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This paper’s aim is modeling and simulation of an advanced controller design for a novel mechatronics system that consists of a hydrostatic journal bearing with servo control. The proposed mechatronic system has more worth in tribology applications as compared to the traditional hydrostatic bearing which has limited efficiency and poor performance because of lower stiffness and load-carrying capacity. The proposed mechatronic system takes advantage of active lubrication to improve stiffness, rotor’s stability and load-carrying capacity.

The current work proposes extended state observer-based controller to control the active lubrication for hydrostatic journal bearing. The advantage of using observer is to estimate unknown state variables and lumped effects because of unmodeled dynamics, model uncertainties, and unknown external disturbances. The effectiveness of the proposed mechatronic system is checked against the traditional hydrostatic bearing.

Proposed mechatronics active hydrostatic journal bearing system is checked against traditional hydrostatic journal bearing. It is found that novel active hydrostatic journal bearing with servo control has good tribology performance factors such as stiffness, less rotor vibration, no wear and friction under starting conditions and high load-carrying capacity under different conditions of spindle speed, temperature, initial oil pressure and external disturbance. The result shows that proposed mechatronics system has more worth in rotary tribology applications.

The current manuscript designs a novel active hydrostatic journal bearing system with servo control. The mathematical model has advantages in term of estimating unknown state variables and lumped effects because of unmodeled dynamics, model uncertainties and unknown external disturbances. The result shows improvement in dynamic characteristics of a hydrostatic journal bearing under different dynamic conditions.

Autonomous vehicles (AVs) have the potential to transform the infrastructure, mobility and social well-being paradigms in New Zealand (NZ) amid its unprecedented population and road safety challenges. But, public acceptance, co-evolution of regulations and AV technology based on interpersonal and institutional trust perspectives pose significant challenges. Previous theories and models need to be more comprehensive to address trust influencing autonomous driving (AD) factors in natural settings. Therefore, this study aims to find key AD factors corresponding to the chain of human-machine interaction (HMI) events happening in real time and formulate a guiding framework for the successful deployment of AVs in NZ.

This study utilized a comprehensive literature review complemented by an AV users’ study with 15 participants. AV driving sprints were conducted on low, medium and high-density roads in Auckland, followed by 15 ideation workshops to gather data about the users’ observations, feelings and attitudes towards the AVs during HMI.

This research study determined nine essential trust-influencing AD determinants in HMI and legal readiness domains. These AD determinants were analyzed, corresponding to eight AV events in three phases. Subsequently, a guiding framework was developed based on these factors, i.e. human-machine interaction autonomous driving events relationship identification framework (HMI-ADERIF) for the deployment of AVs in New Zealand.

This study was conducted only in specific Auckland areas.

This study is significant for advanced design research and provides valuable insights, guidelines and deployment pathways for designers, practitioners and regulators when developing HMI Systems for AD vehicles.

This study is the first-ever AV user study in New Zealand in live traffic conditions. This user study also claimed its novelty due to AV trials in congested and fast-moving traffic on the four-lane motorway in New Zealand. Previously, none of the studies conducted AV user study on SUV BMW vehicle and motorway in real-time traffic conditions; all operations were completely autonomous without any input from the driver. Thus, it explored the essential autonomous driving (AD) trust influencing variables in human factors and legal readiness domains. This research is also unique in identifying critical AD determinants that affect the user trust, acceptance and adoption of AVs in New Zealand by bridging the socio-technical gap with futuristic research insights.