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Viewing 1 to 30 of 4562
2017-04-06
Event
This session focusing on vehicle ride comfort, addressing issues such as ride evaluation, suspension tuning, occupant biomechanics, seating dynamics, semi-active and active suspension and vehicle elastomeric components. Topics may include vehicle ride motion smoothness and control balancing, structural shake, impact harshness and after shake, brake judder/pulsation, smooth road shake/shimmy/nibble, power hop, launch shudder, freeway hop and any other phenomena affecting ride comfort.
2017-04-06
Event
2017-04-05
Event
As information and entertainment to and from the vehicle (Telematics) become more prolific it is critical to increase our understanding of how the driver understands and uses Telematics functions. Equally critical is how those functions impact the driver. This session will address those issues.
2017-04-05
Event
Visual perception continues to be a critical aspect of overall driver performance. This session offers presentations highlighting new developments designed to provide better support for driver rearward vision, better understanding of how to measure light and its effects on drivers’ eyes, and better understanding of how drivers accomplish the visually difficult task of negotiating intersections.
2017-04-05
Event
As information and entertainment to and from the vehicle (Telematics) become more prolific it is critical to increase our understanding of how the driver understands and uses Telematics functions. Equally critical is how those functions impact the driver. This session will address those issues.
2017-04-04
Event
Aging mobility is important to the automotive industry for the following reasons: • 37% of the population is over age 50 • 52% of vehicles sold in 2012 were to > 55 years of age consumers. • A 65 year old is 4x more likely to buy a new car than a 25 year old. Presentations will cover how this group will have unique issues associated with it that will need to be addressed by the automotive industry as they design vehicles for this ever growing population.
2017-04-04
Event
Designing vehicles with good ergonomics is one of the many factors needed to achieve high customer satisfaction. A basic source for comfort (or discomfort) lies in the vehicle’s seats. To design for seat comfort requires knowledge of the size of the driver, the structure of the seat, the position of the seat in the vehicle and the trip duration. Papers offers in this session could include topics such as seat back angle, vehicle packaging and trip duration.
2017-04-04
Event
Designing vehicles with good ergonomics is one of the many factors needed to achieve high customer satisfaction. A basic source for comfort (or discomfort) lies in the vehicle’s seats. To design for seat comfort requires knowledge of the size of the driver, the structure of the seat, the position of the seat in the vehicle and the trip duration. Papers offers in this session could include topics such as seat back angle, vehicle packaging and trip duration.
2017-03-28
Technical Paper
2017-01-0409
Divyanshu Joshi, Anindya Deb, Clifford Chou
Abstract It is recognized that there is a dearth of studies that provide a comprehensive understanding of vehicle-occupant system dynamics for various road conditions, sitting occupancies and vehicle velocities. In the current work, an in-house-developed 50 degree-of-freedom (DOF) multi-occupant vehicle model is employed to obtain the vehicle and occupant biodynamic responses for various cases of vehicle velocities and road roughness. The model is solved using MATLAB scripts and library functions. Random road profiles of Classes A, B, C and D are generated based on PSDs (Power Spectral Densities) of spatial and angular frequencies given in the manual ISO 8608. A study is then performed on vehicle and occupant dynamic responses for various combinations of sitting occupancies, velocities and road profiles. The results obtained underscore the need for considering sitting occupancies in addition to velocity and road profile for assessment of ride comfort for a vehicle.
2017-03-28
Technical Paper
2017-01-0433
Yang Xing, Chen Lv, Wang Huaji, Hong Wang, Dongpu Cao
Abstract Recently, the development of braking assistance system has largely benefit the safety of both driver and pedestrians. A robust prediction and detection of driver braking intention will enable driving assistance system response to traffic situation correctly and improve the driving experience of intelligent vehicles. In this paper, two types unsupervised clustering methods are used to build a driver braking intention predictor. Unsupervised machine learning algorithms has been widely used in clustering and pattern mining in previous researches. The proposed unsupervised learning algorithms can accurately recognize the braking maneuver based on vehicle data captured with CAN bus. The braking maneuver along with other driving maneuvers such as normal driving will be clustered and the results from different algorithms which are K-means and Gaussian mixture model (GMM) will be compared.
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