8 citations · 29 across the 23 of their papers we have counts for
12 papers · 1 filter
Kinematic body responses and perceived discomfort in a bumpy ride: Effects of sitting posture
Marko Cvetkovic, Raj Desai, Georgios Papaioannou +1
The present study investigates perceived comfort and whole-body vibration transmissibility in intensive repetitive pitch exposure representing a bumpy ride. Three sitting strategie…
Modelling individual motion sickness accumulation in vehicles and driving simulators
Varun Kotian, Daan M. Pool, Riender Happee
Users of automated vehicles will move away from being drivers to passengers, preferably engaged in other activities such as reading or using laptops and smartphones, which will str…
Motion Cueing Algorithm for Effective Motion Perception: A frequency-splitting MPC Approach
Vishrut Jain, Andrea Lazcano, Riender Happee +1
Model predictive control (MPC) is a promising technique for motion cueing in driving simulators, but its high computation time limits widespread real-time application. This paper p…
Model Predictive Contouring Control for Vehicle Obstacle Avoidance at the Limit of Handling
Alberto Bertipaglia, Mohsen Alirezaei, Riender Happee +1
This paper proposes a non-linear Model Predictive Contouring Control (MPCC) for obstacle avoidance in automated vehicles driven at the limit of handling. The proposed controller in…
The impact of body and head dynamics on motion comfort assessment
Georgios Papaioannou, Raj Desai, Riender Happee
Head motion is a key determinant of motion comfort and differs substantially from seat motion due to seat and body compliance and dynamic postural stabilization. This paper compare…
Modelling human seat contact interaction for vibration comfort
Raj Desai, Marko Cvetković, Georgios Papaioannou +1
The seat to head vibration transmissibility depends on various characteristics of the seat and the human body. One of these, is the contact interaction, which transmits vibrational…
Computationally efficient human body modelling for real time motion comfort assessment
Raj Desai, Marko Cvetković, Junda Wu +2
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 be…
A new computational perceived risk model for automated vehicles based on potential collision avoidance difficulty (PCAD)
Xiaolin He, Riender Happee, Meng Wang
Perceived risk is crucial in designing trustworthy and acceptable vehicle automation systems. However, our understanding of its dynamics is limited, and models for perceived risk d…
Simulating vibration transmission and comfort in automated driving integrating models of seat, body, postural stabilization and motion perception
Riender Happee, Raj Desai, Georgios Papaioannou
To enhance motion comfort in (automated) driving we present biomechanical models and demonstrate their ability to capture vibration transmission from seat to trunk and head. A comp…
Evaluation of motion comfort using advanced active human body models and efficient simplified models
Raj Desai, Marko Cvetković, Georgios Papaioannou +1
Active muscles are crucial for maintaining postural stability when seated in a moving vehicle. Advanced active 3D non-linear full body models have been developed for impact and com…
Motion comfort and driver feel: An explorative study about their relation in remote driving
Georgios Papaioannou, Lin Zhao, Mikael Nybacka +3
Teleoperation is considered as a viable option to control fully automated vehicles (AVs) of Level 4 and 5 in special conditions. However, by bringing the remote drivers in the loop…
An Unscented Kalman Filter-Informed Neural Network for Vehicle Sideslip Angle Estimation
Alberto Bertipaglia, Mohsen Alirezaei, Riender Happee +1
This paper proposes a novel vehicle sideslip angle estimator, which uses the physical knowledge from an Unscented Kalman Filter (UKF) based on a non-linear single-track vehicle mod…