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2016-06-15
Technical Paper
2016-01-1782
Kyoung-Jin Chang, Dong Chul Park
Abstract This paper discusses approaches to emotionally improve the driving sound based on Active Sound Design (ASD). In the first step, target sound design methods are suggested in order to represent the vehicle’s concept and brand image via a driving sound. In this method, formant filter and musical chords are applied to the target sound synthesis. In the second step, a technique to make a target sound realistic in ASD system is discussed, which enables to stimulate the customers' emotion. In this technique, the process to simulate a musical instrument sound for a vivid driving sound and synthesize the sound with FIR filter is studied. Finally, the improved driving sound is demonstrated in ASD system.
2016-04-06
WIP Standard
J1163
This SAE standard specifies a method and the device for use in determining the position of the Seat Index Point (SIP) for any kind of seat. This SAE document provides a uniform method for defining the location of the SIP in relation to some fixing point on the seat.
2016-04-05
Journal Article
2015-01-9152
André Lundkvist, Arne Nykänen, Roger Johnsson
Abstract Many of the information systems in cars require visual attention, and a way to reduce both visual and cognitive workload could be to use sound. An experiment was designed in order to determine how driving and secondary task performance is affected by the use of information sound signals and their spatial positions. The experiment was performed in a driving simulator utilizing Lane Change Task as a driving scenario in combination with the Surrogate Reference Task as a secondary task. Two different signal sounds with different spatial positions informed the driver when a lane change should be made and when a new secondary task was presented. Driving performance was significantly improved when both signal sounds were presented in front of the driver. No significant effects on secondary task performance were found. It is recommended that signal sounds are placed in front of the driver, when possible, if the goal is to draw attention forward.
2016-04-05
Technical Paper
2016-01-0164
Jamy Li, Xuan Zhao, Mu-Jung Cho, Wendy Ju, Bertram F. Malle
Abstract Autonomous vehicles represent a new class of transportation that may be qualitatively different from existing cars. Two online experiments assessed lay perceptions of moral norms and responsibility for traffic accidents involving autonomous vehicles. In Experiment 1, 120 US adults read a narrative describing a traffic incident between a pedestrian and a motorist. In different experimental conditions, the pedestrian, the motorist, or both parties were at fault. Participants assigned less responsibility to a self-driving car that was at fault than to a human driver who was at fault. Participants confronted with a self-driving car at fault allocated greater responsibility to the manufacturer and the government than participants who were confronted with a human driver at fault did.
2016-04-05
Journal Article
2016-01-0340
Tina Hull, Monika A. Minarcin
Abstract Applications using industrial robotics have typically led to establishing a safeguarded space encompassing a wide radius around the robot. Operator access to this hazard zone was restricted by a combination of means, such as hard guarding, safeguarding, awareness means, and personal protective equipment. The introduction of collaborative robots is redefining safeguarding requirements. Many collaborative robots have inherently safe designs that enable an operator and a robot to work within a shared, collaborative workspace. New technology in industrial robotics has opened up opportunities for collaborative operation. Collaborative operation could include either industrial or collaborative robots, depending on its application. The current defined modes of collaborative operation are hand guiding; speed and separation monitoring; safety-rated monitored stop; and, power and force limiting.
2016-04-05
Journal Article
2016-01-0337
Ana M. Djuric, R.J. Urbanic, J.L. Rickli
Abstract Contemporary manufacturing systems are still evolving. The system elements, layouts, and integration methods are changing continuously, and ‘collaborative robots’ (CoBots) are now being considered as practical industrial solutions. CoBots, unlike traditional CoBots, are safe and flexible enough to work with humans. Although CoBots have the potential to become standard in production systems, there is no strong foundation for systems design and development. The focus of this research is to provide a foundation and four tier framework to facilitate the design, development and integration of CoBots. The framework consists of the system level, work-cell level, machine level, and worker level. Sixty-five percent of traditional robots are installed in the automobile industry and it takes 200 hours to program (and reprogram) them.
2016-04-05
Technical Paper
2016-01-1147
Xiaofeng Yin, Han Lu, Xiaojuan Zhao, Xiaohua Wu, Yongtong Zhang
Abstract To improve the comprehensive performance of vehicles equipped with stepped automatic transmission (SAT), the optimization of gearshift schedule should take into account various performance such as power performance, fuel economy, etc. In addition, the SATs would become more acceptable if the optimized gearshift schedule could also be individualized to reflect the driver’s expectation on vehicle performance to a reasonable extent. For the purpose of ensuring the comprehensive performance and improving the individual-ability (i.e., the ability to adapt to different driver’s performance expectation) of vehicles equipped with SAT, a linear weighted method has been proposed to construct a performance evaluation function, which applies different weights to represent driver’s expectation on performance by using these weights to multiply the normalized value of each sub-performance index.
2016-04-05
Journal Article
2016-01-1303
Haiqing Xu, Chang Jin, Hong Zhou, Yi Zhou
Abstract On the study of reducing the disturbance on driver’s attention induced by low frequency vehicle interior stationary noise, a subjective evaluation is firstly carried out by means of rank rating method which introduces Distraction Level (DL) as evaluation index. A visual-finger response test is developed to help evaluating members better recognize the Distraction Level during the evaluation. A non-linear back propagation artificial neural network (BPANN) is then modeled for the prediction of subjective Distraction Level, in which linear sound pressure RMS amplitudes of five Critical Band Rates (CBRs) from 20 to 500Hz are selected as inputs of the model. These inputs comprise an input vector of BPANN. Furthermore, active noise equalization (ANE) on DL is realized based on Filtered-x Least Mean Square (FxLMS) algorithm that controls the gain coefficients of inputs of trained BPANN.
2016-04-05
Journal Article
2016-01-1304
Tadayoshi Fukushima, Hitoshi Takagi, Toshio Enomoto, Hiroyuki Sawada, Tomoyuki Kaneda
Abstract Interior noise caused by exterior air flow, or wind noise, is one of the noise-and-vibration phenomena for which a systematic simulation method has been desired for enabling their prediction. One of the main difficulties in simulating wind noise is that, unlike most other noises from the engine or road input, wind noise has not one but two different types of sources, namely, convective and acoustic ones. Therefore, in order to synthesize the interior sound pressure level (SPL), the body sensitivities (interior SPL/outer source level) for both types of sources have to be considered. In particular, sensitivity to the convective input has not been well understood, and hence it has not been determined. Moreover, the high-frequency nature of wind noise (e.g., the main energy range extends up to 4000 Hz) has limited the effective application of CAE for determining body sensitivities, for example, from the side window glass to the occupants’ ears.
2016-04-05
Technical Paper
2016-01-1121
Fang Liao, Weimin Gao, Yan Gu, Fei Kang, Yinan Li, Cheng Wang
Abstract Noise signals of the driver’s right ear include those of engine, environment, chassis dynamometer, loaded gears and unloaded gears when they are recorded in full vehicle on chassis dynamometer in semi-anechoic room. Gear rattle noise signals of the driver’s right ear caused by unloaded gear pairs can’t be identified or quantified directly. To solve the problems, relative approaches are used to identify and quantify the gear rattle noise signals. Firstly, the rattle noise signals of the driver’s right ear are filtered by human ear characteristic functions and steady noise signals are extracted by regression and smoothing processes. The noise signals are regressed at 200ms interval in the hearing critical frequency bands and smoothed in the flanking frequencies. Then, the noise relative approaches are obtained by subtracting the steady noise signals from the filtered noise signals, which are the transient noise signals of the unloaded gear pairs inducing the rattle noise.
2016-04-05
Technical Paper
2016-01-0114
Chris Schwarz, Timothy Brown, John Lee, John Gaspar, Julie Kang
Abstract Distracted driving remains a serious risk to motorists in the US and worldwide. Over 3,000 people were killed in 2013 in the US because of distracted driving; and over 420,000 people were injured. A system that can accurately detect distracted driving would potentially be able to alert drivers, bringing their attention back to the primary driving task and potentially saving lives. This paper documents an effort to develop an algorithm that can detect visual distraction using vehicle-based sensor signals such as steering wheel inputs and lane position. Additionally, the vehicle-based algorithm is compared with a version that includes driving-based signals in the form of head tracking data. The algorithms were developed using machine learning techniques and combine a Random Forest model for instantaneous detection with a Hidden Markov model for time series predictions.
2016-04-05
Technical Paper
2016-01-0115
Dev S. Kochhar, Hong Zhao, Paul Watta, Yi Murphey
Abstract Lane change events can be a source of traffic accidents; drivers can make improper lane changes for many reasons. In this paper we present a comprehensive study of a passive method of predicting lane changes based on three physiological signals: electrocardiogram (ECG), respiration signals, and galvanic skin response (GSR). Specifically, we discuss methods for feature selection, feature reduction, classification, and post processing techniques for reliable lane change prediction. Data were recorded for on-road driving for several drivers. Results show that the average accuracy of a single driver test was approx. 70%. It was greater than the accuracy for each cross-driver test. Also, prediction for younger drivers was better.
2016-04-05
Technical Paper
2016-01-0111
Hiroaki Tanaka, Daisuke Takemori, Tomohiro Miyachi
Abstract Establishing drivers’ trust in the automated driving system is critical to the success of automated vehicle. The focus of this paper is how to make drivers drive automated vehicles with confidence during braking events. In this study, 10 participants drove a test vehicle and experienced 24 different deceleration settings each. Prior to each drive, we indicated to each participant the expected brake starting and stopping position. During each drive, participants would first maintain a set speed, and then stop the vehicle when they see a signal to apply the brakes. After each drive, we asked the participants’ perceived safety about the deceleration setting he/she just experienced. The results revealed that ‘jerk’ have significant influence on drivers’ perceived safety.
2016-04-05
Technical Paper
2016-01-0118
Shinji Niwa, Mori Yuki, Tetsushi Noro, Shunsuke Shioya, Kazutaka Inoue
Abstract This paper presents detection technology for a driver monitoring system using JINS MEME, an eyewear-type wearable device. Serious accidents caused by human error such as dozing while driving or inattentive driving have been increasing recently in Japan. JINS MEME is expected to contribute to reducing the number of traffic deaths by constantly monitoring the driver with an ocular potential sensor. This paper also explains how a driver’s drowsiness level can be estimated from information on their blink rate, which can be calculated from the ocular potential.
2016-04-05
Technical Paper
2016-01-0119
Preeti J. Pillai, Veeraganesh Yalla, Kentaro Oguchi
Abstract This paper is an extension of our previous work on the CHASE (Classification by Holistic Analysis of Scene Environment) algorithm, that automatically classifies the driving complexity of a road scene image during day-time conditions and assigns it an ‘Ease of Driving’ (EoD) score. At night, apart from traffic variations and road type conditions, illumination changes are a major predominant factor that affect the road visibility and the driving easiness. In order to resolve the problem of analyzing the driving complexity of roads at night, a brightness detection module is incorporated in our end-to-end nighttime EoD system, which computes the ‘brightness factor’ (bright or dark) for that given night-time road scene. The brightness factor along with a multi-level machine learning classifier is then used to classify the EoD score for a night-time road scene.
2016-04-05
Journal Article
2016-01-0145
Madeleine Gibson, John Lee, Vindhya Venkatraman, Morgan Price, Jeffrey Lewis, Olivia Montgomery, Bilge Mutlu, Joshua Domeyer, James Foley
Abstract The rapid increase in the sophistication of vehicle automation demands development of evaluation protocols tuned to understanding driver-automation interaction. Driving simulators provide a safe and cost-efficient tool for studying driver-automation interaction, and this paper outlines general considerations for simulator-based evaluation protocols. Several challenges confront automation evaluation, including the limited utility of standard measures of driver performance (e.g., standard deviation of lane position), and the need to quantify underlying mental processes associated with situation awareness and trust. Implicitly or explicitly vehicle automation encourages drivers to disengage from driving and engage in other activities. Thus secondary tasks play an important role in both creating representative situations for automation use and misuse, as well as providing embedded measures of driver engagement.
2016-04-05
Technical Paper
2016-01-0144
Morgan A. Price, Vindhya Venkatraman, Madeleine Gibson, John Lee, Bilge Mutlu
Abstract Increasingly sophisticated vehicle automation can perform steering and speed control, allowing the driver to disengage from driving. However, vehicle automation may not be capable of handling all roadway situations and driver intervention may be required in such situations. The typical approach is to indicate vehicle capability through displays and warnings, but control algorithms can also signal capability. Psychophysical methods can be used to link perceptual experiences to physical stimuli. In this situation, trust is an important perceptual experience related to automation capability that is revealed by the physical stimuli produced by different control algorithms. For instance, precisely centering the vehicle in the lane may indicate a highly capable system, whereas simply keeping the vehicle within lane boundaries may signal diminished capability.
2016-04-05
Technical Paper
2016-01-0158
Toshio Ito, Arata Takata, Kenta Oosawa
Abstract Automation of vehicles can be expected to improve safety, comfort and efficiency, and is being developed in various countries. Introduction of automated driving can be ranked from 0 to 5 (0: no automation, 1: driver assistance, 2: partial automation, 3: conditional automation, 4: high automation, 5: full automation). Currently, feasible automation levels are considered to be levels 2 or 3, and human manual take-over from the automated system is needed when the automated system exceeds these levels. In this situation, time required for take-over is an important issue. This study focuses on describing driving simulator experimental results of time required for take-over. The experimental scenario is that the automated system finds an object ahead during automated driving on the highway, and issues a take-over request to the driver. The subject driver can be in the following driver situations: hands-on or hands-off the steering, and strong or weak distractions.
2016-04-05
Technical Paper
2016-01-1542
Shaosong Li, Jiafei Niu, Ren Sheng, Zhixin Yu, Shunhang Zheng, Yongfa Tu
Abstract With motor and reduction mechanism applied to Electric Power Steering (short for EPS) system of automobile, the frictional loss torque of steering system is increased. The common friction compensation control through the sign function of angular velocity or the saturation function of angular velocity is conducted to reduce the frictional loss torque of steering system. However, when the motor used in steering system generates assist torque based on the common friction compensation control, the longitudinal intercepts of steering torque change obviously at different steering wheel angles. The driver will get different frictional loss torque of steering system at different steering wheel angle. The information of steering torque contains the change of steering reaction torque and the frictional loss torque of steering system, so the change of frictional loss torque can cause the fuzzy of road feeling.
2016-04-05
Technical Paper
2016-01-1536
Chung-Kyu Park, Cing-Dao Kan
Abstract In this study, the available metrics to evaluate the crash pulse severity are reviewed and their assessability is investigated by using frontal New Car Assessment Program (NCAP) test data. Linear regression analysis and sled test simulations are conducted. In addition, a new approach is proposed to measure the crash pulse severity and restraint system performance separately and objectively.
2016-04-05
Journal Article
2016-01-1526
Daniel V. McGehee, Cheryl A. Roe, Linda Ng Boyle, Yuqing Wu, Kazutoshi Ebe, James Foley, Linda Angell
Abstract Pedal misapplications may be rare, but the outcomes can be tragic. A naturalistic driving study with 30 drivers was conducted to gain a better understanding of foot pedal behaviors. Foot movements were observed from the moment subjects entered and positioned themselves in their vehicle, and continued through starting the ignition, shifting into gear, accelerating to driving speed, and finally, resting their foot after parking the vehicle. A coding methodology was developed to categorize the various foot movements and behaviors. Over 3,300 startup and parking sequences were coded. This paper describes the unique challenges involved in classifying foot movements and behaviors when drivers’ intentions are not known. For example, hesitant or interrupted foot movements often occurred when a driver was transitioning from a gas pedal press to a brake pedal press.
2016-04-05
Technical Paper
2016-01-1514
Varun Bollapragada, Taewung Kim, Mark Clauser, Jeff Crandall, Jason Kerrigan
Abstract Some rollover testing methodologies require specification of vehicle kinematic parameters including travel speed, vertical velocity, roll rate, and pitch angle, etc. at the initiation of vehicle to ground contact, which have been referred to as touchdown conditions. The complexity of the vehicle, as well as environmental and driving input characteristics make prediction of realistic touchdown conditions for rollover crashes, and moreover, identification of parameter sensitivities of these characteristics, is difficult and expensive without simulation tools. The goal of this study was to study the sensitivity of driver input on touchdown parameters and the risk of rollover in cases of steering-induced soil-tripped rollovers, which are the most prevalent type of rollover crashes. Knowing the range and variation of touchdown parameters and their sensitivities would help in picking realistic parameters for simulating controlled rollover tests.
2016-04-05
Technical Paper
2016-01-1555
Jack Ekchian, William Graves, Zackary Anderson, Marco Giovanardi, Olivia Godwin, Janna Kaplan, Joel Ventura, James R. Lackner, Paul DiZio
Abstract It is widely anticipated that autonomous vehicles will offer increased productivity and convenience by freeing occupants from the responsibility of driving. However, studies indicate that the occurrence of motion sickness in autonomous vehicles will be substantially higher than in conventionally driven vehicles. Occupants of autonomous vehicles are more likely to be involved in performing tasks and activities, such as reading, writing and using a computer or tablet, that typically increase the occurrence of motion sickness. The authors present a novel high bandwidth active suspension system, GenShock®, and tailored control algorithms targeted toward mitigating motion sickness in autonomous vehicles. GenShock actuators can actively push and pull the wheels of a vehicle in order to keep the chassis level and reduce heave, pitch, and roll motion.
2016-04-05
Technical Paper
2016-01-1552
Renato Galluzzi, Andrea Tonoli, Nicola Amati, Gabriele Curcuruto, Piero Conti, Giordano Greco, Andrea Nepote
Abstract The development of suspension systems has seen substantial improvements in the last years due to the use of variable dampers. Furthermore, the efficiency increase in the subsystems within the automotive chassis has led to the use of regenerative solutions, in which electric machines can be employed as generators to recover part of the energy otherwise dissipated. However, the harvesting capability of regenerative suspensions is often limited by friction and inertial phenomena. The former ones waste mechanical energy into heat, while the latter ones hamper the shock absorption by locking the suspension when subject to dynamic excitation. Besides a suitable design and sizing of components, recent research works highlight the use of the so-called motion rectifier to improve energy recovery by constraining the motion of the electric motor to a single sense of rotation.
2016-04-05
Journal Article
2016-01-1553
Akihito Yamamoto, Wataru Tanaka, Takafumi Makino, Shunya Tanaka, Ken Tahara
Abstract This paper reports that estimation accuracy of suspension stroke velocity is increased by considering the damping force delay characteristics to an observer. Thereby ride comfort is improved, using the simple and low-cost semi active suspension systems that use only three vertical acceleration sensors.
2016-04-05
Technical Paper
2016-01-1451
Mingyang Chen, Xichan Zhu, Zhixiong Ma, Lin Li
Abstract In China there are many mixed driving roads which cause a lot of safety problems between vehicles and pedalcyclists. Research on driver behavior under risk scenarios with pedalcyclist is relatively few. In this paper driver brake parameters under naturalistic driving are studied and pedalcyclists include bicyclist, tricyclist, electric bicyclist and motorcyclist. Brake reaction time and maximum brake jerk are used to evaluate driver brake reaction speed. Average deceleration is used to evaluate the effect of driver brake operation. Maximum deceleration is used to evaluate driver braking ability. Driver behaviors collected in China are classified and risk scenarios with pedalcyclist are obtained. Driver brake parameters are extracted and statistical characteristics of driver brake parameters are obtained. Influence factors are analyzed with univariate ANOVA and regression analysis.
2016-04-05
Technical Paper
2016-01-1440
Julia Seeanner, Johnell Brooks, Mary Mossey, Casey Jenkins, Paul Venhovens, Constance Truesdail
Abstract While motorcycle safety frequently focuses on topics like helmet use and engineering aspects such as anti-lock braking systems, little research has investigated aging riders’ use of technologies (i.e., phones, navigation systems, etc.) or the characteristics of older riders (defined as above the age of 40) who use them. This study surveyed a convenience sample of typical motorcycle riders in the United States in order to provide an overview of the types of technologies that riders of different age groups use while riding, problems or concerns about those technologies, as well as rider demographics and riding habits. The sample included 97 riders (84 males and 13 females) between the ages of 20 and 71 years (M= 50.9, SD= 10.6) who were divided into three age groups (under 40 years, between 40 and 50 years, 50 years and older).
2016-04-05
Technical Paper
2016-01-1441
Jonathan Frank Antin, Justin Owens, James Foley, Kazutoshi Ebe, Brian Wotring
Abstract This study presents a long-term examination of the effects of two types of perceptual-cognitive brain training programs on senior driver behavior and on-road driving performance. Seniors (70+) engaged in either a Toyota-designed in-vehicle training program based on implicit learning principles or a commercially available computer-based training program developed by Posit Science. Another group served as a no-contact control group; total enrollment was 55 participants. Participants completed a series of four experimental sessions: (1) baseline pre-training, (2) immediate post-training, (3) 6-9 months post-training, and (4) 12-16 months post-training. Experimental metrics taken at each session included measures of vehicle control and driver glance behavior on public roads.
2016-04-05
Technical Paper
2016-01-1438
Alexander Siefert
Abstract The objective evaluation of occupant comfort is a complex task where numerous aspects such as posture, pressure distribution, internal tissue loads, handling of steering wheel or gear shift have to be taken into consideration. Currently the standard evaluation procedures are hardware tests with human subjects, who are sensitive to all these aspects. However, the reproducibility of subjective tests for the comparison of design variants is a questionable issue and the costs for each test cycle with new prototypes are very high. As an alternative, numerical approaches using human body models such as AnyBody [1], CASIMIR [2] or RAMSIS [3] are applied. Here the issue of reproducibility does not exist and only little effort is required to investigate new setups. However, the disadvantage is that each approach focuses only on one specific aspect of occupant comfort, while in reality the emotions of the occupant are always a combination of all impressions.
2016-04-05
Technical Paper
2016-01-1444
Shayne McConomy, Johnell Brooks, Paul Venhovens, Yubin Xi, Patrick Rosopa, John DesJardins, Kevin Kopera, Kathy Lococo
Abstract The research objective was to measure and understand the preferred seat position of older drivers and younger drivers within their personal vehicles to influence recommended practices and meet the increased safety needs of all drivers. Improper selection of driver’s seat position may impact safety during a crash event and affect one’s capacity to see the roadway and reach the vehicle’s controls, such as steering wheel, accelerator, brake, clutch, and gear selector lever. Because of the stature changes associated with ageing and the fact that stature is normally distributed for both males and females, it was hypothesized that the SAE J4004 linear regression would be improved with the inclusion of gender and age terms that would provide a more accurate model to predict the seat track position of older drivers. Participants included 97 older drivers over the age of 60 and 20 younger drivers between the ages of 30 to 39.
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