Determining the Parameters of Feeling for a Mechanism of Seat Adjustment

2017 ◽  
Author(s):  
Abhilash CHOUBEY ◽  
RAJESH PAL ◽  
Kotanageswararao Puli ◽  
Pankaj Maheshwari ◽  
Sandeep Raina
Keyword(s):  
Seat Adjustment

The Simulation Study for Auto Electrical Seat Controller Based on Fuzzy Control Technology

2011 ◽  
Vol 383-390 ◽  
pp. 7328-7331
Author(s):  
Lan Jiang Zhang ◽  
Gui Jie Wang
Keyword(s):  
Control System ◽  
Fuzzy Control ◽  
Effective Means ◽  
Nonlinear Function ◽  
Control Technology ◽  
Highly Nonlinear ◽  
Adjustment System ◽  
The Mathematical Model ◽  
Seat Adjustment ◽  
Controlled Object

Designed the control system policy for automobile electric seat using fuzzy control technology, therefore established its control model by Fuzzy Logic Toolbox, and carried on the off-line simulation to choose controller's optimum control parameters. From the dynamic viewpoint, the auto electric seat adjustment system is not only a complex nonlinear function which includes the location of the DC servo motor and the speed, but also contains serious nonlinear coupling interference, so the system is a highly nonlinear strong coupling, variable multivariable system. Application of traditional control methods (such as traditional PID) is difficult to meet its order requirements, so the research is highly robust method of intelligent control is an effective way to solve the problem. Fuzzy control technology has become the field in which drawn greater attention and researched in recent years. It doesn’t depend on the mathematical model of controlled object, has a good robustness, and nonlinear control characteristics, so it is an effective means to control the object with time-varying, non- linear parameters. In this paper, fuzzy control technology to achieve the orders of auto electric seat adjustment control system functions in the Literature [1], and the tracking of the system was simulated.

Optimisation-based approach for determining driver seat adjustment range for vehicles

2011 ◽  
Vol 57 (2/3) ◽  
pp. 148 ◽  
Author(s):  
Jared Gragg ◽  
Jingzhou Yang ◽  
James David Long
Keyword(s):  
Seat Adjustment

Intervention on seat adjustment among drivers of forest tractors

1997 ◽  
Vol 19 (3) ◽  
pp. 231-237 ◽  
Author(s):  
Merja Perkiö-Mäkelä ◽  
Hilkka Riihimäki
Keyword(s):  
Seat Adjustment

Development and Evaluation of a Computational Human Performance Model of In-vehicle Manual and Speech Interactions

2018 ◽  
Vol 62 (1) ◽  
pp. 1642-1642
Author(s):  
Heejin Jeong ◽  
Yili Liu
Keyword(s):  
Completion Time ◽  
Human Performance ◽  
Human Subjects ◽  
Manual Control ◽  
Task Completion ◽  
Task Completion Time ◽  
Vehicle Systems ◽  
Lower Lumbar ◽  
Digital Simulations ◽  
Seat Adjustment

Usability evaluation traditionally relies on costly and time-consuming human-subject experiments, which typically involve developing physical prototypes, designing usability experiment, and recruiting human subjects. To minimize the limitations of human-subject experiments, computational human performance models can be used as an alternative. Human performance models generate digital simulations of human performance and examine the underlying psychological and physiological mechanisms to help understand and predict human performance. A variety of in-vehicle information systems (IVISs) using advanced automotive technologies have been developed to improve driver interactions with the in-vehicle systems. Numerous studies have used human subjects to evaluate in-vehicle human-system interactions; however, there are few modeling studies to estimate and simulate human performance, especially in in-vehicle manual and speech interactions. This paper presents a computational human performance modeling study for a usability test of IVISs using manual and speech interactions. Specifically, the model was aimed to generate digital simulations of human performance for a driver seat adjustment task to decrease the comfort level of a part of driver seat (i.e., the lower lumbar), using three different IVIS controls: direct-manual, indirect-manual, and voice controls. The direct-manual control is an input method to press buttons on the touchscreen display located on the center stack in the vehicle. The indirect-manual control is to press physical buttons mounted on the steering wheel to control a small display in the dashboard-cluster, which requires confirming visual feedback on the cluster display located on the dashboard. The voice control is to say a voice command, “ deflate lower lumbar” through an in-vehicle speaker. The model was developed to estimate task completion time and workload for the driver seat adjustment task, using the Queueing Network cognitive architecture (Liu, Feyen, & Tsimhoni, 2006). Processing times in the model were recorded every 50 msec and used as the estimates of task completion time. The estimated workload was measured by percentage utilization of servers used in the architecture. After the model was developed, the model was evaluated using an empirical data set of thirty-five human subjects from Chen, Tonshal, Rankin, & Feng (2016), in which the task completion times for the driver seat adjustment task using commercial in-vehicle systems (i.e., SYNC with MyFord Touch) were recorded. Driver workload was measured by NASA’s task load index (TLX). The average of the values from the NASA-TLX’s six categories was used to compare to the model’s estimated workload. The model produced results similar to actual human performance (i.e., task completion time, workload). The real-world engineering example presented in this study contributes to the literature of computational human performance modeling research.

Seat adjustment – capacity and repeatability among occupants in a modern car

Ergonomics ◽  
2008 ◽  
Vol 51 (2) ◽  
pp. 232-241 ◽  
Author(s):  
Bertil Jonsson ◽  
Hans Stenlund ◽  
Mats Y. Svensson ◽  
Ulf Björnstig
Keyword(s):  
Seat Adjustment

scholarly journals Driving-induced lower back pain: Investigation of causes and recommendations with TRIZ

F1000Research ◽  
2021 ◽  
Vol 10 ◽  
pp. 871
Author(s):  
Poh Kiat Ng ◽  
Muhammad Syafiq Syed Mohamed ◽  
Jian Ai Yeow
Keyword(s):  
Back Pain ◽  
Lower Back Pain ◽  
Cost Effective ◽  
Inert Atmosphere ◽  
Medical Treatments ◽  
Traumatic Injuries ◽  
Lower Back ◽  
Chain Analysis ◽  
Seat Adjustment ◽  
Posterior Position

Background: Driving-induced lower back pain (DLBP) is associated with long driving times and awkward postures. Nonetheless, its actual causes and solutions remain unclear due to intervening causes from activities of daily living and traumatic injuries. This study investigated the causes and recommendations for DLBP using the theory of inventive problem solving (TRIZ). Methods: A cause-and-effect chain analysis (CECA) was conducted based on discussions with 19 ergonomics experts from Malaysia. Engineering contradictions were formulated according to the causes and associated with the parameters of the TRIZ system. These parameters were then intersected in the contradiction matrix to extract the inventive principles. Finally, recommendations were made based on these principles. Results: CECA uncovered the design- and posture-related causes of DLBP. It was implied that missing seat adjustment controls might cause drivers to sit with their knees positioned higher than their hips. This issue causes an excessive posterior pelvic tilt, resulting in DLBP. To address this issue, an inert atmosphere involving the addition of inflatable bubble wraps to elevate the posterior position was recommended. Conclusion: While there have been studies on DLBP, the present study demonstrated originality by using TRIZ to preliminarily but systematically investigate and resolve DLBP. Further triangulations, prototyping, experimentations, and verifications were not possible due to time and budgetary constraints. Nevertheless, this research uncovered the TRIZ-integrated perspectives on ergonomic solutions to DLBP that are more cost-effective than medical treatments or design overhauls.

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