| Optimal Braking Trajectory Generation for Motion Sickness Minimization Based on High-fidelity Subjective Vertical Conflict Modeling |
| Wenfei Ji, Guangyu Tian, Yunchang Yu |
| School of Vehicle and Mobility, Tsinghua University, Beijing, 100084, China |
|
|
|
Received: June 23, 2025; Revised: September 8, 2025 Accepted: October 21, 2025. Published online: December 22, 2025. |
|
|
|
| ABSTRACT |
|
This study proposes an optimal braking trajectory generation framework for minimizing motion sickness in automated vehicles. In contrast to conventional approaches that rely on statistical metrics such as the Motion Sickness Dose Value (MSDV), this framework explicitly embeds the full nonlinear dynamics of the six-degree-of-freedom Subjective Vertical Conflict (6DOF-SVC) model into a solver-compatible optimization scheme. A robust nonlinear programming formulation, complemented by a warm-start initialization strategy, is developed to ensure reliable convergence. Comparative simulations between MSDV- and SVC-based schemes reveal significantly different braking speed profiles. It is shown that the MSDV model systematically overestimates Motion Sickness Incidence (MSI) by an order of magnitude, rendering it inadequate for braking-focused discomfort modeling. Furthermore, the framework is extended to incorporate active pitch control, which dynamically adjusts vehicle posture during deceleration. The active scheme achieves up to a 91.27% reduction in MSI, and analysis of optimal pitch trajectories reveals that standard quadratic cost formulations fail to exploit its full potential. Finally, the proposed method is validated in the CarMaker simulation environment, confirming its feasibility for real-time motion-sickness-aware control. |
| Key Words:
Motion sickness · Subjective vertical conflict theory · Ride comfort · Automated vehicles · Optimal trajectory generation · Nonlinear programming |
|
Corresponding Author.
Wenfei Ji , Email. 
Preview 
Full text via DOI 
Download Citation
Print
