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2017-09-23
Technical Paper
2017-01-1982
Xiaoming Lan, Hui Chen, Xiaolin He, Jiachen Chen, Yosuke Nishimura, Kazuya Ando, Kei Kitahara
Abstract In the recent years, the interaction between human driver and Advanced Driver Assistance System (ADAS) has gradually aroused people’s concern. As a result, the concept of personalized ADAS is being put forward. As an important system of ADAS, Lane Keeping Assistance System (LKAS) also attracts great attention. To achieve personalized LKAS, driver lane keeping characteristic (DLKC) indices which could distinguish different driver lane keeping behavior should be researched. However, there are few researches on DLKC indices for personalized LKAS. Although there are many researches on modeling driver steering behavior, these researches are not sufficient to obtain DLKC indices. One reason is that most of researches are for double lane change behavior which is different from driver lane keeping behavior.
2017-09-23
Technical Paper
2017-01-1987
Renjie Li, Shengbo Li, Hongbo Gao, Keqiang Li, Bo Cheng, Deyi Li
Abstract Vehicle automation is a fundamental approach to reduce traffic accidents and driver workload. However, there is a notable risk of pushing human drivers out of the control loop before automation technology fully matures. Cooperative driving (or vehicle co-piloting) is a novel paradigm which is defined as the vehicle being jointly navigated by a human driver and an automatic controller through shared control technology. Indirect shared control is an emerging shared control method, which is able to realize cooperative driving through input complementation instead of haptic guidance. In this paper we first establish an indirect shared control method, in which the driver’s commanded input and the controller’s desired input are balanced with a weighted summation. Thereafter, we propose a predictive model to capture driver adaptation and trust in indirect shared control.
2017-09-23
Journal Article
2017-01-1983
Bing Zhu, Shude Yan, Jian Zhao, Weiwen Deng, Ning Bian
Abstract Electric power steering (EPS) system is a kind of dynamic control system for vehicle steering, which can amplify the driver steering torque inputs to the vehicle to improve steering comfortable and performance, but the present EPS can’t cater to the driving habits of different people. In this paper, a personalized EPS controller is designed based on the driver behavior, which combines real-time driver behavior identification strategy with personalized assistance characteristic. Firstly, the driver behavior data acquisition system is designed and established, based on which, the input data of different kinds of drivers along with vehicle signals are collected under typical working conditions, then the identification of driver behavior online is realized using the BP neural network.
2017-09-23
Technical Paper
2017-01-1984
Jun Ma, Junyi Li, Zaiyan Gong, Jihong Yu
Abstract Given the wide adoption of touchscreens in vehicles, an interesting debate is taking place regarding the good screen size, length-width ratio and whether the usability of in-vehicle information system (IVIS) would be decreased by a larger screen, especially. Moreover, the lack of scientific evidence about the concrete impact of touch screen size on usability raises questions to practitioners. In this paper, we investigated the impact of in-vehicle touch screen size on users’ visual behavior and usability as measured using eye tracker and questionnaire. Two experiments were conducted on 30 participants. In the first experiment, participants were asked to seek same information on four different in-vehicle screens based on simulated driving environment, while eye movement was recorded for analyzing efficiency of visual behavior.
2017-09-23
Technical Paper
2017-01-1993
Daoyuan Sun, Xiaofei Pei, Xu Hu, Hao Pan, Bo Yang
Abstract This paper presents a Driver-In-the-Loop (DIL) bench test system for development of ESC controller. The real-time platform is built-up based on NI/PXI system and the real steering/throttle/braking actuator. In addition, the CarSim provides the vehicle model and the animator for virtual driving environment. A hierarchical ESC controller is proposed in MATLAB/Simulink then download into PXI. In the upper motion controller, the sliding mode theory is adopted and the logic threshold algorithm is used in the lower slip controller. Finally, ESC test is implemented under typical conditions by DIL and Model-In-the-Loop (MIL). The results show that, DIL could make up the shortage of driver model which can’t accurately simulate the emergency response of real driver. Therefore, DIL test could verify the ESC controller more accurately and effectively with considering the human-vehicle-road environment.
2017-08-11
Journal Article
2017-01-9379
John Thomas, Shean Huff, Brian West, Paul Chambon
Abstract Aggressive driving is an important topic for many reasons, one of which is higher energy used per unit distance traveled, potentially accompanied by an elevated production of greenhouse gases and other pollutants. Examining a large data set of self-reported fuel economy (FE) values revealed that the dispersion of FE values is quite large and is larger for hybrid electric vehicles (HEVs) than for conventional gasoline vehicles. This occurred despite the fact that the city and highway FE ratings for HEVs are generally much closer in value than for conventional gasoline vehicles. A study was undertaken to better understand this and better quantify the effects of aggressive driving, including reviewing past aggressive driving studies, developing and exercising a new vehicle energy model, and conducting a related experimental investigation.
2017-07-10
Technical Paper
2017-28-1932
Ganesh Dharmar, Ravichandrika Bhamidipati, Satheesh Kumar
Abstract Traffic awareness of the driver is one of the prime focus in terms of pedestrian and road safety. Driver experience plays a significant role and driving requires careful attention to changing environments both within and outside the vehicle. Any lapse in driver attention from the primary task of driving could potentially lead to an accident. It is observed that, lack of attention on the ongoing traffic and ignorant about the traffic information such as traffic lights, road signs, traffic rules and regulations are major cause for the vehicle crash. Traffic signals & signage are the most appropriate choice of traffic control for the intersection, it is important to ensure that driver can see the information far away from the intersection so that he/she can stop safely upon viewing the yellow and red display. Then, upon viewing the signal operations and conditions the motorist can stop his/her vehicle successfully before entering the intersection.
2017-07-10
Technical Paper
2017-28-1960
Satish Chandra Mudavath, Ganesh Dharmar, Mohanraj Balakrishnan
Abstract In automotive industry, design of vehicle to end customer with proper ergonomics and balancing the design is always a challenge, for which an accurate prediction of postures are needed. Several studies have used Digital Human Models (DHM) to examine specific movements related to ingress and egress by translating complex tasks, like vehicle egress through DHMs. This requires an in-depth analysis of users to ensure such models reflect the range of abilities inherent to the population. Designers are increasingly using digital mock-ups of the built environment using DHMs as a means to reduce costs and speed-up the “time-to-market” of products. DHMs can help to improve the ergonomics of a product but must be representative of actual users.
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
2017-01-1372
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
2017-01-1374
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
2017-01-0061
Sultan A.M Alkhteeb, Shigeru Oho, Yuki Nagashima, Seisuke Nishimura, Hiroyuki Shimizu
Abstract Lightning strikes on automobiles are usually rare, though they can be fatal to occupants and hazardous to electronic control systems. Vehicles’ metal bodies are normally considered to be an effective shield against lightning. Modern body designs, however, often have wide window openings, and plastic body parts have become popular. Lightning can enter the cabin of vehicles through their radio antennas. In the near future, automobiles may be integrated into the electric power grid, which will cause issues related to the smart grid and the vehicle-to-grid concept. Even today, electric vehicles (EVs) and plug-in hybrid vehicles (PHEVs) are charged at home or in parking lots. Such automobiles are no longer isolated from the power grid and thus are subject to electric surges caused by lightning strikes on the power grid.
2017-03-28
Technical Paper
2017-01-0168
B. Vasanth, Muthukumar Arunachalam, Sathya Narayana, S. Sathish Kumar, Murali govindarajalu
In current scenario, there is an increasing need to have faster product development and achieve the optimum design quickly. In an automobile air conditioning system, the main function of HVAC third row floor duct is to get the sufficient airflow from the rear heating ventilating and air-conditioning (HVAC) system and to provide the sufficient airflow within the leg locations of passenger. Apart from airflow and temperature, fatigue strength of the duct is one of the important factors that need to be considered while designing and optimizing the duct. The challenging task is to package the duct below the carpet within the constrained space and the duct should withstand the load applied by the passenger leg and the luggage. Finite element analysis (FEA) has been used extensively to validate the stress and deformation of the duct under different loading conditions applied over the duct system.
2017-03-28
Technical Paper
2017-01-0163
Gursaran D. Mathur
The author has developed a model that can be used to predict build-up of cabin carbon dioxide levels for automobiles based on many variables. There are a number of parameters including number of occupants that dictates generation of CO2 within the control volume, cabin leakage (infiltration or exfiltration) characteristics, cabin volume, blower position or airflow rate; vehicle age, etc. Details of the analysis is presented in the paper. Finally, the developed model has been validated with experimental data. The simulated data follows the same trend and matches fairly well with the experimental data.
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
2017-01-0409
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
2017-01-0407
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
2017-01-1647
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
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
2017-01-1394
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
2017-01-1442
Dawei Luo, Jianbo Lu, Gang Guo
Abstract This paper proposes a low-cost but indirect method for occupancy detection and occupant counting purpose in current and future automotive systems. It can serve as either a way to determine the number of occupants riding inside a car or a way to complement the other devices in determining the occupancy. The proposed method is useful for various mobility applications including car rental, fleet management, taxi, car sharing, occupancy in autonomous vehicles, etc. It utilizes existing on-board motion sensor measurements, such as those used in the vehicle stability control function, together with door open and closed status. The vehicle’s motion signature in response to an occupant’s boarding and alighting is first extracted from the motion sensors that measure the responses of the vehicle body. Then the weights of the occupants are estimated by fitting the vehicle responses with a transient vehicle dynamics model.
2017-03-28
Technical Paper
2017-01-1440
Shixing Chen, Ming Dong, Jerry Le, Mike Rao
Abstract Vehicle safety systems may use occupant physiological information, e.g., occupant heights and weights to further enhance occupant safety. Determining occupant physiological information in a vehicle, however, is a challenging problem due to variations in pose, lighting conditions and background complexity. In this paper, a novel occupant height estimation approach is presented. Depth information from a depth camera, e.g., Microsoft Kinect is used. In this 3D approach, first, human body and frontal face views (restricted by the Pitch and Roll values in the pose estimation) based on RGB and depth information are detected. Next, the eye location (2D coordinates) is detected from frontal facial views by Haar-cascade detectors. The eye-location co-ordinates are then transferred into vehicle co-ordinates, and seated occupant eye height is estimated according to similar triangles and fields of view of Kinect.
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
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.
2017-03-28
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.
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