spectral data analysis, highlighting advancements in computational methods that have contributed to improving detection accuracy and efficiency. This systematic review, following the PRISMA 2020 guidelines, explores the applications of non-destructive measurements, techniques, and algorithms, including hyperspectral imaging and spectrometry for detecting a wide range of chemical compounds and elements in lettuce, basil, and spinach. This review focuses on studies published from 2019 onward, focusing on the detection of compounds such as chlorophyll, carotenoids, nitrogen, nitrate, and anthocyanin. Additional compounds such as phosphorus, vitamin C, magnesium, glucose, sugar, water content, calcium, soluble solid content, sulfur, and pH are also mentioned, although they were not the primary focus of this study. The techniques used are showcased and highlighted for each compound, and the accuracies achieved are presented to demonstrate effective detection.

With a shift in the automotive industry’s focus towards sustainability and energy efficiency, optimizing vehicle handling dynamics has been put on a secondary level. Moreover, there is a growing trend towards comfort-oriented design, conversely to the vehicle-handling one. Nevertheless, recent advancements such as the integration of multiple independently controlled electric motors on a vehicle is enabling torque vectoring, which offers a promising opportunity for reconciling these conflicting objectives. This paper proposes a novel approach for jointly improving vehicle handling and energy efficiency performance. Indeed, through advanced simulation techniques, the effects of various suspension configurations are explored to strike a balance between cornering performance and energy consumption. Then, a torque vectoring controller is designed in combination with a meticulous tuning of the suspension setup. This innovative approach of considering the active control design together with the suspensions’ setup allows to obtain superior performances. Indeed, the desired vehicle cornering capabilities can be achieved while also guaranteeing a significantly more efficient vehicle in straight-line running, which covers most of the usual road driving time.

The vehicle sideslip angle or lateral velocity is a measure both for driving stability and for occupant’s subjective perception of safety. With the introduction of vehicle dynamics control systems and automated driving functions, knowledge of this vehicle motion state is required for many control strategies. This article gives an overview on the state of the art on sideslip angle estimation. In contrast to other literature studies on this topic, it focuses on vehicle dynamics based algorithms. The following types of observers are discussed: Kalman Filter-type, recursive least squares (RLS), sliding mode observers (SMO) or nonlinear observers (NLO). Eventually, cascaded observers are used that first estimate some states, which then act as input to the sideslip angle estimator. Since the choice of an observer strategy always depends on the application, this article provides a brief insight into the work of selected research groups that have studied the topic. These examples will help to clarify the presence of many different approaches in the literature. A detailed discussion on vehicle and tire models is not included but referenced to other sources. Finally, this article provides recommendations for two main target groups: First, researchers and engineers that plan to design an algorithm for sideslip angle estimation using deterministic vehicle dynamics based approaches. Second, researchers and engineers planning to include an existing algorithm in an automated driving function that want to learn about advantages and limitations of these types of algorithms.

Torque vectoring is a widely known technique to improve vehicle handling and to increase stability in limit conditions. With the advent of electric vehicles, this is becoming a key topic since it is possible to have distributed powertrains, i.e., multiple motors are adopted, in which each motor is controlled separately from the others. Moreover, electric motors deliver the torque required by the controller faster and more precisely than internal combustion engines, active differentials and conventional hydraulic brakes. The state of the art of Direct Yaw Moment Control (DYC) techniques, ranging from classical to modern control theories, are analyzed and discussed in this paper. The aim is to give an overview of the currently available approaches while identifying their drawbacks regarding performances and robustness when dealing with common issues like model uncertainties, external disturbances, friction limit and common state estimation problems. This contribution analyzes all the steps from the lateral dynamics reference generation to the desired control action computation and allocation to the available actuators. In addition, some of the presented control logic is evaluated in a simulation environment for a passenger car. Results of both open-loop and closed-loop maneuvers allow the comparison and clarification of each control strategy’s key advantages.

Multi-purpose agricultural tractors are vehicles that are usually involved in different operations, including road maintenance in small villages and cultivation of small agricultural plots, particularly in mountainous areas. These vehicles typically feature narrow tracks to enhance manoeuvrability, making rollover stability a critical consideration in operational settings. This characteristic arises from the interplay between the suspension and vehicle chassis. This paper introduces a numerical multi-body model designed to replicate the dynamics of a multi-purpose tractor with a torsional chassis. Model parameters were derived through experimental measurements conducted on an actual vehicle. Static measurements were performed to assess tire and suspension stiffness while tilting tests were performed to establish the static rollover limit of the vehicle. Dynamic tests conducted on a four-post test rig characterised the vehicle’s dynamics. The validated model was utilised to explore the vehicle’s stability by reproducing the static rollover tests and simulating the vehicle’s performance under working conditions on a banked road. The vehicle rollover stability was studied by performing a sensitivity analysis that considered both chassis torsional stiffness and suspension stiffness under different loading conditions. The results indicate a trade-off between frame and suspension stiffnesses that enhances overall vehicle stability.