This study highlights the challenge of motion sickness (MS) in autonomous vehicles (AVs), providing a comprehensive review of assessing, predicting, and preventing this issue with a special focus on vehicle dynamics and control-based approaches. Unlike previous studies, this review bridges the gap between MS prediction models and vehicle dynamics-based mitigation strategies by presenting an integrated perspective. Effective mitigation requires accurate and reliable prediction. In this context, motion-based prediction approaches, recognised for their practicality, cost-effectiveness, and promising results, are examined in detail with particular focus on ISO-based methods and sensory conflict theory-based models. The importance of identifying MS triggers and validating these models experimentally is also emphasised, alongside recent trends in customised approaches addressing individual variability in MS susceptibility. The study then investigates mitigation strategies centred on vehicle dynamics and control systems, due to their potential for directly controlling motion triggers, calling for tailored and integrated approaches. Furthermore, the critical role of trajectory planning and tracking algorithms in mitigating MS is reviewed, emphasising their potential through optimal control and the incorporation of MS metrics into cost functions. Additionally, integrating trajectory planning with active chassis systems is identified as a promising direction for reducing MS. The study concludes by underscoring the importance of optimised, personalised, integrated and connected vehicle dynamics and control-based methods to effectively mitigate MS in AVs. Finally, a future horizons approach, supported by a vision roadmap, is introduced as a means to address current challenges, define research directions, and ultimately advance the adoption of AVs with minimum MS.

An accurate method is needed to estimate the lateral loads acting externally on road vehicles such that transient aerodynamic loads and driver response can be studied in-situ. The aim of this work is to develop a Kalman filter that can be practically applied to estimate external lateral loads using measurements from sensors that are commonly installed by manufacturers on modern road vehicles. An appraisal of the accuracy of the estimates – and the estimate uncertainties – is presented using real-world experiments performed with a test vehicle in the presence of crosswinds. A network of surface pressure taps was installed on the vehicle body to provide a reference estimation of the aerodynamic loads. The effect of making different assumptions about the process, measurement and cross-covariance matrices – as well as a Gaussian random walk and a latent force model of the unknown loads – on the accuracy and precision of the estimates is discussed and recommendations are given for best practice. Given a calibrated single-track model, the method can be applied to any road vehicle legally operating on public roads and has potential to be used as a low-cost method to collect large datasets describing road and crosswind disturbances on public road networks.

Subjective vehicle stability evaluation is generally conducted during closed-loop driving in which the driver controls the vehicle through transient manoeuvres and evaluate how the vehicle responds to steering inputs, especially how the slip angle builds up. To conduct such evaluation in moving base, driving simulators require that the fed vehicle response to steering inputs is representative. Limited simulator workspace often requires motion scaling, introducing errors in planar dynamics This work, therefore, investigates how the scaling of the planar motion and the slip filtering should be performed in a driving simulator, including the relative relationships between lateral acceleration, yaw rate and slip rate. Two strategies were developed based on the scaling of planar circular motion: one retaining radius information, and the other retaining velocity information. Both strategies avoided filtering the slip rate, as simulations show that the slip rate should be separated from the high-pass filtering process in cueing algorithms and that the scaling should be equal to that of the yaw rate to avoid false cues. A subjective assessment was conducted, and the results indicate advantages for retaining radius information and conclusively the advantage of unfiltered slip information in motion cueing for stability evaluation.

The road transport sector, a major consumer of global energy, relies predominantly on oil-based fuels and contributes significantly to greenhouse gas emissions. Enhancing fuel efficiency through improved vehicle aerodynamics is essential for sustainable mobility. However, crosswind disturbances compromise aerodynamic performance by increasing drag and rolling resistance, particularly for heavy-duty vehicles. This study investigates the impact of extreme crosswind on vehicle energy consumption and dynamic behaviour by considering driver steering response under extreme conditions at different delay times. A two-way coupled aerodynamic and vehicle dynamics simulation framework is employed to capture these interactions. The findings highlight the critical role of driver skills, i.e., prompt steering by driver effectively mitigates energy losses, whereas delayed or abrupt corrections exacerbate rolling resistance through pronounced tyre slip angles. For example, delayed steering response of the driver (e.g., 1.0 second delay) increases energy consumption by 77% when compared to 44% maximum increase for prompt steering of the driver. These results underscore the complex interplay between aerodynamic forces and driver-induced dynamics in shaping vehicle energy efficiency under crosswind conditions.

Some of the strongest wind -induced lateral perturbations of the vehicle -driver system on bridges are observed when passing the towers. Occupants may feel uncomfortable or unsafe as a result. The aims of this work are to characterise the wind velocity profile observed in the wakes of bridge towers and understand the mechanisms through which the vehicle -driver system responds. A test vehicle was repeatedly driven across 5 cable -supported bridges with towers, of which 4 have been studied. Observed changes in wind speed were between 7 and 20 m/s with reference wind speeds of 14 to 25 m/s. The spatial periods of the wind profiles varied between 1.0 and 3.5 vehicle lengths giving disturbances at frequencies of 0.7 to 3.2 Hz at 60 to 80 km/h. The results show that the driver overcompensates for the changes in aerodynamic loading at the towers and the handling response of the vehicle is dominated by steering input - rather than aerodynamic input - once the driver initiates steering compensation. It is also shown, in agreement with an existing conceptual model, that the amplitude of the driver's steering response is linearly related to the change in the vehicle's yaw rate immediately preceding the compensation attempt.

Rolling resistance dictates a large part of the energy consumption of trucks. Therefore, it is necessary to have a sound understanding of the parameters affecting rolling resistance. This article proposes a semi-physical thermodynamic tyre rolling resistance model, which captures the essential properties of rolling resistance, such as transient changes due to temperature effects and the strain-amplitude dependency of the viscous properties. In addition, the model includes cooling effects from the surroundings. Both tyre temperature and rolling resistance are obtained simultaneously in the simulation model for each time step. The nonlinear viscoelasticity in rubber is modelled using the Bergström–Boyce model, where the viscous creep function is scaled with temperature changes. The cooling of the tyre is considered with both convective and radiative cooling. Moreover, the article explains different material parameters and their physical meaning. Additionally, examples of how the model could be used in parameter studies are presented.

The steer-by-wire (SbW) system is seen as the next generation of vehicle steering system. However, there is a possibility of system failure, and it is not yet clear how failure modes will impact driving behaviour. This work studies the impact of different SbW failure modes on driving safety. Firstly, potential failure modes in the SbW system were identified with the help of a hazard and operability (HAZOP) study. Secondly, a physical model based steering force feedback, with the possibility to simulate the failure modes, was implemented in Matlab/Simulink. Third, two test scenarios were constructed, including driving on a country road at 70 km/h and driving on a highway at 110 km/h. Additionally, a driver-in-the-loop experiment was performed using a stationary driving simulator, where subjective and objective data was collected. Then, in terms of result analysis, both subjective and objective evaluation methods were used for severity assessment. Finally, the result of the severity analysis in the form of yaw rate is shown.

Electric and hybrid propulsion systems for articulated vehicles have been gaining increased attention, with the aim to decrease exhaust particle emissions. However, the more environmentally-friendly electric or hybrid articulated vehicles are expected to have increased nonexhaust pollution-related sources because of their significantly increased mass compared with conventional vehicles. One of the main sources of nonexhaust pollution is tire wear, which could potentially cancel the benefits of removing the exhaust through electrification. Tire wear is mainly affected by internal (tire structure and shape) and external (suspension configuration, speed, road surface, etc.) factors. This work focuses on suspension systems and, more specifically, on the ability of active and semiactive suspensions to decrease tire wear in an articulated vehicle. In this direction, an articulated vehicle model that incorporates the tread in its modeling is built to study tire wear during cornering over a class C road. A novel active suspension design based on the H approach is suggested in this work and is compared with passive, semiactive, and other active suspension systems. The suspension systems are also compared mainly with regard to tire wear levels but also with other vehicle performance aspects (i.e., comfort and road holding). The Hop active suspension design is the most effective in decreasing tire wear, with decreases of about 8% to 11%, but without neglecting the rest of the objectives.

Background: Rolling resistance and aerodynamic losses cause a significant part of a truck’s energy consumption. Therefore there is an interest from both vehicle manufacturers and regulators to measure these losses to understand, quantify and reduce the energy consumption of vehicles. On-road measurements are particularly interesting because it enables testing in various ambient conditions and road surfaces with vehicles in service. Objective: Common driving loss measurement devices require unique instrumented measurement wheels, which hinders effective measurements of multiple tyre sets or measurements of vehicles in service. For this purpose, the objective is to develop a novel load-sensing device for measuring braking or driving torque. Methods: The strength of the measurement device is calculated using finite element methods, and the output signal is simulated using virtual strain gauge simulations. In addition to the signal simulation, the device is calibrated using a torsional test rig. Results: The simulation results confirm that the device fulfils the strength requirements and is able to resolve low torque levels. The output signal is simulated for the novel cascaded multi-Wheatstone bridge using the strains extracted from the finite element analysis. The simulations and measurements show that the measurement signal is linear and not sensitive to other load directions. The device is tested on a truck, and the effort of mounting the device is comparable to a regular tyre change. Conclusions: A novel driving loss measurement device design is presented with an innovative positioning of strain gauges decoupling the parasitic loads from the driving loss measurements. The design allows on-road testing using conventional wheels without requiring special measurement wheels or instrumentation of drive shafts, enabling more affordable and accurate measurements.

Driving simulators are increasingly important in vehicle development, benefiting from hardware and motion cueing algorithm (MCA) advancements. However, current state-of-the-art MCAs are optimising with regards to a vehicle fixed vestibular system, ignoring active and passive head movements during manoeuvres. Research shows that drivers actively move their heads to focus their gaze and passively stabilising it during involuntary trunk movements, resulting in significant differences between vehicle and head yaw angles. Humans isolate trunk and head movement in the range of 0.1–1.0 Hz, suggesting neck-driven gaze stabilisation. This behaviour is not accounted for in current MCAs, warranting an investigation. This study develops a driver gaze model to enhance motion cueing strategies and compares it to existing methods. Findings indicate significant discrepancies between vehicle and estimated head yaw rate in winter testing with high slip angles, and that omitting vestibular models and separating the slip angle in the yaw feedback improves the motion cueing with regards to induced head movements. Further, the results shows that there is a clear relationship between motion cueing, visual feedback, and induced driver head movement. In conclusion, driver gaze models can improve motion cueing strategies in driving simulators, and thus the study highlights the need for considering driver gaze behaviour and provides insights for tuning and optimising MCAs.