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Viewing 1 to 30 of 271
2017-03-28
Technical Paper
2017-01-1443
Lu ZiLin, Gangfeng Tan, Yuxin Pang, YU TANG, Keyu Qian
Abstract The development of the vehicle quantity and the transportation system accompanies the rise of traffic accidents. Statistics shows that nearly 35-45% traffic accidents are due to drivers’ fatigue. If the driver’s fatigue status could be judged in advance and reminded accurately, the driving safety could be further improved. In this research, the blink frequency and eyes movement information are monitored and the statistical method was used to assess the status of the driving fatigue. The main tasks include locating the edge of the human eyes, obtaining the distance between the upper and lower eyelids for calculating the frequency of the driver's blink. The velocity and position of eyes movement are calculated by detecting the pupils’ movement. The normal eyes movement model is established and the corresponding database is updated constantly by monitoring the driver blink frequency and eyes movement during a certain period of time.
2017-03-28
Technical Paper
2017-01-1372
Bo Wang, Smruti Panigrahi, Mayur Narsude, Amit Mohanty
Abstract Increasing number of vehicles are equipped with telematics devices and are able to transmit vehicle CAN bus information remotely. This paper examines the possibility of identifying individual drivers from their driving signatures embedded in these telematics data. The vehicle telematics data used in this study were collected from a small fleet of 30 Ford Fiesta vehicles driven by 30 volunteer drivers over 15 days of real-world driving in London, UK. The collected CAN signals included vehicle speed, accelerator pedal position, brake pedal pressure, steering wheel angle, gear position, and engine RPM. These signals were collected at approximately 5Hz frequency and transmitted to the cloud for offline driver identification modeling. A list of driving metrics was developed to quantify driver behaviors, such as mean brake pedal pressure and longitudinal jerk. Random Forest (RF) was used to predict driver IDs based on the developed driving metrics.
2017-03-28
Technical Paper
2017-01-1394
Seung Nam Min, Murali Subramaniyam, Seunghee Hong, Damee Kim, Dong Joon Kim, Kyung-Sun Lee, Sun Ho Hur, Hyuk KIM, Se Jin Park
Abstract Drivers’ physical and physiological states change with prolonged driving. Driving for extended periods of time can lead to an increased risk of low back pain and other musculoskeletal disorders, caused by the discomfort of the seats. Static and dynamic are the two main categories must be considered within the seating development. The posture and orientation of the occupant are the important factors on static comfort. Driving posture measurement is essential for the evaluation of a driver workspace and improved seat comfort design. This study evaluated the comfortable driving posture through physiological and ergonomics measurements of an automotive premium driver seat. The physiological evaluation includes electroencephalographic (EEG) for brain waves, Biopac’s AcqKnowledge program, and subjective measurements on 32 healthy individuals. JACK simulation was used for the ergonomics evaluation, i.e., the magnitude of the spinal loads about lumbar vertebrae was estimated.
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.
2017-03-28
Technical Paper
2017-01-0432
Bing Zhu, Zhipeng Liu, Jian Zhao, Weiwen Deng
Abstract Adaptive cruise control system with lane change assistance (LCACC) is a novel advanced driver assistance system (ADAS), which enables dual-target tracking, safe lane change, and longitudinal ride comfort. To design the personalized LCACC system, one of the most important prerequisites is to identify the driver’s individualities. This paper presents a real-time driver behavior characteristics identification strategy for LCACC system. Firstly, a driver behavior data acquisition system was established based on the driver-in-the-loop simulator, and the behavior data of different types of drivers were collected under the typical test condition. Then, the driver behavior characteristics factor Ks we proposed, which combined the longitudinal and lateral control behaviors, was used to identify the driver behavior characteristics. And an individual safe inter-vehicle distances field (ISIDF) was established according to the identification results.
2017-03-28
Technical Paper
2017-01-0406
Jindong Ren, Xiaoming Du, Tao Liu, Honghao Liu, Meng Hua, Qun Liu
Abstract This paper presents an integrated method for rapid modeling, simulation and virtual evaluation of the interface pressure between driver human body and seat. For simulation of the body-seat interaction and for calculation of the interface pressure, besides body dimensions and material characteristics an important aspect is the posture and position of the driver body with respect to seat. In addition, to ensure accommodation of the results to the target population usually several individuals are simulated, whose body anthropometries cover the scope of the whole population. The multivariate distribution of the body anthropometry and the sampling techniques are usually adopted to generate the individuals and to predict the detailed body dimensions. In biomechanical modeling of human body and seat, the correct element type, the rational settings of the contacts between different parts, the correct exertion of the loads to the calculation field, etc., are also crucial.
2017-03-28
Technical Paper
2017-01-0407
Fei Huo, Huyao Wu
Abstract Biomechanics and biodynamics are increasingly focused on the automotive industry to provide comfortable driving environment, reduce driver fatigue, and improve passenger safety. Man-centered conception is a growing emphasis on the open design of automobile. During the long-term driving, occupational drivers are easily exposed to the neck pain, so it is important to reduce the muscle force load and its fatigue, which are not usually considered quantitatively during traditional ergonomics design, so standards related are not well developed to guide the vehicle design; On the other hand, the head-neck models are always built based on the statics theory, these are not sufficient to predict the instantaneous variation of the muscle force. In this paper, a head-neck model with multi DOFs is created based on multibody dynamics. Firstly, a driver-vehicle-road model considering driver multi-rigid body model, vehicle subsystems, and different ranks of pavement is built.
2017-03-28
Technical Paper
2017-01-1374
Michael J. Flannagan, Shan Bao, Anuj Pradhan, John Sullivan, Yu Zhang
Abstract Mcity at the University of Michigan in Ann Arbor provides a realistic off-roadway environment in which to test vehicles and drivers in complex traffic situations. It is intended for testing of various levels of vehicle automation, from advanced driver assistance systems (ADAS) to fully self-driving vehicles. In a recent human factors study of interfaces for teen drivers, we performed parallel experiments in a driving simulator and Mcity. We implemented driving scenarios of moderate complexity (e.g., passing a vehicle parked on the right side of the road just before a pedestrian crosswalk, with the parked vehicle partially blocking the view of the crosswalk) in both the simulator and at Mcity.
2017-03-28
Technical Paper
2017-01-1380
Richard Young
Abstract Dingus and colleagues recently estimated the crash odds ratios (ORs) for secondary tasks in the Strategic Highway Research Program Phase 2 (SHRP 2) naturalistic driving study. Their OR estimate for hand-held cell phone conversation (Talk) was 2.2, with a 95% confidence interval (CI) from 1.6 to 3.1. This Talk OR estimate is above 1, contrary to previous estimates below 1. A replication discovered two upward biases in their analysis methods. First, for video clips with exposure to a particular secondary task, Dingus and colleagues selected clips not only with exposure to that task, but often with concurrent exposure to other secondary tasks. However, for video clips without exposure to that task, Dingus and colleagues selected video clips without other secondary tasks. Hence, the OR estimate was elevated simply because of an imbalanced selection of video clips, not because of risk from a particular secondary task.
2017-03-28
Technical Paper
2017-01-1382
Michelle L. Reyes, Cheryl A. Roe, Ashley B. McDonald, Julia E. Friberg, Daniel V. McGehee
Abstract Advanced driver assistance systems (ADAS) show tremendous promise for increasing safety on our roadways. However, while these technologies are rapidly infiltrating the American passenger vehicle market, many consumers have little to no experience or knowledge of them prior to getting behind the wheel. The Technology Demonstration Study was conducted to evaluate how the ways in which drivers learn about ADAS affect their perceptions of the technologies. This paper investigates drivers’ knowledge of the purpose, function, and limitations of the advanced driver assistance technology of adaptive cruise control (ACC), along with ratings of perceived usefulness, apprehension, and effort required to learn to use ACC.
2017-03-28
Technical Paper
2017-01-1398
Yoshiyuki Hatakeyema
Abstract Since drowsy driving is a major cause of serious traffic accidents, there is a growing requirement for drowsiness prevention technologies. This study proposes a drowsy driving prediction method based on eye opening time. One issue of using eye opening time is predicting strong drowsiness before the driver actually feels sleepy. Because overlooking potential hazards is one of the causes of traffic accidents and is closely related to driver cognition and drowsiness, this study focuses on eye opening movements during driving. First, this report describes hypotheses concerning drowsiness and eye opening time based on the results of previous studies. It is assumed that the standard deviation of eye opening time (SDEOP) indicates driver drowsiness and the following two transitions are considered: increasing and decreasing SDEOP. To confirm the hypotheses, the relationship between drowsiness and SDEOP was investigated.
2017-03-28
Technical Paper
2017-01-1402
SeHwan Kim, Junmin Wang, Dennis Guenther, Gary Heydinger, Joshua Every, M. Kamel Salaani, Frank Barickman
Abstract The rapid development of driver assistance systems, such as lane-departure warning (LDW) and lane-keeping support (LKS), along with widely publicized reports of automated vehicle testing, have created the expectation for an increasing amount of vehicle automation in the near future. As these systems are being phased in, the coexistence of automated vehicles and human-driven vehicles on roadways will be inevitable and necessary. In order to develop automated vehicles that integrate well with those that are operated in traditional ways, an appropriate understanding of human driver behavior in normal traffic situations would be beneficial. Unlike many research studies that have focused on collision-avoidance maneuvering, this paper analyzes the behavior of human drivers in response to cut-in vehicles moving at similar speeds. Both automated and human-driven vehicles are likely to encounter this scenario in daily highway driving.
2017-03-28
Technical Paper
2017-01-1647
Se Jin Park, Murali Subramaniyam, Seunghee Hong, Damee Kim, Jaehak Yu
Abstract Driving is a complex activity with the continuously changing environment. Safe driving can be challenged by changes in drivers’ physical, emotional, and mental condition. Population in the developed world is aging, so the number of older drivers is increasing. Older drivers have relatively higher incidences of crashes precipitated by drivers’ medical emergencies when compared to another age group. On the elderly population, automakers are paying more attention to developing cars that can measure and monitor the drivers’ health status to protect them. In recent years, the automotive industry has been integrating health, wellness, and wellbeing technologies into cars with Internet of Things (IoT). A broad range of applications is possible for the IoT-based elderly smart healthcare monitoring systems.
2017-03-28
Journal Article
2017-01-1566
Willibald Brems, Nico Kruithof, Richard Uhlmann, Andreas Wagner, Werner Krantz, Jochen Wiedemann
Abstract In recent years, driving simulators have become a valuable tool in the automotive design and testing process. Yet, in the field of vehicle dynamics, most decisions are still based on test drives in real cars. One reason for this situation can be found in the fact that many driving simulators do not allow the driver to evaluate the handling qualities of a simulated vehicle. In a driving simulator, the motion cueing algorithm tries to represent the vehicle motion within the constrained motion envelope of the motion platform. By nature, this process leads to so called false cues where the motion of the platform is not in phase or moving in a different direction with respect to the vehicle motion. In a driving simulator with classical filter-based motion cueing, false cues make it considerably more difficult for the driver to rate vehicle dynamics.
2017-03-28
Journal Article
2017-01-1564
Minh-Tri Nguyen, Jürgen Pitz, Werner Krantz, Jens Neubeck, Jochen Wiedemann
Abstract In addition to the analysis of human driving behavior or the development of new advanced driver assistance systems, the high simulation quality of today’s driving simulators enables investigations of selected topics pertaining to driving dynamics. With high reproducibility and fast generation of vehicle variants the subjective evaluation process leads to a better system understanding in the early development stages. The transfer of the original on-road test run to the virtual reality of the driving simulator includes the full flexibility of the vehicle model, the maneuver and the test track, which allows new possibilities of investigation. With the opportunity of a realistic whole-vehicle simulation provided by the Stuttgart Driving Simulator new analysis of the human’s thresholds of perception are carried out.
2017-03-28
Journal Article
2017-01-0426
Chen Lv, Hong Wang, Bolin Zhao, Dongpu Cao, Wang Huaji, Junzhi Zhang, Yutong Li, Ye Yuan
Abstract The interactions between automatic controls, physics, and driver is an important step towards highly automated driving. This study investigates the dynamical interactions between human-selected driving modes, vehicle controller and physical plant parameters, to determine how to optimally adapt powertrain control to different human-like driving requirements. A cyber-physical system (CPS) based framework is proposed for co-design optimization of the physical plant parameters and controller variables for an electric powertrain, in view of vehicle’s dynamic performance, ride comfort, and energy efficiency under different driving modes. System structure, performance requirements and constraints, optimization goals and methodology are investigated. Intelligent powertrain control algorithms are synthesized for three driving modes, namely sport, eco, and normal modes, with appropriate protocol selections. The performance exploration methodology is presented.
2017-03-28
Journal Article
2017-01-1432
Tadasuke Katsuhara, Yoshiki Takahira, Shigeki Hayashi, Yuichi Kitagawa, Tsuyoshi Yasuki
Abstract This study used finite element (FE) simulations to analyze the injury mechanisms of driver spine fracture during frontal crashes in the World Endurance Championship (WEC) series and possible countermeasures are suggested to help reduce spine fracture risk. This FE model incorporated the Total Human Model for Safety (THUMS) scaled to a driver, a model of the detailed racecar cockpit and a model of the seat/restraint systems. A frontal impact deceleration pulse was applied to the cockpit model. In the simulation, the driver chest moved forward under the shoulder belt and the pelvis was restrained by the crotch belt and the leg hump. The simulation predicted spine fracture at T11 and T12. It was found that a combination of axial compression force and bending moment at the spine caused the fractures. The axial compression force and bending moment were generated by the shoulder belt down force as the driver’s chest moved forward.
2017-03-14
Journal Article
2016-01-9114
Hoon Lee, Delbert Tesar, Pradeepkumar Ashok
Abstract In order to design the in-wheel motor (IWM) for Electric Vehicles (EV), it is necessary to analyze the desired (expected) duty cycle at a higher performance level in order that the IWM becomes commercially relevant. The duty cycle may be representative of different segments of the customer base. Or, the individual customer may wish to have a set of IWMs that uniquely meet his/her measured “demand” cycle for a balance of drivability and efficiency. Questions then arise: How to measure the demand cycle of an individual? What 2 or 3 standard duty cycles should be offered as customer choices for their vehicle? Should the IWM represent multiple speed domains to enhance efficiency and drivability? Can the vehicle be updated rapidly 2 to 3 years after purchase? Etc. In this paper, we lay the groundwork to answer these types of customer questions for an EV with four independent IWMs.
2017-01-10
Technical Paper
2017-26-0252
Sahil Garg, Sujit Bhide, Shashank Gupta
Abstract Vehicle Ergonomics is one of the most vital factor to be considered in vehicle design and development, as the customer wants a comfortable and performance oriented vehicle. An uncomfortable driving posture can lead to painful driving experiences for longer hauls. The control pedals viz. Accelerator, Brake and clutch pedal (ABC Pedals), are the most frequently used parts in the vehicle, their proper positioning with respect to human anthropology is of prime importance, from driver comfort viewpoint. The methodology currently used for optimizing ergonomics with respect to the positioning of pedals in a vehicle included; measuring anthropometric angles manually with the help of H-Point Machine, subjective jury analysis and through software like RAMSIS, JACK, etc. Manual measurement doesn’t give the flexibility of iterations for optimization. The subjective analysis is based on insinuations thereby, cannot be standardized.
2017-01-10
Technical Paper
2017-26-0002
Sitikantha Padhy, Pradeep Agrawal, Yoginder Yadav
Abstract Most of the time in motor vehicle accidents, the driver of the vehicle (especially driver of the larger vehicle in case of collision involving multiple vehicles) is held responsible for rash and negligent driving. But in-depth study and statistics, points out several external or environmental factors playing crucial role in these unfortunate incidents. In some cases these factors directly influence an accident/crash and in some cases these factors influence the behavior pattern of the driver, which increases risk of unsafe practices. Based on the real time data collected by ADAC on the Gurgaon - Jaipur Stretch of NH-8 and others parts of India, some of the factors that directly or indirectly influences the drivers behaviour, are illustrated in this paper.
2017-01-10
Technical Paper
2017-26-0012
S Lakshmi Narayanan, Suresh Palraj, Madanagopal Mani, Shekhar Pathak
Abstract This paper makes an attempt to focus on a study to evaluate angle of vision and obstruction in a vehicle, it is an objective assessment through different percentiles of population. In a view of Safety and comfort of a driver, a good perception of environment in which his vehicle is operating will be a determining component. Driver visibility and hidden corner in vehicle is a major safety area for passengers and pedestrian. Driver eye vision is an important key factor to design vehicle windshield, rear window and A-Pillar/ B-Pillar, positioning of side view mirror and IRVM based on anthropometry data. This study focuses on method of capturing and measuring the i) Driver's Direct field of vision that the driver sees directly by moving his/her eyesii) Driver's Indirect field of vision in which driver views indirectly by using imaging devices Rear View mirror, Display cameras.iii) Driver's Angle of obstruction - by A pillar, B pillar.
2017-01-10
Technical Paper
2017-26-0081
Karthikeyan Nagarajan
Abstract The objective of this work is to develop a realistic driver model which helps in simulating drive related behavior of system vehicle and other vehicles in a traffic simulation environment. A driver model is said to be realistic only if it can learn and adapt to any variations in vehicle parameters and simulated road conditions. At the same time, the control action and the learning should represent human-like computation. In this paper, the proposed driver model consists of a Self-Learning Model Reference Fuzzy Longitudinal and Lateral controller. The model employs a set of fuzzy rules to realize a path-following lateral controller whereas the longitudinal control is governed by another set of fuzzy rules. The adaptive capabilities of the model are realized using supervisory fuzzy set and simple self-learning algorithm. This adaptive mechanism evaluates the current controller performance against the desired closed loop reference model.
2017-01-10
Technical Paper
2017-26-0153
Krishnaraj Chandrasekaran, Navaneetha Rao, Suresh Palraj, Chaitanya Kurella, Mohamed noohu Lebbai
Abstract Over the ages of automotive history, expectations of the customers increases vastly starting from driving comfort, better fuel economy and a safe vehicle. Requirement of good vehicle drivability from customers are increasing without any compromise of fuel economy and vehicle features. To enhance the product, it is a must for every OEM’s to have better drivability to fulfill the needs of the customer. This paper explains Objective Drivability Evaluation done on compact SUV vehicle and comparison with subjective drivability. Vehicle manufacturer usually evaluate drivability based on the subjective assessments of experienced test drivers with a sequence of certain maneuvers. In this study, we have used the objective drivability assessment tool AVL drive to obtain the vehicle drivability rating.
2017-01-10
Technical Paper
2017-26-0355
Lokesh Soni
Abstract With the increase in number of vehicles and amount of traffic, safety has come out to be a big concern in vehicle’s dynamic stability. There are certain system’s limits beyond which if a vehicle is pushed it may become unstable. One of the major areas of research in vehicle dynamics control has been lateral velocity and yaw rate control. With this, situations like vehicle spinning, oversteer, understeer etc. can be addressed. The challenge for the next generations of vehicle control is the integration of the available actuators into a unique holistic control concept. This paper presents the driver reference generator developed for the Integrated Vehicle Dynamics Control concept. The driver reference generator processes the driver inputs to determine the target vehicle behavior. The generation of reference behavior is a key factor for the integrated control design. The driver reference generation is validated on a real vehicle.
2016-10-25
Technical Paper
2016-36-0196
Francisco Ganzarolli, Samuel Lopes Souza, Jose Maria Campos Dos Santos
Abstract The purpose of the theme developed in this work is to increase the volume of information related to vehicle evaluation and how human perception can be translated into numbers, thus facilitating the process of definitions, refinement and analysis of its performance. Based on the discipline of psychophysics, where it is possible to study the relationship between stimulus and sensation and the use of post processing tool known as PSD (Power Spectral Density), post process the acceleration data of inputs perceived by the occupants of the vehicle, when driving in routes considered ergodic. By this, in a summarized way, get to human subjective perception of comfort. This material shows in a conceptual way a sequence of studies that were conducted to make it possible, to generate a performance classification of the subjective vehicle attribute of Smoothness, by processing values of acceleration measured the driver's seat.
2016-09-14
Technical Paper
2016-01-1870
Jun Ma, Maofei Xu, Yuchun Du
Abstract Gesture control has been increasingly applied to automotive industry to reduce the distraction caused by in-vehicle interactions to the primary task of driving. The aim of this study is to find out if gestures can reasonably be used to control in-car devices. Since there exists a big cultural difference of gesture between different countries because of its particularity, a set of gestures which support intuitive human-machine interaction in an automotive environment is searched. The results show a gesture dictionary for a variety of on-board functions, which conforms to Chinese drivers’ driving habits. Furthermore, this paper also describes a driving simulator test to evaluate the usability of gesture from different aspects including the effectiveness, efficiency, satisfaction, memorability and security. Static driving simulator is considered as an excellent environment for the in-car secondary task as its high safety level, repeatability and reliability.
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
2016-01-0140
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
2016-01-0111
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
2016-01-0080
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.
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