Modelling Neck Postural Stabilization Using Optimal Control Techniques for Dynamic Driving

The goal of this paper is to contribute to the accurate prediction of human body motion by proposing a novel head-neck model for dynamic driving scenarios with complex vehicle motions. While automated vehicles are considered a potential solution to several transportation issues, there are still significant challenges that need to be addressed, including fundamental questions regarding motion comfort and postural stability. Existing standards fail to accurately describe motion comfort, and current head-neck models have limitations, such as their inability to accurately capture human head responses to dynamic perturbations and lack of adaptability to different perturbations, amplitudes, and individual characteristics. To address these challenges, the authors propose a 3D double inverted pendulum model (DIPM) with a total of 6 degrees of freedom (DoF) as an approximation of head-neck system. The proposed model uses Model Predictive Control (MPC) to derive optimal control inputs for head-neck stabilization. The study validates the proposed model against experimental data of anterior-posterior seat translation and rotation from the literature. The results indicate that the model fitted the experimental data with a variance accounted for 82.80 % in translation and 73.15 % in rotation (pitch). The proposed model paves the path for the accurate assessment of occupants’ postural stability in automated vehicles.Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Intelligent Vehicle

Sensor Fusion and Advanced Controller for Connected and Automated Vehicles

Intelligent Vehicle

Reducing Tyre Wear Emissions of Automated Articulated Vehicles through Trajectory Planning

Effective emission control technologies and eco-friendly propulsion systems have been developed to decrease exhaust particle emissions. However, more work must be conducted on non-exhaust traffic-related sources such as tyre wear. The advent of automated vehicles (AVs) enables researchers and automotive manufacturers to consider ways to further decrease tyre wear, as vehicles will be controlled by the system rather than by the driver. In this direction, this work presents the formulation of an optimal control problem for the trajectory optimisation of automated articulated vehicles for tyre wear minimisation. The optimum velocity profile is sought for a predefined road path from a specific starting point to a final one to minimise tyre wear in fixed time cases. Specific boundaries and constraints are applied to the problem to ensure the vehicle’s stability and the feasibility of the solution. According to the results, a small increase in the journey time leads to a significant decrease in the mass loss due to tyre wear. The employment of articulated vehicles with low powertrain capabilities leads to greater tyre wear, while excessive increases in powertrain capabilities are not required. The conclusions pave the way for AV researchers and manufacturers to consider tyre wear in their control modules and come closer to the zero-emission goal.Intelligent Vehicle

Computationally Efficient Human Body Modelling for Real Time Motion Comfort Assessment

Due to the complexity of the human body and its neuromuscular stabilization, it has been challenging to efficiently and accurately predict human motion and capture posture while being driven. Existing simple models of the seated human body are mostly two-dimensional and developed in the mid-sagittal plane exposed to in-plane excitation. Such models capture fore-aft and vertical motion but not the more complex 3D motions due to lateral loading. Advanced 3D full body active human models (AHMs), such as in MADYMO, can be used for comfort analysis and to investigate how vibrations influence the human body while being driven. However, such AHMs are very time-consuming due to their complexity. To effectively analyze motion comfort, a computationally efficient and accurate three dimensional (3D) human model, which runs faster than real time, is presented. The model's postural stabilization parameters are tuned using available 3D vibration data for head, trunk and pelvis translation and rotation. A comparison between AHM and EHM is conducted regarding human body kinematics. According to the results, the EHM model configuration with two neck joints, two torso bending joints, and a spinal compression joint accurately predicts body kinematics.Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Intelligent Vehicle

Optimal Trajectory Planning for Mitigated Motion Sickness: Simulator Study Assessment

In the transition from partial to high automation, occupants will no longer be actively involved in driving. This will allow the use of travel time for work or leisure, where high comfort levels preventing motion sickness are required. In this paper, an optimal trajectory planning algorithm is presented in order to minimise motion sickness in automated vehicles. A predefined path is provided as an input to the algorithm, to generate an optimal path with limited lateral deviation and the corresponding optimal velocity profile, for the minimisation of motion sickness. An optimal control problem is formulated with a cost function combining both motion sickness and travel time. For a sickening curvy road, the algorithm reduced the motion sickness dose value (MSDV) up to 52% depending on the allowed lateral deviation and the weighting on travel time. The efficacy of the proposed algorithm has been evaluated via human-in-the-loop experiments using a moving-base driving simulator. Motion cueing parameters were selected to optimally transmit the sickening stimuli resulting in close to full vibration transmission above 0.2 Hz. During the experiment, the participants were asked to rate their experience based on the standard MIsery SCore ratings. According to these, sickness levels were reduced on average by 65% with reduced motion sickness in all 16 participants.Intelligent Vehicle

Workshop on Multimodal Motion Sickness Detection and Mitigation Methods for Car Journeys

The mass adoption of automated vehicles in the near future will benefit safety (of occupants and pedestrians), the environment (low emissions), and society (accessibility, on-demand travel). There are, however, still challenges that need to be addressed, with one of the most crucial being motion sickness. In automated vehicles, the interior could be transformed into a living room or a working space, allowing occupants to spend their time with non-driving activities. These changes are likely to provoke, and increase, motion sickness incidence. To that end, this workshop will explore the current state of motion sickness detection and mitigation methods from different angles (e.g., closed-loop detection, multimodal motion cues,etc.) through expert talks and reflections, followed by discussions. The workshop will develop an agenda for motion sickness research in automated vehicles, facilitate new research ideas and fruitful collaborations. Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Intelligent Vehicle

2nd Workshop on Multimodal Motion Sickness Detection and Mitigation Methods for Car Journeys - Finding Consensus in the Field

The adoption of automated vehicles will be a positive step towards road safety and environmental benefits. However, one major challenge that still exist is motion sickness. The move from drivers to passengers who will engage in non-driving related tasks as well as the potential change in the layout of the car interior that will come with automated vehicles are expected to result in a worsened experience of motion sickness. The previous workshop [18] highlighted the need for consensus on guidelines regarding study design for motion sickness research. Hence, this workshop will develop a guide for motion sickness research through reflection and discussions on the current methodologies used by experts in the field. Further it will build on the knowledge collected from the previous workshop and will thereby facilitate not only new research ideas and fruitful collaborations but also find a consensus in the field in regard to study design and methodologies.Intelligent Vehicle

Post-anaesthesia pulmonary complications after use of muscle relaxants (POPULAR): a multicentre, prospective observational study

Background Results from retrospective studies suggest that use of neuromuscular blocking agents during general anaesthesia might be linked to postoperative pulmonary complications. We therefore aimed to assess whether the use of neuromuscular blocking agents is associated with postoperative pulmonary complications.Methods We did a multicentre, prospective observational cohort study. Patients were recruited from 211 hospitals in 28 European countries. We included patients (aged >= 18 years) who received general anaesthesia for any in-hospital procedure except cardiac surgery. Patient characteristics, surgical and anaesthetic details, and chart review at discharge were prospectively collected over 2 weeks. Additionally, each patient underwent postoperative physical examination within 3 days of surgery to check for adverse pulmonary events. The study outcome was the incidence of postoperative pulmonary complications from the end of surgery up to postoperative day 28. Logistic regression analyses were adjusted for surgical factors and patients' preoperative physical status, providing adjusted odds ratios (ORadj) and adjusted absolute risk reduction (ARR(adj)). This study is registered with ClinicalTrials. gov, number NCT01865513.Findings Between June 16, 2014, and April 29, 2015, data from 22 803 patients were collected. The use of neuromuscular blocking agents was associated with an increased incidence of postoperative pulmonary complications in patients who had undergone general anaesthesia (1658 [7.6%] of 21 694); ORadj 1.86, 95% CI 1.53-2.26; ARR(adj) -4.4%, 95% CI -5.5 to -3.2). Only 2.3% of high-risk surgical patients and those with adverse respiratory profiles were anaesthetised without neuromuscular blocking agents. The use of neuromuscular monitoring (ORadj 1.31, 95% CI 1.15-1.49; ARR(adj) -2.6%, 95% CI -3.9 to -1.4) and the administration of reversal agents (1.23, 1.07-1.41; -1.9%, -3.2 to -0.7) were not associated with a decreased risk of postoperative pulmonary complications. Neither the choice of sugammadex instead of neostigmine for reversal (ORadj 1.03, 95% CI 0.85-1 center dot 25; ARR(adj) -0.3%, 95% CI -2.4 to 1.5) nor extubation at a train-of-four ratio of 0.9 or more (1.03, 0.82-1.31; -0.4%, -3.5 to 2.2) was associated with better pulmonary outcomes.Interpretation We showed that the use of neuromuscular blocking drugs in general anaesthesia is associated with an increased risk of postoperative pulmonary complications. Anaesthetists must balance the potential benefits of neuromuscular blockade against the increased risk of postoperative pulmonary complications