Browsing by Author "Papaioannou, Georgios"

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    Fundamentals of motion planning for mitigating motion sickness in automated vehicles
    (IEEE, 2021-12-28) Htike, Zaw; Papaioannou, Georgios; Siampis, Efstathios; Velenis, Efstathios; Longo, Stefano
    This paper investigates the fundamentals of motion planning for minimizing motion sickness in transportation systems of higher automation levels. The optimum velocity profile is sought for a predefined road path from a specific starting point to a final one within specific and given boundaries and constraints in order to minimize the motion sickness and the journey time. An empirical approach based on British standard is used to evaluatemotion sickness. The tradeo between minimizing motion sickness and journey time is investigated through multi-objective optimization by altering the weighting factors. The correlation between sickness and journey time is represented as a Pareto front because of their conflicting relation. The compromise between the two components is quantified along the curve, while the severity of the sickness is determined using frequency analysis. In addition, three case studies are developed to investigate the eect of driving style, vehicle speed, and road width, which can be considered among the main factors aecting motion sickness. According to the results, the driving style has higher impact on both motion sickness and journey time compared to the vehicle speed and the road width. The benefit of higher vehicle speed gives shorter journey time while maintaining relatively lower illness rating compared with lower vehicle speed. The eect of the road width is negligible on both sickness and journey time when travelling on a longer road.The results pave the path for the development of vehicular technologies to implement for real-world driving from the outcomes of this paper.
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    Investigation of seat suspensions with embedded negative stiffness elements for isolating bus users’ whole-body vibrations
    (Society of Automotive Engineers, 2021-03-17) Papaioannou, Georgios; Sekulic, Dragan; Velenis, Efstathios; Antoniadis, Ioannis
    Bus drivers are a group at risk of often suffering from musculoskeletal problems, such as low-back pain, while bus passengers on the last-row seats experience accelerations of high values. In this paper, the contribution of K-seat in decreasing the above concern is investigated with a detailed simulation study. The K-seat model, a seat with a suspension that functions according to the KDamper concept, which combines a negative stiffness element with a passive one, is benchmarked against the conventional passive seat (PS) in terms of comfort when applied to different bus users’ seats. More specifically, it is tested in the driver’s and two different passengers’ seats, one from the rear overhang and one from the middle part. For the benchmark shake, both are optimized by applying excitations that correspond to real intercity bus floor responses when it drives over a real road profile. Then a human model is placed on the seats in order to compare their optimum solutions in terms of the user’s whole-body vibrations (WBVs), using objective comfort metrics. Based on the results, the K-seat improves significantly the comfort of the users (~92%) compared to the PS, while it achieves a similar decrease in the maximum values of the user’s back accelerations (~97%).
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    Multi-criteria evaluation for sorting motion planner alternatives
    (MDPI, 2022-07-11) Papaioannou, Georgios; Htike, Zaw; Lin, Chenhui; Siampis, Efstathios; Longo, Stefano; Velenis, Efstathios
    Automated vehicles are expected to push towards the evolution of the mobility environment in the near future by increasing vehicle stability and decreasing commute time and vehicle fuel consumption. One of the main limitations they face is motion sickness (MS), which can put their wide impact at risk, as well as their acceptance by the public. In this direction, this paper presents the application of motion planning in order to minimise motion sickness in automated vehicles. Thus, an optimal control problem is formulated through which we seek the optimum velocity profile for a predefined road path for multiple fixed journey time (JT) solutions. In this way, a Pareto Front will be generated for the conflicting objectives of MS and JT. Despite the importance of optimising both of these, the optimum velocity profile should be selected after taking into consideration additional objectives. Therefore, as the optimal control is focused on the MS minimisation, a sorting algorithm is applied to seek the optimum solution among the pareto alternatives of the fixed time solutions. The aim is that this solution will correspond to the best velocity profile that also ensures the optimum compromise between motion comfort, safety and driving behaviour, energy efficiency, journey time and riding confidence.
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    Path-tracking control strategy for enhanced comfort in all-wheel-steering autonomous vehicles
    (Springer, 2024-10-13) Lin, Chenhui; Papaioannou, Georgios; Siampis, Efstathios; Velenis, Efstathios
    In this paper, a path-tracking controller is developed for an autonomous vehicle with All-Wheel-Steering (AWS) capability. Based on nonlinear model predictive control, the proposed controller is formulated in a way that allows the manipulation of vehicle’s attitude during path-tracking. With high-fidelity vehicle dynamics simulation, the controller is examined at various velocities up to the limit handling condition. Comparison is carried out in the aspects of path-tracking, ride comfort and motion sickness, between the implementation with a constant yaw angle reference (referred to as crab steering) and the nominal steering behaviour for negotiating the same path. The ride comfort metric suggested by ISO-2631 is used to capture the benefits of the crab steering approach against the nominal case, and the simulation results reveal that crab steering is able to enhance the ride comfort for AWS vehicles in double lane-change and slalom manoeuvres.