Display:

Results

Viewing 61 to 90 of 16460
2017-03-28
Technical Paper
2017-01-1660
Huaxin Li, Di Ma, Brahim Medjahed, Qianyi Wang, Yu Seung Kim, Pramita Mitra
Abstract Nowadays, the automotive industry is experiencing the advent of unprecedented applications with connected devices, such as identifying safe users for insurance companies or assessing vehicle health. To enable such applications, driving behavior data are collected from vehicles and provided to third parties (e.g., insurance firms, car sharing businesses, healthcare providers). In the new wave of IoT (Internet of Things), driving statistics and users’ data generated from wearable devices can be exploited to better assess driving behaviors and construct driver models. We propose a framework for securely collecting data from multiple sources (e.g., vehicles and brought-in devices) and integrating them in the cloud to enable next-generation services with guaranteed user privacy protection.
2017-03-28
Technical Paper
2017-01-1659
Mert D. Pesé, Karsten Schmidt, Harald Zweck
Abstract The automotive industry experiences a major change as vehicles are gradually becoming a part of the Internet. Security concepts based on the closed-world assumption cannot be deployed anymore due to a constantly changing adversary model. Automotive Ethernet as future in-vehicle network and a new E/E Architecture have different security requirements than Ethernet known from traditional IT and legacy systems. In order to achieve a high level of security, a new multi-layer approach in the vehicle which responds to special automotive requirements has to be introduced. One essential layer of this holistic security concept is to restrict non-authorized access by the deployment of embedded firewalls. This paper addresses the introduction of automotive firewalls into the next-generation domain architecture with a focus on partitioning of its features in hardware and software.
2017-03-28
Technical Paper
2017-01-1572
Wesley Kerstens
Abstract The detection and diagnosis of sensor faults in real-time is necessary for satisfactory performance of vehicle Electronic Stability Control (ESC) and Roll Stability Control (RSC) systems. This paper presents an observer designed to detect faults of a roll rate sensor that is robust to model uncertainties and disturbances. A reference vehicle roll angle estimate, independent of roll-rate sensor measurement, is formed from available ESC inertial sensor measurements. Residuals are generated by comparing the reference roll angle and roll rate, with the observer outputs. Stopping rules based on the current state of the vehicle and the magnitude of the residuals are then used to determine if a sensor fault is present. The system’s low order allows for efficient implementation in real-time on a fixed-point microprocessor. Modification of the roll rate sensor signal during in vehicle experiments shows the algorithm’s ability to detect faults.
2017-03-28
Technical Paper
2017-01-1555
Mirosław Jan Gidlewski, Krystof JANKOWSKI, Andrzej MUSZYŃSKI, Dariusz ŻARDECKI
Abstract Lane change automation appears to be a fundamental problem of vehicle automated control, especially when the vehicle is driven at high speed. Selected relevant parts of the recent research project are reported in this paper, including literature review, the developed models and control systems, as well as crucial simulation results. In the project, two original models describing the dynamics of the controlled motion of the vehicle were used, verified during the road tests and in the laboratory environment. The first model - fully developed (multi-body, 3D, nonlinear) - was used in simulations as a virtual plant to be controlled. The second model - a simplified reference model of the lateral dynamics of the vehicle (single-body, 2D, linearized) - formed the basis for theoretical analysis, including the synthesis of the algorithm for automatic control. That algorithm was based on the optimal control theory.
2017-03-28
Technical Paper
2017-01-1384
Richard Young
Abstract This proof-of-concept demonstrates a new method to predict the relative crash risk in naturalistic driving that is caused (or prevented) by the effects on attention of visual-manual secondary tasks performed while driving in a track experiment. The method required five steps. (1) Estimate valid relative crash/near-crash risks of visual-manual secondary tasks measured during naturalistic driving. These data were taken from a prior SAE publication of unbiased estimates of the relative crash/near-crash risks of secondary tasks in the 100-Car naturalistic driving study. (2) Calculate the “physical demand” and “cognitive demand” scores for visual-manual secondary tasks performed while driving on a track.
2017-03-28
Technical Paper
2017-01-1381
Satheesh Kumar Chandran, James Forbes, Carrie Bittick, Shimul Bhuva
Abstract There is a strong business case for automotive companies to improve by understanding what consumers want, like and dislike. Various aspects of ergonomics such as reach, visibility, usability, feel are dependent on measuring consumer’s ability, opinions and satisfaction. Rating scales (such as adjective, continuous, logarithmic, etc.) are used to measure these complex attitudes. It is essential the correct rating scale and appropriate analysis methods are used to capture these attitudes. Previous psychology research has been conducted on the performance of different rating scales. This ratings scale research focused on scales and their reliability and validity for various applications. This paper will summarize past research, discuss the use of rating scales specific to vehicle ergonomics, and analyze the results of an automotive interface study that correlates the seven-point adjective rating scale to the system usability score (SUS).
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
2017-01-1387
Jing Zhang
Abstract Existing automotive infotainment and telematics systems are increasingly feature-rich; they are simultaneously more densely packed with information and more complicated in terms of human-machine interactions. This complexity negatively impacts the situational awareness (SA) of the driver, and contributes to driver distraction. With the proliferation of tablets and smart phones, automotive mobile applications are growing in popularity; however, their content has been confined to a limited subset of vehicle information and control functions. Phone projection systems such as Apple CarPlay™ allow in-vehicle consumption of phone-based media but offer no improvement for the rest of connected vehicle features. The author proposes a content strategy to significantly reduce in-vehicle system complexity and elevate driver SA.
2017-03-28
Technical Paper
2017-01-1386
Yu Zhang, Linda Angell, Silviu Pala, Tetsuya Hara, Doua Vang
Abstract The popularity of new Human-Machine-Interfaces (HMIs) comes with growing concerns for driver distraction. In part, this concern stems from a rising challenge to design systems that can make functions accessible to drivers while maintaining drivers’ ability to cope with the complex driving task. Therefore, engineers need assessment methods which can evaluate how well a user interface achieves the dual-goal of making secondary tasks accessible, while allowing safe driving. Most prior methods have emphasized measuring off-road glances during HMI use. An alternative to this is to consider both on-road and off-road glances, as done in Kircher and Ahlstrom’s AttenD algorithm [1]. In this study, we compared two types of prevalent visual-manual user interfaces based on AttenD. The two HMIs of interest were a touchscreen-based interface (already in production) and a remote-rotary-controller-based interface (a high-fidelity prototype).
2017-03-28
Technical Paper
2017-01-1385
Satheesh Kumar Chandran, James Forbes, Carrie Bittick, Kathleen Allanson, Santosh Erupaka, Fnu Brinda
Abstract Measurement of usability with the System Usability Scale (SUS) is successfully applied to products in many industries. The benefit of any measurement scale, however, is limited by the repeatability of the associated testing process. For SUS, these factors can include sample size, study protocol, previous experience, and pre study exposure to the system being tested. Differences in user exposure can influence the usability assessment of interfaces which could affect the validity of SUS scores.
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
2017-01-1378
Gianna F. Gomez-Levi, Ksenia Kozak, Nanxin Wang, Jian Wan, Linas Mikulionis
Abstract Researchers report an estimated 35.7 million of vehicles with touchscreens will be sold in 2019 worldwide [1]. As the use of touchscreens grows in the automotive industry, there is a need to study how driver’s arm and hand moves to access the touchscreen as well as how the driver utilizes the hardware around the touchscreen. In order to aid drivers while using the touchscreen and to minimize distractions, the drivers’ hand must be able to freely move to perform a task on the touchscreen without the trim interfering with the task. At the same time some trim may be used to support the hand and fingers while accessing the touchscreen particularly during tasks that take a longer period of time to complete. A study was performed to understand the effect of the size and the angle of a shelf placed under a touchscreen. Motion capture (Mocap) data of the hand of subjects performing two different tasks on the touchscreen was collected in the Human Occupant Package Simulator (HOPS).
2017-03-28
Technical Paper
2017-01-1375
Louis Tijerina, Danielle Warren, Sang-Hwan Kim, Francine Dolins
Abstract This study investigated the effects of three navigation system human-machine interfaces (HMIs) on driver eye-glance behavior, navigational errors, and subjective assessments. Thirty-six drivers drove an unfamiliar 3-segment route in downtown Detroit. HMIs were 2D or 3D (level-of-detail) electronic map display + standard voice prompts, or 3D map-display augmented by photorealistic images + landmark-enhanced voice prompts. Participants drove the same three route segments in order but were assigned a different HMI condition/segment in a 3-period/3-treatment crossover experimental design. Results indicate that drivers’ visual attention using the advanced navigation systems HMIs were within US Department of Transportation recommended visual distraction limits. More turns missed in the first route segment, regardless of HMI, were attributable to greater route complexity and a late-onset voice prompt.
2017-03-28
Technical Paper
2017-01-1376
David H. Weir, Kevin Chao, R. Michael Van Auken
Abstract A class of driver attentional workload metrics has been developed for possible application to the measuring and monitoring of attentional workload and level of distraction in actual driving, as well as in the evaluation and comparison of in-vehicle human machine interface (HMI or DVI) devices. The metrics include driver/vehicle response and performance measures, driver control activity, and driver control models and parameters. They are the result of a multidisciplinary, experimental and analytical effort, applying control theory, manual control, and human factors principles and practices. Driving simulator and over-the-road experiments were used to develop, confirm, and demonstrate the use of the metrics in distracted driving situations. The visual-manual secondary tasks used in the study included navigation destination entry, radio tuning, critical tracking task, and a generic touch screen entry task.
2017-03-28
Journal Article
2017-01-0555
Salvatore Iaccarino, Sebastiano Breda, Alessandro D'Adamo, Stefano Fontanesi, Adrian Irimescu, Simona Merola
Abstract The increasing limitations in engine emissions and fuel consumption have led researchers to the need to accurately predict combustion and related events in gasoline engines. In particular, knock is one of the most limiting factors for modern SI units, severely hindering thermal efficiency improvements. Modern CFD simulations are becoming an affordable instrument to support experimental practice from the early design to the detailed calibration stage. To this aim, combustion and knock models in RANS formalism provide good time-to-solution trade-off allowing to simulate mean flame front propagation and flame brush geometry, as well as “ensemble average” knock tendency in end-gases. Still, the level of confidence in the use of CFD tools strongly relies on the possibility to validate models and methodologies against experimental measurements.
2017-03-28
Journal Article
2017-01-0551
Alessandro D'Adamo, Sebastiano Breda, Salvatore Iaccarino, Fabio Berni, Stefano Fontanesi, Barbara Zardin, Massimo Borghi, Adrian Irimescu, Simona Merola
Abstract Engine knock is one of the most limiting factors for modern Spark-Ignition (SI) engines to achieve high efficiency targets. The stochastic nature of knock in SI units hinders the predictive capability of RANS knock models, which are based on ensemble averaged quantities. To this aim, a knock model grounded in statistics was recently developed in the RANS formalism. The model is able to infer a presumed log-normal distribution of knocking cycles from a single RANS simulation by means of transport equations for variances and turbulence-derived probability density functions (PDFs) for physical quantities. As a main advantage, the model is able to estimate the earliest knock severity experienced when moving the operating condition into the knocking regime.
2017-03-28
Technical Paper
2017-01-0573
Mohammed Jaasim Mubarak ali, Francisco Hernandez Perez, R Vallinayagam, S Vedharaj, Bengt Johansson, Hong Im
Abstract Full cycle simulations of KAUST optical diesel engine were conducted in order to provide insights into the details of fuel spray, mixing, and combustion characteristics at different start of injection (SOI) conditions. Although optical diagnostics provide valuable information, the high fidelity simulations with matched parametric conditions improve fundamental understanding of relevant physical and chemical processes by accessing additional observables such as the local mixture distribution, intermediate species concentrations, and detailed chemical reaction rates. Commercial software, CONVERGE™, was used as the main simulation tool, with the Reynolds averaged Navier-Stokes (RANS) turbulence model and the multi-zone (SAGE) combustion model to compute the chemical reaction terms. SOI is varied from late compression ignition (CI) to early partially premixed combustion (PPC) conditions.
2017-03-28
Technical Paper
2017-01-0066
Shogo Nakao, Akihiko Hyodo, Masaki Itabashi, Tomio Sakashita, Shingo Obara, Tetsuya Uno, Yasuo Sugure, Yoshinobu Fukano, Mitsuo Sasaki, Yoshihiro Miyazaki
This paper presents the “Virtual Failure Mode and Effects Analysis (vFMEA)” system, which is a high-fidelity electrical-failure-simulation platform, and applies it to the software verification of an electric power steering (EPS) system. The vFMEA system enables engineers to dynamically inject a drift fault into a circuit model of the electronic control unit (ECU) of an EPS system, to analyze system-level failure effects, and to verify software-implemented safety mechanisms, which consequently reduces both cost and time of development. The vFMEA system can verify test cases that cannot be verified using an actual ECU and can improve test coverage as well. It consists of a cycle-accurate microcontroller model with mass-production software implemented in binary format, analog and digital circuit models, mechanical models, and a state-triggered fault-injection mechanism.
2017-03-28
Technical Paper
2017-01-0065
Bülent Sari, Hans-Christian Reuss
Abstract Safety is becoming more and more important with the ever increasing level of safety related E/E Systems built into the cars. Increasing functionality of vehicle systems through electrification of power train and autonomous driving leads to complexity in designing system, hardware, software and safety architecture. The application of multicore processors in the automotive industry is becoming necessary because of the needs for more processing power, more memory and higher safety requirements. Therefore it is necessary to investigate the safety solutions particularly for Automotive Safety Integrity Level (ASIL-D) Systems. This brings additional challenges because of additional requirements of ISO 26262 for ASIL-D safety concepts. This paper presents an approach for model-based “dependent failure analysis” which is required from ISO 26262 for ASIL-D safety concepts with decomposition approach.
2017-03-28
Technical Paper
2017-01-0068
Pablo Sauras-Perez, Andrea Gil, Jasprit Singh Gill, Pierluigi Pisu, Joachim Taiber
Abstract In the next 20 years fully autonomous vehicles are expected to be in the market. The advance on their development is creating paradigm shifts on different automotive related research areas. Vehicle interiors design and human vehicle interaction are evolving to enable interaction flexibility inside the cars. However, most of today’s vehicle manufacturers’ autonomous car concepts maintain the steering wheel as a control element. While this approach allows the driver to take over the vehicle route if needed, it causes a constraint in the previously mentioned interaction flexibility. Other approaches, such as the one proposed by Google, enable interaction flexibility by removing the steering wheel and accelerator and brake pedals. However, this prevents the users to take control over the vehicle route if needed, not allowing them to make on-route spontaneous decisions, such as stopping at a specific point of interest.
2017-03-28
Technical Paper
2017-01-0067
Wei Han, Xinyu Zhang, Jialun Yin, Yutong Li, Deyi Li
Abstract Safety of buses is crucial because of the large proportion of the public transportation sector they constitute. To improve bus safety levels, especially to avoid driver error, which is a key factor in traffic accidents, we designed and implemented an intelligent bus called iBus. A robust system architecture is crucial to iBus. Thus, in this paper, a novel self-driving system architecture with improved robustness, such as to failure of hardware (including sensors and controllers), is proposed. Unlike other self-driving vehicles that operate either in manual driving mode or in self-driving mode, iBus offers a dual-control mode. More specifically, an online hot standby mechanism is incorporated to enhance the reliability of the control system, and a software monitor is implemented to ensure that all software modules function appropriately. The results of real-world road tests conducted to validate the feasibility of the overall system confirm that iBus is reliable and robust.
2017-03-28
Technical Paper
2017-01-0070
Longxiang Guo, Sagar Manglani, Xuehao Li, Yunyi Jia
Abstract Autonomous driving technologies can provide better safety, comfort and efficiency for future transportation systems. Most research in this area has mainly been focused on developing sensing and control approaches to achieve various autonomous driving functions. Very little of this research, however, has studied how to efficiently handle sensing exceptions. A simple exception measured by any of the sensors may lead to failures in autonomous driving functions. The autonomous vehicles are then supposed to be sent back to manufacturers for repair, which takes both time and money. This paper introduces an efficient approach to make human drivers able to online teach autonomous vehicles to drive under sensing exceptions. A human-vehicle teaching-and-learning framework for autonomous driving is proposed and the human teaching and vehicle learning processes for handling sensing exceptions in autonomous vehicles are designed in detail.
2017-03-28
Technical Paper
2017-01-0069
Venkatesh Raman, Mayur Narsude, Damodharan Padmanaban
Abstract This manuscript compares window-based data imputation approaches for data coming from connected vehicles during actual driving scenarios and obtained using on-board data acquisition devices. Three distinct window-based approaches were used for cleansing and imputing the missing values in different CAN-bus (Controller Area Network) signals. Lengths of windows used for data imputation for the three approaches were: 1) entire time-course for each vehicle ID, 2) day, and 3) trip (defined as duration between vehicle's ignition statuses ON to OFF). An algorithm for identification of ignition ON and OFF events is also presented, since this signal was not explicitly captured during the data acquisition phase. As a case study, these imputation techniques were applied to the data from a driver behavior classification experiment.
2017-03-28
Technical Paper
2017-01-0053
Wolfgang Granig, Friedrich Rasbornig, Dirk Hammerschmidt, Mario Motz, Thomas Zettler, Michael Strasser, Alessandro Michelutti
Abstract Functional safe systems fulfilling the ISO 26262 standard are getting more important for automotive applications where additional redundant and diverse functionality is needed for higher rated ASIL levels. This can result in a very complex and expensive system setup. Here we present a sensor product developed according ISO 26262. This sensor product comprises a two channel redundant and also diverse implemented magnetic field sensor concept with linear digital outputs on one monolithically integrated silicon substrate. This sensor is used for ASIL D applications like power-steering torque measurement, where the torque is transferred into a magnetic field signal in a certain magnetic setup, but can also be used in other demanding sensor applications concerning safety. This proposed and also implemented solution is beneficial because of implementation on a single chip in one single chip-package but anyway fulfilling ASIL D requirements on system level.
2017-03-28
Journal Article
2017-01-0052
Andre Kohn, Rolf Schneider, Antonio Vilela, Udo Dannebaum, Andreas Herkersdorf
Abstract A main challenge when developing next generation architectures for automated driving ECUs is to guarantee reliable functionality. Today’s fail safe systems will not be able to handle electronic failures due to the missing “mechanical” fallback or the intervening driver. This means, fail operational based on redundancy is an essential part for improving the functional safety, especially in safety-related braking and steering systems. The 2-out-of-2 Diagnostic Fail Safe (2oo2DFS) system is a promising approach to realize redundancy with manageable costs. In this contribution, we evaluate the reliability of this concept for a symmetric and an asymmetric Electronic Power Steering (EPS) ECU. For this, we use a Markov chain model as a typical method for analyzing the reliability and Mean Time To Failure (MTTF) in majority redundancy approaches. As a basis, the failure rates of the used components and the microcontroller are considered.
2017-03-28
Technical Paper
2017-01-0056
Naveen Mohan, Martin Törngren, Sagar Behere
Abstract With the advent of ISO 26262 there is an increased emphasis on top-down design in the automotive industry. While the standard delivers a best practice framework and a reference safety lifecycle, it lacks detailed requirements for its various constituent phases. The lack of guidance becomes especially evident for the reuse of legacy components and subsystems, the most common scenario in the cost-sensitive automotive domain, leaving vehicle architects and safety engineers to rely on experience without methodological support for their decisions. This poses particular challenges in the industry which is currently undergoing many significant changes due to new features like connectivity, servitization, electrification and automation. In this paper we focus on automated driving where multiple subsystems, both new and legacy, need to coordinate to realize a safety-critical function.
2017-03-28
Technical Paper
2017-01-0054
Daniel Kaestner, Antoine Miné, André Schmidt, Heinz Hille, Laurent Mauborgne, Stephan Wilhelm, Xavier Rival, Jérôme Feret, Patrick Cousot, Christian Ferdinand
Abstract Safety-critical embedded software has to satisfy stringent quality requirements. All contemporary safety standards require evidence that no data races and no critical run-time errors occur, such as invalid pointer accesses, buffer overflows, or arithmetic overflows. Such errors can cause software crashes, invalidate separation mechanisms in mixed-criticality software, and are a frequent cause of errors in concurrent and multi-core applications. The static analyzer Astrée has been extended to soundly and automatically analyze concurrent software. This novel extension employs a scalable abstraction which covers all possible thread interleavings, and reports all potential run-time errors, data races, deadlocks, and lock/unlock problems. When the analyzer does not report any alarm, the program is proven free from those classes of errors. Dedicated support for ARINC 653 and OSEK/AUTOSAR enables a fully automatic OS-aware analysis.
2017-03-28
Technical Paper
2017-01-0059
Barbaros Serter, Christian Beul, Manuela Lang, Wiebke Schmidt
Abstract Today, highly automated driving is paving the road for full autonomy. Highly automated vehicles can monitor the environment and make decisions more accurately and faster than humans to create safer driving conditions while ultimately achieving full automation to relieve the driver completely from participating in driving. As much as this transition from advanced driving assistance systems to fully automated driving will create frontiers for re-designing the in-vehicle experience for customers, it will continue to pose significant challenges for the industry as it did in the past and does so today. As we transfer more responsibility, functionality and control from human to machine, technologies become more complex, less transparent and making constant safe-guarding a challenge. With automation, potential misuse and insufficient system safety design are important factors that can cause fatal accidents, such as in TESLA autopilot incident.
2017-03-28
Technical Paper
2017-01-0058
Dajiang Suo, Sarra Yako, Mathew Boesch, Kyle Post
Abstract Developing requirements for automotive electric/electronic systems is challenging, as those systems become increasingly software-intensive. Designs must account for unintended interactions among software features, combined with unforeseen environmental factors. In addition, engineers have to iteratively make architectural tradeoffs and assign responsibilities to each component in the system to accommodate new safety requirements as they are revealed. ISO 26262 is an industry standard for the functional safety of automotive electric/electronic systems. It specifies various processes and procedures for ensuring functional safety, but does not limit the methods that can be used for hazard and safety analysis. System Theoretic Process Analysis (STPA) is a new technique for hazard analysis, in the sense that hazards are caused by unsafe interactions between components (including humans) as well as component failures and faults.
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.
Viewing 61 to 90 of 16460