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.

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.

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.

Remote driving plays an essential role in coordinating automated vehicles in some challenging situations. Due to the changed driving environment, the experiences and behaviors of remote drivers would undergo some changes compared to conventional drivers. To study this, a continuous real-life and remote driving experiment is conducted under different driving conditions. In addition, the effect of steering force feedback (SFF) on the driving experience is also investigated. In order to achieve this, three types of SFF modes are compared. According to the results, no SFF significantly worsens the driving experience in both remote and real-life driving. Additionally, less force and returnability on steering wheel are needed in remote driving, and the steering force amplitude appears to influence the steering velocity of remote drivers. Furthermore, there is an increase in lane following deviation during remote driving. Remote drivers are also prone to driving at lower speeds and have a higher steering reversal rate. They also give larger steering angle inputs when crossing the cones in a slalom manoeuvre and cause the car to experience larger lateral acceleration. These findings provide indications on how to design SFF and how driving behavior and experience change in remote driving.

Autonomous 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 Frenetbased 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.

Knowing the tire pressure during driving is essential since it affects multiple tire properties such as rolling resistance, uneven wear, and how prone the tire is to tire bursts. Tire temperature and cavity pressure are closely tied to each other; a change in tire temperature will cause an alteration in tire cavity pressure. This article gives insights into which tire temperature measurement position is representative enough to estimate pressure changes inside the tire, and whether the pressure changes can be assumed to be nearly isochoric. Climate wind tunnel and road measurements were conducted where tire pressure and temperature at the tire inner liner, the tire shoulder, and the tread surface were monitored. The measurements show that tires do not have a uniform temperature distribution. The ideal gas law is used to estimate the tire pressure from the measured temperatures. The results indicate that of the compared temperature points, the inner liner temperature is the most accurate for estimating tire pressure changes (average error 0.63%), and the pressure changes during driving are nearly isochoric. This conclusion can be drawn because the ratio between inner liner temperature and tire pressure is nearly constant, and the pressure can be simulated well using the isochoric gas law.