HAL will be down for maintenance from Friday, June 10 at 4pm through Monday, June 13 at 9am. More information
Skip to Main content Skip to Navigation

Investigating Stability of Driver-Vehicle System under Aperiodic Sampling Measurements

Abstract : High-speed rails have a significant driving safety requirement than other public transport because of faster speed and an increasing public demand. However, the particularity of train driving often leads to driver’s susceptible to fatigue. Under this consideration, last decade has seen widespread adoption of ADAS in rail-based transportation industry, specifically driver fatigue detection system. ADAS is meant to help the train drivers. The trajectory planner in ADAS guides the driver to maintain a level of velocity (v) and acceleration (a) to go from station A to station B, by considering various factors as fuel efficiency, road terrain, traffic and also the state of the driver from the driver fatigue detection system. However, sometimes due to bad lighting conditions/ bad driver position/ faulty sensor, the accurate information about the train and the driver state may be delayed. The aperiodic unavailability of the driver and the train state to the ADAS system raises concern about the train dynamics stability and safety. Therefore, consideration of uncertainty in driver’s and train’s state during train stability analysis becomes essential. For this purpose, a model-based approach is employed to approximate ADAS-Driver-Train interaction and prove stability of driver advisory train control system. For the stability study, the system consisting of Driver-Train in open-loop is considered as a sampled-data system and ADAS as a controller. Further, the input-delay approach is used to transform the sampled-data system to time-varying delay system. Further, timedependent Lyapunov functionals and convexification arguments are used to derive stability criteria in terms of LMI conditions. The criteria allows to estimate the maximum allowable delay in driver and train state measurement to guarantee train dynamics stability.
Document type :
Complete list of metadata

Contributor : Abes Star :  Contact
Submitted on : Friday, January 14, 2022 - 11:02:08 AM
Last modification on : Saturday, April 9, 2022 - 3:39:11 AM
Long-term archiving on: : Friday, April 15, 2022 - 6:31:56 PM


Version validated by the jury (STAR)


  • HAL Id : tel-03525967, version 1



Ayush Kumar Jain. Investigating Stability of Driver-Vehicle System under Aperiodic Sampling Measurements. Automatic. Université Polytechnique Hauts-de-France, 2021. English. ⟨NNT : 2021UPHF0036⟩. ⟨tel-03525967v1⟩



Record views


Files downloads