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Viewing 91 to 120 of 16442
2017-03-28
Technical Paper
2017-01-0041
Shengguang Xiong, Gangfeng Tan, Xuexun Guo, Longjie Xiao
Abstract Automotive Front Lighting System(AFS) can receive the steering signal and the vehicular speed signal to adjust the position of headlamps automatically. AFS will provide drivers more information of front road to protect drivers safe when driving at night. AFS works when there is a steering signal input. However, drivers often need the front road's information before they turn the steering wheel when vehicles are going to go through a sharp corner, AFS will not work in such a situation. This paper studied how to optimize the working time of AFS based on GIS (Geographic Information System) and GPS(Geographic Information System) to solve the problem. This paper analyzed the process of the vehicle is about to go through a corner. Low beams and high beams were discussed respectively.
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
2017-01-0056
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
2017-01-0050
Mario Berk, Hans-Martin Kroll, Olaf Schubert, Boris Buschardt, Daniel Straub
Abstract With increasing levels of driving automation, the perception provided by automotive environment sensors becomes highly safety relevant. A correct assessment of the sensors’ perception reliability is therefore crucial for ensuring the safety of the automated driving functionalities. There are currently no standardized procedures or guidelines for demonstrating the perception reliability of the sensors. Engineers therefore face the challenge of setting up test procedures and plan test drive efforts. Null Hypothesis Significance Testing has been employed previously to answer this question. In this contribution, we present an alternative method based on Bayesian parameter inference, which is easy to implement and whose interpretation is more intuitive for engineers without a profound statistical education. We show how to account for different environmental conditions with an influence on sensor performance and for statistical dependence among perception errors.
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
2017-01-0069
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
2017-01-0070
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
2017-01-0067
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
2017-01-0066
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
2017-01-0061
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
2017-01-0078
Alexander Katriniok, Peter Kleibaum, Christian Ress, Lutz Eckstein
Abstract Today, automated vehicles mostly rely on ego vehicle sensors such as cameras, radar or LiDAR sensors that are limited in their sensing capability and range. Vehicle-to-everything (V2X) communication has the potential to appropriately complement these sensors and even allow for a cooperative, proactive interaction of vehicles. As such, V2X communication might play a vital role on the way to smart and efficient traffic solutions. In the public funded research project UK Autodrive, we are currently investigating and experimentally evaluating V2X-based applications based on dedicated short range communication (DSRC). Moreover, the novel application intersection priority management (IPM) is part of the research project. IPM aims at automating intersections in such a way that vehicles can pass safely and even more efficiently without the use of traffic lights or signs.
2017-03-28
Technical Paper
2017-01-0076
Modar Horani, Ghaith Al-Refai, Osamah Rawashdeh
Abstract Current implementations of vision-based Advanced Driver Assistance Systems (ADAS) are largely dependent on real-time vehicle camera data along with other sensory data available on-board such as radar, ultrasonic, and GPS data. This data, when accurately reported and processed, helps the vehicle avoid collisions using established ADAS applications such as Forward Collision Avoidance (FCA), Autonomous Cruise Control (ACC), Pedestrian Detection, etc. Vehicle to Vehicle (V2V) and Vehicle to Infrastructure (V2I) over Dedicated Short Range Communication (DSRC) provides basic sensory data from other vehicles or roadside infrastructure including position information of surrounding traffic. Exchanging rich data such as vision data between multiple vehicles, and between vehicles and infrastructure provides a unique opportunity to advance driver assistance applications and Intelligent Transportation Systems (ITS).
2017-03-28
Technical Paper
2017-01-0081
Majid Majidi, Majid Arab, Vahid Tavoosi
Abstract In this research, an optimal real-time trajectory planning method is proposed for autonomous ground vehicles in case of overtaking a moving obstacle. When an autonomous vehicle detects a moving vehicle ahead of it in a proper speed and distance and the braking is not efficient due to the lost of its kinematic energy, the autonomous vehicle decides to overtake the obstacle by performing a double lane-change maneuver. A two-phase nonlinear optimal problem is developed for generating the path for the overtaking maneuver. The cost function of the first phase is defined in such a way that the vehicle approaches the moving obstacle as close as possible. Besides, the cost function of the second phase is defined as the minimization of the sum of the vehicle lateral deviation from the reference path and the rate of steering angle during the overtaking maneuver while the lateral acceleration of the vehicle does not exceed a safe limit.
2017-03-28
Technical Paper
2017-01-0093
Balachander Dhanavanthan
Abstract Radio Frequency (RF) propagation in vehicular environments exhibits major transformations from indoor, outdoor and farmland multipath environments. The innovative advancement in Wireless Sensor Networks (WSNs) has made it necessary to recognise and predict the RF propagation losses for WSNs in vehicular environments. Very few models exist for network planning and deployment in vehicular environments. All of these models need an extensive statistical estimations and an in-depth knowledge of the vehicular environment. In this paper a different approach has been pursued and as a first step is to evaluate the factors which affect RF propagation in vehicular environments and how these factors affect each other while predicting propagation losses in vehicular environments.
2017-03-28
Technical Paper
2017-01-0092
Vladimir Hahanov, Wajeb Gharibi, Eugenia Litvinova, Svitlana Chumachenko, Arthur Ziarmand, Irina Englesi, Igor Gritsuk, Vladimir Volkov, Anastasiia Khakhanova
Abstract The new cyber-technological culture of the transport control based on virtual road signs and streetlight signals on the screen of car is the future of Humanity. A cyber-physical system (CPS) Smart Cloud Traffic Control, which realizes the mentioned culture, is proposed; it is characterized by the presence of the digitized regulatory rules, vehicles, infrastructure components, and also accurate monitoring, active cloud streetlight-free cyber control of road users, traffic lights, automatic output of operational regulatory actions (virtual traffic signs and traffic signals) to monitor of each vehicle. The main components of the cyber-physical system are the following: infrastructure, road users and rules, which have digital representation in cyberspace to realize a route, based on digital monitoring and cloud mobile control.
2017-03-28
Technical Paper
2017-01-0090
Ondrej Santin, Jaroslav Beran, Jaroslav Pekar, John Michelini, Junbo Jing, Steve Szwabowski, Dimitar Filev
Abstract Conventional cruise control systems in automotive applications are usually designed to maintain the constant speed of the vehicle based on the desired set-point. It has been shown that fuel economy while in cruise control can be improved using advanced control methods namely adopting the Model Predictive Control (MPC) technology utilizing the road grade preview information and allowance of the vehicle speed variation. This paper is focused on the extension of the Adaptive Nonlinear Model Predictive Controller (ANLMPC) reported earlier by application to the trailer tow use-case. As the connected trailer changes the aerodynamic drag and the overall vehicle mass, it may lead to the undesired downshifts for the conventional cruise controller introducing the fuel economy losses. In this work, the ANLMPC concept is extended to avoid downshifts by translating the downshift conditions to the constraints of the underlying optimization problem to be solved.
2017-03-28
Technical Paper
2017-01-0091
Songyao Zhou, Gangfeng Tan, Kangping Ji, Renjie Zhou, Hao Liu
Abstract The mountainous roads are rugged and complex, so that the driver can not make accurate judgments on dangerous road conditions. In addition, most heavy vehicles have characteristics of large weight and high center of gravity. The two factors above have caused most of the car accidents in mountain areas. A research shows that 90% of car accidents can be avoided if drivers can respond within 2-3 seconds before the accidents happen. This paper proposes a speed warning scheme for heavy-duty vehicle over the horizon in mountainous area, which can give the drivers enough time to respond to the danger. In the early warning aspect, this system combines the front road information, the vehicle characteristics and real-time information obtained from the vehicle, calculates and forecasts the danger that may happen over the horizon ahead of time, and prompts the driver to control the vehicle speed.
2017-03-28
Technical Paper
2017-01-0110
Hao Sun, Weiwen Deng, Chen Su, Jian Wu
Abstract The ability to recognize traffic vehicles’ lane change maneuver lays the foundation for predicting their long-term trajectories in real-time, which is a key component for Advanced Driver Assistance Systems (ADAS) and autonomous automobiles. Learning-based approach is powerful and efficient, such approach has been used to solve maneuver recognition problems of the ego vehicles on conventional researches. However, since the parameters and driving states of the traffic vehicles are hardly observed by exteroceptive sensors, the performance of traditional methods cannot be guaranteed. In this paper, a novel approach using multi-class probability estimates and Bayesian inference model is proposed for traffic vehicle lane change maneuver recognition. The multi-class recognition problem is first decomposed into three binary problems under error correcting output codes (ECOC) framework.
2017-03-28
Technical Paper
2017-01-0275
N. Obuli Karthikeyan, N. Prajitha, P. Sethu Madhavan
Abstract As technology gets upgraded every day, automotive manufacturers are paying more attention towards delivering a highly reliable product which performs its intended function throughout its useful life (without any failure). To develop a reliable product, accelerated combined stress testing should be conducted in addition to the conventional design validation protocol for the product. It brings out most of the potential failure modes of the product, so that necessary actions can be taken for the reliability improvement. This paper discusses about the field failure simulation and reliability estimation of automotive headlamp relays using accelerated combined stress testing. To analyze various field failure modes, performance and tear down analysis were carried out on the field failure samples. Field data (i.e. electrical, thermal and vibration signals) were acquired to evaluate normal use conditions.
2017-03-28
Technical Paper
2017-01-0398
Robert A. Smith, Allison Ward, Daniel Brintnall
Abstract Both pellet raw material and resulting extruded insulation samples were obtained from three grades of PVC used to produce automotive insulation and were examined for thermal stability on a Thermogravimetric Analyzer (TGA). The Flynn Wall technique was used to obtain degradation activation energies by plotting ln(heating rate) vs 1/T and using a literature value of 7% weight loss as the point of performance failure. The Arrhenius relationship was used to predict multiple year lifetimes at 100°C from the multiple hour degradation times observed on the TGA at 200°C. The insulation specimens of two of the samples were found to be significantly less thermally stable than the pellets - indicating slight decomposition occurred during extrusion onto the cable core. All cable insulation samples predicted service lifetimes many times the expected auto life. A PVC insulation sample was examined for failure at various oven aging temperatures using ASTM D3032 mandrel wrap testing.
2017-03-28
Technical Paper
2017-01-0395
Xin Xie, Danielle Zeng, Boyang Zhang, Junrui Li, Liping Yan, Lianxiang Yang
Abstract Vehicle front panel is an interior part which has a major impact on the consumers’ experience of the vehicles. To keep a good appearance during long time aging period, most of the front panel is designed as a rough surface. Some types of surface defects on the rough surface can only be observed under the exposure of certain angled sun light. This brings great difficulties in finding surface defects on the production line. This paper introduces a novel polarized laser light based surface quality inspection method for the rough surfaces on the vehicle front panel. By using the novel surface quality inspection system, the surface defects can be detected real-timely even without the exposure under certain angled sun light. The optical fundamentals, theory derivation, experiment setup and testing result are shown in detail in this paper.
2017-03-28
Technical Paper
2017-01-0190
Neelakandan Kandasamy, Steve Whelan
Abstract The range of Plug-In Electric Vehicles (EVs) is highly influenced by the electric power consumed by various sub systems, the major part of the power being used for vehicle climate control strategies in order to ensure an acceptable level of thermal comfort for the passengers. Driving range decreases with low temperatures in particular because cabin heating system requires significant amount of electric power. Range also decreases with high ambient temperatures because of the air conditioning system with electrically-driven compressor. Both thermal systems reduce EV driving range under real life operating cycles, which can be a barrier against market penetration. The structure of a vehicle is capable of absorbing a significant amount of heat when exposed to hot climate conditions. 50-70% of this heat penetrates through the glazing and raises both the internal cabin air temperature and the interior trim surface temperature.
2017-03-28
Technical Paper
2017-01-0240
Yanli Zhao, Hao Zhou, Yimin Liu
Abstract Ride Hailing service and Dynamic Shuttle are two key smart mobility practices, which provide on-demand door-to-door ride-sharing service to customers through smart phone apps. On the other hand, some big companies spend millions of dollars annually in third party vendors to offer shuttle services to pick up and drop off employees at fixed locations and provide them daily commutes for employees to and from work. Efficient fixed routing algorithms and analytics are the key ingredients for operating efficiency behind these services. They can significantly reduce operating costs by shortening bus routes and reducing bus numbers, while maintaining the same quality of service. This study developed an off-line optimization routing method for employee shuttle services including regular work shifts and demand based shifts (e.g. overtime shifts) in some regions.
2017-03-28
Technical Paper
2017-01-0238
Velappan Shalini, Sridharan Krishnamurthy, Srinivasan Narasimhan
Abstract This study compares the model efficacy of Neural Network and Vector Auto Regression. Further it also analyses the impact of predictors controlling for total industry volume. Understanding both the methodologies has their distinctive advantages and disadvantages. Our empirical findings indicate that based on the characteristics of data such as non-stationary, non-linearity and non-normality paves the way for use of machine learning algorithm relative to econometrics technique. Our results suggest that data type and its characteristics are more important in determining the methodology than the methodology itself. In industry, econometrics methodologies are widely used due to their usage simplicity and its ability to explain the relationships in simple terms.
2017-03-28
Technical Paper
2017-01-0239
Seth Bryan, Maria Guido, David Ostrowski, N. Khalid Ahmed
Abstract It is desirable to find methods to increase electric vehicle (EV) driving range and reduce performance variability of Plug-in Hybrid Electric Vehicles (PHEV). One strategy to improve EV range is to increase the charge power limit of the traction battery, which allows for more brake energy recovery. This paper applies Big Data technology to investigate how increasing the charge power limit could affect EV range in real world usage with respect to driving behavior. Big Data Drive (BDD) data collected from Ford employee vehicles in Michigan was analyzed to assess the impact of regenerative braking power on EV range. My Ford Mobile (MFM) data was also leveraged to find correlation to drivers nationwide based on brake score statistics. Estimated results show incremental improvements in EV range from increased charge power levels. Subsequently, this methodology and process could be applied to make future design decisions based on the dynamic nature of driving habits.
2017-03-28
Technical Paper
2017-01-0620
Chandrakant Parmar, Sethuramalingam Tyagarajan, Sashikant Tiwari, Ravindra Thonge, S Arun Paul
Abstract The engine compartment of passenger car application contains various source which radiates the produced heat and raises the temperature level of the compartment. The rise in compartment temperature increases the body temperature of individual component. The rise in body temperature of critical components can endanger the durability or functionality of the specific component or a system in which it operates. The aim of this paper is to strategize thermal protection of the rear mounted engine and its components of a vehicle having radiator and cooling fan mounted in front. An additional ventilation fan with speed sensor is fitted alongside rear mounted engine and a unique monitoring technique framed in the EMS ECU to protect critical components like HT cables, alternators, ECUs, wiring harness etc. from thermal damage. The EMS continuously monitors the engine speed, vehicle speed and the PWM signal of ventilation fan to ensure the intended operation of the ventilation fan.
2017-03-28
Technical Paper
2017-01-0006
Harald Bucher, Clemens Reichmann, Juergen Becker
Abstract The increasing complexity of electric/electronic architectures (EEA) in the automotive domain raised the necessity of model-based development processes for the design of such heterogeneous systems, which combine different engineering principles with different viewpoints. High-level simulation is a great means to evaluate the EEA in the concept phase of the design, since it reduces costly real-world experiments. However, model-based EEA design and analysis as well as its simulation are often separate processes in the development lifecycle. In this paper, we present a novel approach that extends state-of-the-art model-based systems engineering principles of EEA by a behavior specification reusing library components. The specification is seamlessly integrated in the development process of a single source EEA model. Therewith, the starting point is the abstract logical function architecture of the EEA.
2017-03-28
Technical Paper
2017-01-0004
Norbert Wiechowski, Thomas Rambow, Rainer Busch, Alexander Kugler, Norman Hansen, Stefan Kowalewski
Abstract Modern vehicles become increasingly software intensive. Software development therefore is critical to the success of the manufacturer to develop state of the art technology. Standards like ISO 26262 recommend requirement-based verification and test cases that are derived from requirements analysis. Agile development uses continuous integration tests which rely on test automation and evaluation. All these drove the development of a new model-based software verification environment. Various aspects had to be taken into account: the test case specification needs to be easily comprehensible and flexible in order to allow testing of different functional variants. The test environment should support different use cases like open-loop or closed-loop testing and has to provide corresponding evaluation methods for continuously changing as well as for discrete signals.
2017-03-28
Technical Paper
2017-01-0008
James Andrew Miloser
Abstract Simulink is a very successful and popular method for modelling and auto-coding embedded automotive features, functions and algorithms. Due to its history of success, university feeder programs, and large third party tool support, it has, in some cases, been applied to areas of the software system where other methods, principles and strategies may provide better options for the software and systems engineers and architects. This paper provides approaches to determine when best to apply UML and when best to apply Simulink to a typical automotive feature. Object oriented software design patterns as well as general guidelines are provided to help in this effort. This paper's intent is not to suggest a replacement for Simulink but to provide the software architects and designers additional options when decomposing high level requirements into reusable software components.
Viewing 91 to 120 of 16442