A High Fidelity Driving Simulation Platform for the Development and Validation of Advanced Driver Assistance Systems

Grottoli, Marco; Heide, Anne van der; Lemmens, Yves

doi:10.1007/978-3-030-29131-0_7

Cited by 3 publications

(5 citation statements)

References 10 publications

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“…The model data was compared with data collected on an instrumented motorcycle. Also, the subjective validation showed good levels of simulator presence (Grottoli et al, 2019). It was also validated with a focus on low speeds of 0m/s and 10m/s.…”

Section: Motoristmentioning

confidence: 91%

Systematic Literature Review: Motorcycle Simulators

Wildner,

Diermeyer

2023

The Evolving Scholar - BMD 2023, 5th Edition

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An increasing number of researchers have started to focus on motorcyclists. An important tool hereby is the use of motorcycle simulators. They can be used to evaluate human-machine interfaces, design future advanced riding systems like forward collision warning, or determine an optimal ergonomic position to reduce mental loads and stress. However, compared to the automotive sector, only a few simulators exist, but they differ greatly. Therefore, this literature review provides an overview of the current state-of-the-art powered two-wheeler simulators. A total of 13 simulators are described in detail, as well as their prioritized research areas, conducted studies, strengths and limitations, their development over the recent years, and their validation.

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Section: Motoristmentioning

confidence: 91%

Systematic Literature Review: Motorcycle Simulators

Wildner,

Diermeyer

2023

The Evolving Scholar - BMD 2023, 5th Edition

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“…The riding scenario presented to the experiment subjects is very similar to the scenario used for the experimental validation of the motorcycle model used in Grottoli et al, 3 where the test data acquired on a real motorcycle were used to validate simulation results. The maneuvers used for model validation were selected to be reproduced here: A30: accelerating from standstill to 30 km h -1 (8.3 ms -1 ), U25: constant turn with 10.5 m radius performed at 25 km h -1 (6.9 ms -1 ), and B12: braking from 30 km h -1 (8.3 ms -1 ) to standstill in 12 m.…”

Section: Riding Scenariomentioning

confidence: 99%

“…The velocity of the simulated vehicle during acceleration and braking was directly compared with the experimental data acquired on a real instrumented motorcycle, where a test rider performed the same maneuvers. 3 For the turning maneuver the ideal speed was considered to be constant. The deviation from this ideal speed was computed as error and integrated over the execution of the maneuvers.…”

Section: Dependent Measuresmentioning

confidence: 99%

“…This torque also included countersteering torque. 3 To stabilize the motorcycle at standstill, the roll dynamics were augmented with dedicated lateral controller. This augmentation was only effective between standstill and 0.5 ms -1 and phased out at 3.0 ms -1 .…”

Section: Riding Simulatormentioning

confidence: 99%

“…The fidelity of a simulator partly depends on the quality of the vehicle dynamics model, as this is the basis for rendering the visual stimuli as well as haptic and motion cueing. 1,2 This topic was addressed in Grottoli et al, 3 where a high fidelity model of a motorcycle was developed based on multibody dynamics theory. The dynamic model is used together with models of motorcycle sub-systems for engine, Continuously Variable Transmission (CVT), brakes, and tires.…”

Section: Introductionmentioning

confidence: 99%

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Motorcycle simulator subjective and objective validation for low speed maneuvering

Grottoli

Mulder

Happee

2022

Proceedings of the Institution of Mechanical Engineers, Part D:

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The use of driving simulators for training and for development of new vehicles is widely spread in the automotive industry. In the last decade, a few motorcycle riding simulators have been developed for similar purposes, with focus on maneuvering at high speed. This article presents the subjective and objective evaluation of a motorcycle riding simulator specifically for low speed longitudinal and lateral maneuvering, between 0 and 10 ms–1. An experiment was conducted with and without platform motion, focusing on three maneuvers: acceleration from standstill, braking to standstill and turning at constant speed. Participants briefly evaluated the fidelity of the simulator after each maneuver and more extensively after each motion condition. Behavioral fidelity was evaluated using experimental data measured on an instrumented motorcycle. Overall, the results show that the participants could reproduce the selected maneuvers without falling or losing balance, reporting a sufficient level of simulator realism. In terms of subjective fidelity, platform motion had a positive effect on simulator presence, significantly increasing the feeling of being involved in the virtual environ0ment. In terms of behavioral fidelity, the comparison between the simulator and experimental results shows good agreement, with a limited positive influence of motion for the braking maneuver, which indicates that for this maneuver the use of motion is beneficial to reproduce the real-life experience and performance.

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