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Viewing 31 to 60 of 6140
2016-04-05
Technical Paper
2016-01-1546
Dongpil Lee, Bongchoon Jang, Kyongsu Yi, Sehyun Chang, Byungrim Lee
Abstract This paper describes a reference steering feel tracking algorithm for Electric-Power-Steering (EPS) system. Development of the EPS system with intended steering feel has been time-consuming procedure, because the feedforward map-based method has been applied to the conventional EPS system. However, in this study, a three-dimensional reference steering feel surface, which is determined from current vehicle states, is proposed. In order to track the proposed reference steering feel surface, sliding mode approach is applied to second-order steering dynamics model considering a coulomb friction model. An adaptive technique is utilized for robustness against uncertainties. In order to validate the proposed EPS control algorithm, hardware-in-the-loop simulation (HILS) has been conducted with respect to a typical steering test. It is shown that the reference steering feel is realized well by the proposed EPS control algorithm.
2016-04-05
Technical Paper
2016-01-0014
Shun Yang, Weiwen Deng, Haizhen Liu, Rui He, Lei Qian, Wenlong Sun, Ji Gao
Abstract Nowadays, the vehicle market puts forward urgent requirement for new kinds of braking booster because the traditional vacuum booster cannot meet the demands of new energy vehicles anymore. However, one problem that all the new plans should face is how to guarantee an ideal pedal feeling. In this paper, a novel mechatronics braking booster is proposed, and servo motor introduced into the booster makes the assist rate can be adjusted under a great degrees of freedom, so the structural parameters and control parameters of the booster should be determined elaborately to get an optimal pedal feeling. The pedal feeling is always represented by the pedal stoke-force curve which is influenced by different parameters.
2016-04-05
Technical Paper
2016-01-0080
Hiroyuki Miyake
Abstract This paper explains a performance enhancement of the lane guidance function in car navigation systems. In order to achieve intuitive lane guidance, a function is considered that displays lane guidance on an image of the front scene that matches what drivers actually see outside the vehicle. Therefore, two developed items were lane accurate positioning based on image recognition and augmented reality visualization that renders lane guidance images overlaid on the scenery of the road ahead. The eye glance time to the navigation screen has been reduced in a comparison test with a conventional lane guidance method. It is confirmed that this lane guidance function is more intuitive than the conventional method.
2016-04-05
Technical Paper
2016-01-0110
Mohammad Huq, Douglas McConnell
Abstract Adaptive Cruise Control (ACC) runs with a set of parameters that determine how the ACC performs. Some of these parameters are tunable to some degree through HMI and the rest are pre-determined. The proposed Behavior Trainable ACC (BTACC) is able to learn all these parameters from driving behavior of the driver. To develop BTACC adapted to the driver’s driving behavior, the ACC keeps collecting driving data such as set speed, acceleration, deceleration, headway settings, etc., of the vehicle over time and keeps updating the related parameters. After training is over, the driver is able to drive the vehicle in BTACC mode, when the vehicle would drive itself according to driving behavior of the driver, young or elderly, and thus, provide the drivers with a higher level of safety and comfort. BTACC can be embedded with an existing ACC module so that the drivers may choose either ACC or BTACC.
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
2016-01-0114
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
2016-01-0118
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
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
2016-01-0141
Prasanna Vasudevan, Sreegururaj Jayachander
Abstract Several studies in the field of hedonics using subjective responses to gauge the nature and influence of odors have attempted to explain the complex psychological and chemical processes. Work on the effect of odors in alleviating driver fatigue is limited. The potential to improve road safety through non-pharmacological means such as stimulating odors is the impetus behind this paper. This is especially relevant in developing countries today with burgeoning economies such as India. Longer road trips by commercial transport vehicles with increasingly fatigued drivers and risk of accidents are being fuelled by distant producer - consumer connections. This work describes a two stage comparative study on the effects of different odors typically obtainable in India. The stages involve administration of odorants orthonsally and retronasally after the onset of circadian fatigue in test subjects. This is followed by a small cognitive exercise to evaluate hand-eye coordination.
2016-04-05
Technical Paper
2016-01-0135
Ji Zhang, Mengjing Shen, Xiangyu Zhu, Qipeng Chen
Abstract Nowadays researches of automotive electromagnetic field mainly focus on the component level and electromagnetic compatibility, while there is a lack of relevant studies on internal electromagnetic environment of the vehicles. With the increasingly complex internal electromagnetic environment of the vehicle, people are increasingly concerned about its potential impact of human health. This article researches on a type of electric vehicle and the occupants and analyses its electromagnetic radiation effects on human health. Firstly, considering the characters of Pro/E, Hypermesh and FEKO, the “Characteristics grouping subdivision” method is used to establish the entire vehicle body FE model. According to the requirement of MOM/FEM method, the entire vehicle model is optimized to be a high quality body model with simple construction and moderate grid size.
2016-04-05
Technical Paper
2016-01-0140
Yang Zheng, Navid Shokouhi, Nicolai Thomsen, Amardeep Sathyanarayana, John Hansen
Abstract The use of smart portable devices in vehicles creates the possibility to record useful data and helps develop a better understanding of driving behavior. In the past few years the UTDrive mobile App (a.k.a MobileUTDrive) has been developed with the goal of improving driver/passenger safety, while simultaneously maintaining the ability to establish monitoring techniques that can be used on mobile devices on various vehicles. In this study, we extend the ability of MobileUTDrive to understand the impact on driver performance on public roads in the presence of distraction from speech/voice based tasks versus tactile/hands-on tasks. Drivers are asked to interact with the device in both voice-based and hands-on modalities and their reaction time and comfort level are logged. To evaluate the driving patterns while handling the device by speech/hand, the signals from device inertial sensors are retrieved and used to construct Gaussian Mixture Models (GMM).
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
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
2016-01-0254
Gursaran D. Mathur
Field tests were conducted on a late full sized sedan with the HVAC unit operating in both Recirculation and OSA modes to monitor build-up of the CO2 concentration inside the cabin and its influence on occupant’s fatigue and alertness. These tests were conducted during 2015 summer on interstate highways with test durations ranging from 4 to 7 hours. During the above tests, fatigue or tiredness of the occupants (including CO2 levels) was monitored and recorded at 30 min intervals. Based on this investigation it is determined that the measured cabin concentration levels reaches ASHRAE (Standard 62-1999) specified magnitudes (greater than 700 ppm over ambient levels) with three occupants in the vehicle. Further, the occupants did show fatigue when the HVAC unit was operated in recirculation mode in excess of 5 hours. Further details have been presented in the paper.
2016-04-05
Technical Paper
2016-01-0246
Rupesh Sonu Kakade, Prashant Mer
Abstract Vehicle occupants, unlike building occupants, are exposed to continuously varying, non-uniform solar heat load. Automotive manufacturers use photovoltaic cells based solar sensor to measure intensity and direction of the direct-beam solar radiation. Use of the time of the day and the position - latitude and longitude - of a vehicle is also common to calculate direction of the direct-beam solar radiation. Two angles - azimuth and elevation - are used to completely define the direction of solar radiation with respect to the vehicle coordinate system. Although the use of solar sensor is common in today’s vehicles, the solar heat load on the occupants, because of their exposure to the direct-beam solar radiation remains the area of in-car subjective evaluation and tuning. Since the solar rays travel in parallel paths, application of the ray tracing method to determine solar insolation of the vehicle occupants is possible.
2016-04-05
Technical Paper
2016-01-0334
Lucas e Silva, Tennakoon Mudiyanselage Tennakoon, Mairon Marques, Ana M. Djuric
Abstract A collaborative robot or cobot is a robot that can safely and effectively interact with human workers while performing industrial tasks. The ability to work alongside humans has increased the importance of collaborative robots in the automation industry, as this unique feature is a much needed property among robots nowadays. Rethink Robotics has pioneered this unique discipline by building many robots including the Baxter Robot which is exclusive not only because it has collaborative properties, but because it has two arms working together, each with 7 Degrees Of Freedom. The main goal of this research is to validate the kinematic equations for the Baxter collaborative robot and develop a unified reconfigurable kinematic model for the Left and Right arms so that the calculations can be simplified.
2016-04-05
Technical Paper
2016-01-1518
Carolyn W. Roberts, Jacek Toczyski, Jack Cochran, Qi Zhang, Patrick Foltz, Bronislaw Gepner, Jason Kerrigan, Mark Clauser
Abstract Multiple laboratory dynamic test methods have been developed to evaluate vehicle crashworthiness in rollover crashes. However, dynamic test methods remove some of the characteristics of actual crashes in order to control testing variables. These simplifications to the test make it difficult to compare laboratory tests to crashes. One dynamic method for evaluating vehicle rollover crashworthiness is the Dynamic Rollover Test System (DRoTS), which simulates translational motion with a moving road surface and constrains the vehicle roll axis to a fixed plane within the laboratory. In this study, five DRoTS vehicle tests were performed and compared to a pair of unconstrained steering-induced rollover tests. The kinematic state of the unconstrained vehicles at the initiation of vehicle-to-ground contact was determined using instrumentation and touchdown parameters were matched in the DRoTS tests.
2016-04-05
Technical Paper
2016-01-1516
Takahiro Suzaki, Noritaka Takagi, Kosho Kawahara, Tsuyoshi Yasuki
Abstract Approximately 20% of traffic fatalities in United States 2012 were caused by rollover accidents. Mostly injured parts were head, chest, backbone and arms. In order to clarify the injury mechanism of rollover accidents, kinematics of six kinds of Anthropomorphic Test Devices (ATD) and Post Mortem Human Subjects (PMHS) in the rolling compartment, whose body size is 50th percentile male (AM50), were researched by Zhang et al.(2014) using rollover buck testing system. It was clarified from the research that flexibility of the backbone and thoracic vertebra affected to occupant’s kinematics. On the other hand, the kinematics research of body size except AM50 will be needed in order to decrease traffic fatalities. There were few reports about the researches of occupant kinematics using FE models of body sizes except AM50.
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
2016-01-1504
Monica Lynn Haumann Jones, Sheila Ebert-Hamilton, Matthew Reed
Abstract Law enforcement officers (LEO) make extensive use of vehicles to perform their jobs, often spending large portions of a shift behind the wheel. Few LEO vehicles are purpose-built; the vast majority are modified civilian vehicles. Data from the field indicate that LEO suffer from relatively high levels musculoskeletal injury that may be due in part to poor accommodation provided by their vehicles. LEO are also exposed to elevated crash injury risk, which may be exacerbated by a compromise in the performance of the occupant restraint systems due to body-borne equipment. A pilot study was conducted to demonstrate the application of three-dimensional anthropometric scanning and measurement technology to address critical concerns related to vehicle design. Detailed posture and belt fit data were gathered from five law enforcement officers as they sat in the patrol vehicles that they regularly used and in a mockup of a mid-sized vehicle.
2016-04-05
Technical Paper
2016-01-1506
David Poulard, Huipeng Chen, Matthew Panzer
Abstract Pedestrian finite element models (PFEM) are used to investigate and predict the injury outcomes from vehicle-pedestrian impact. As postmortem human surrogates (PMHS) differ in anthropometry across subjects, it is believed that the biofidelity of PFEM cannot be properly evaluated by comparing a generic anthropometry model against the specific PMHS test data. Global geometric personalization can scale the PFEM geometry to match the height and weight of a specific PMHS, while local geometric personalization via morphing can modify the PFEM geometry to match specific PMHS anatomy. The goal of the current study was to evaluate the benefit of morphed PFEM compared to globally-scaled and generic PFEM by comparing the kinematics against PMHS test results. The AM50 THUMS PFEM (v4.01) was used as a baseline for anthropometry, and personalized PFEM were created to the anthropometric specifications of two obese PMHS used in a previous pedestrian impact study using a mid-size sedan.
2016-04-05
Technical Paper
2016-01-1498
Hironori Wakana, Masuyoshi Yamada, Minoru Sakairi
Abstract The problem of high fatal accident rates due to drunk driving persists, and must be reduced. This paper reports on a prototype system mounted on a car mock-up and a prototype portable system that enables the checking of the drivers’ sobriety using a breath-alcohol sensor. The sensor unit consists of a water-vapor-sensor and three semiconductor gas sensors for ethanol, acetaldehyde, and hydrogen. One of the systems’ features is that they can detect water vapor from human-exhaled breath to prevent false detection with fake gases. Each gas concentration was calculated by applying an algorithm based on a differential evolution method. To quickly detect the water vapor in exhaled breath, we applied an AC voltage between the two electrodes of the breath-water-vapor sensor and used our alcohol-detection algorithm. The ethanol level was automatically calculated from the three gas sensors as soon as the water vapor was detected.
2016-04-05
Technical Paper
2016-01-1421
Sean Seaman, Li Hsieh, Richard Young
Abstract This study investigated driver glances while engaging in infotainment tasks in a stationary vehicle while surrogate driving: watching a driving video recorded from a driver’s viewpoint and projected on a large screen, performing a lane-tracking task, and performing the Tactile Detection Response Task (TDRT) to measure attentional effects of secondary tasks on event detection and response. Twenty-four participants were seated in a 2014 Toyota Corolla production vehicle with the navigation system option. They performed the lane-tracking task using the vehicle’s steering wheel, fitted with a laser pointer to indicate wheel movement on the driving video. Participants simultaneously performed the TDRT and a variety of infotainment tasks, including Manual and Mixed-Mode versions of Destination Entry and Cancel, Contact Dialing, Radio Tuning, Radio Preset selection, and other Manual tasks. Participants also completed the 0-and 1-Back pure auditory-vocal tasks.
2016-04-05
Technical Paper
2016-01-1419
Helen S. Loeb, Sam Chamberlain, Yi-Ching Lee
Abstract Motor vehicles crashes are the leading cause of injury and death of US teens. Driving simulators offer a way to safely expose drivers to specific events in a controlled and repeatable manner. They empower researchers by enabling them to compare different groups and driving behaviors and assess the cognitive and attention skills that are essential to safe driving. Classically, assessment of eye glances and gaze duration relies largely on time-consuming data reduction and video coding. In addition, the synchronization of eye tracker and simulator data is essential to a valid analysis of the eye glances patterns in relation to the driving scenario. To better understand and quantify eye glances in relation to a driving scene, Eyesync was developed as a synchronization bridge between an eye tracker and a driving simulator. It allows the real time synchronization and logging of eye tracking and simulator data. The design of the software is presented in this paper.
2016-04-05
Technical Paper
2016-01-1420
Shinichi Kojima, Shigeyoshi Hiratsuka, Nobuyuki Shiraki, Kazunori Higuchi, Toshihiko Tsukada, Keiichi Shimaoka, Kazuya Asaoka, Sho Masuda, Kazuhiko Nakashima
Abstract This study aims at the development of a projection pattern that is capable of shortening the time required by a driver to perceive a pedestrian at night when a vehicle’s high beams are utilized. Our approach is based on the spatio-temporal frequency characteristics of human vision. Visual contrast sensitivity is dependent on spatiotemporal frequency, and maximum contrast sensitivity frequency varies depending on environmental luminance. Conventionally, there are several applications that utilize the spatio-temporal frequency characteristics of human vision. For example, the National Television System Committee (NTSC) television format takes into consideration low-sensitivity visual characteristics. In contrast, our approach utilizes high-sensitivity visual characteristics based on the assumption that the higher contrast sensitivity of spatio-temporal frequencies will correlate more effectively with shorter perception times.
2016-04-05
Technical Paper
2016-01-1425
Thomas McWilliams, Daniel Brown, Bryan Reimer, Bruce Mehler, Jonathan Dobres
Abstract Advanced driver assistance systems (ADAS) are an increasingly common feature of modern vehicles. The influence of such systems on driver behavior, particularly in regards to the effects of intermittent warning systems, is sparsely studied to date. This paper examines dynamic changes in physiological and operational behavior during lane departure warnings (LDW) in two commercial automotive systems utilizing on-road data. Alerts from the systems, one using auditory and the other haptic LDWs, were monitored during highway driving conditions. LDW events were monitored during periods of single-task driving and dual-task driving. Dual-task periods consisted of the driver interacting with the vehicle’s factory infotainment system or a smartphone to perform secondary visual-manual (e.g., radio tuning, contact dialing, etc.) or auditory-vocal (e.g. destination address entry, contact dialing, etc.) tasks.
2016-04-05
Technical Paper
2016-01-1424
Yi G. Glaser, Robert E. Llaneras, Daniel S. Glaser, Charles A. Green
Abstract Partially automated driving involves the relinquishment of longitudinal and/or latitudinal control to the vehicle. Partially automated systems, however, are fallible and require driver oversight to avoid all road hazards. Researchers have expressed concern that automation promotes extended eyes-off-road (EOR) behavior that may lead to a loss of situational awareness (SA), degrading a driver’s ability to detect hazards and make necessary overrides. A potential countermeasure to visual inattention is the orientation of the driver’s glances towards potential hazards via cuing. This method is based on the assumption that drivers are able to rapidly identify hazards once their attention is drawn to the area of interest regardless of preceding EOR duration. This work examined this assumption in a simulated automated driving context by projecting hazardous and nonhazardous road scenes to a participant while sitting in a stationary vehicle.
2016-04-05
Technical Paper
2016-01-1422
Tarek Ouali, Nirav Shah, Bill Kim, David Fuente, Bo Gao
Abstract This paper introduces a new method for driving style identification based on vehicle communication signals. The purpose of this method is to classify a trip, driven in a vehicle, into three driving style categories: calm, normal or aggressive. The trip is classified based on the vehicle class, the type of road it was driven on (urban, rural or motorway) and different types of driving events (launch, accelerating and braking). A representative set of parameters, selected to take into consideration every part of the driver-vehicle interaction, is associated to each of these events. Due to the usage of communication signals, influence factors, other than vehicle speed and acceleration (e.g. steering angle or pedals position), can be considered to determine the level of aggressiveness on the trip. The conversion of the parameters from physical values to dimensionless score is based on conversion maps that consider the road and vehicle types.
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