86 citations · 135 across the 20 of their papers we have counts for
14 papers · 1 filter
Does the testing environment matter? Carsickness across on-road, test-track, and driving simulator conditions
Georgios Papaioannou, Barys Shyrokau
Carsickness has gained significant attention with the rise of automated vehicles, prompting extensive research across on-road, test-track, and driving simulator environments to und…
Reducing Discomfort in Driving Simulators: Motion Cueing for Motion Sickness Mitigation
Varun Kotian, Riender Happee, Barys Shyrokau
Driving simulators are increasingly used in research and development. However, simulators often cause motion sickness due to downscaled motion and unscaled veridical visuals. In th…
Multi-Modal Model Predictive Path Integral Control for Collision Avoidance
Alberto Bertipaglia, Dariu M. Gavrila, Barys Shyrokau
This paper proposes a novel approach to motion planning and decision-making for automated vehicles, using a multi-modal Model Predictive Path Integral control algorithm. The method…
A Vehicle System for Navigating Among Vulnerable Road Users Including Remote Operation
Oscar de Groot, Alberto Bertipaglia, Hidde Boekema +21
We present a vehicle system capable of navigating safely and efficiently around Vulnerable Road Users (VRUs), such as pedestrians and cyclists. The system comprises key modules for…
Efficient Motion Sickness Assessment: Recreation of On-Road Driving on a Compact Test Track
Huseyin Harmankaya, Adrian Brietzke, Rebecca Pham-Xuan +3
The ability to engage in other activities during the ride is considered by consumers as one of the key reasons for the adoption of automated vehicles. However, engagement in non-dr…
A Learning-Based Model Predictive Contouring Control for Vehicle Evasive Manoeuvres
Alberto Bertipaglia, Mohsen Alirezaei, Riender Happee +1
This paper presents a novel Learning-based Model Predictive Contouring Control (L-MPCC) algorithm for evasive manoeuvres at the limit of handling. The algorithm uses the Student-t…
A Nonlinear Model Predictive Control for Automated Drifting with a Standard Passenger Vehicle
Stan Meijer, Alberto Bertipaglia, Barys Shyrokau
This paper presents a novel approach to automated drifting with a standard passenger vehicle, which involves a Nonlinear Model Predictive Control to stabilise and maintain the vehi…
Model Predictive Contouring Control for Vehicle Obstacle Avoidance at the Limit of Handling Using Torque Vectoring
Alberto Bertipaglia, Davide Tavernini, Umberto Montanaro +4
This paper presents an original approach to vehicle obstacle avoidance. It involves the development of a nonlinear Model Predictive Contouring Control, which uses torque vectoring…
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…
Computationally-efficient Motion Cueing Algorithm via Model Predictive Control
Akhil Chadha, Vishrut Jain, Andrea Michelle Rios Lazcano +1
Driving simulators have been used in the automotive industry for many years because of their ability to perform tests in a safe, reproducible and controlled immersive virtual envir…
Comfort-oriented driving: performance comparison between human drivers and motion planners
Yanggu Zheng, Barys Shyrokau, Tamas Keviczky
Motion planning is a fundamental component in automated vehicles. It influences the comfort and time efficiency of the ride. Despite a vast collection of studies working towards im…
Search-Based Task and Motion Planning for Hybrid Systems: Agile Autonomous Vehicles
Zlatan Ajanović, Enrico Regolin, Barys Shyrokau +3
To achieve optimal robot behavior in dynamic scenarios we need to consider complex dynamics in a predictive manner. In the vehicle dynamics community, it is well know that to achie…
Search-based optimal motion planning for automated driving
Zlatan Ajanovic, Bakir Lacevic, Barys Shyrokau +2
This paper presents a framework for fast and robust motion planning designed to facilitate automated driving. The framework allows for real-time computation even for horizons of se…