Automotive Domain Research Articles

Model-based fault injection for testing gray-box systems

Motivated by applications in the automotive domain, particularly the Autosar basic software standard, we present a technique to improve model-based testing by allowing model-level fault injections. These models are plugged into a larger system as executable components to test it for general tolerance to slightly varying, possibly faulty components or library implementations. Such model execution is possible through applying an automated mocking mechanism and model cross-referencing. Systematic modelling and testing is possible by having comprehensive fault models which both simulate faults and guide the model-based testing procedure towards quicker discovery of these faults. We show the principles of our method on an illustrative example and discuss how it is implemented in a commercial model-based testing tool QuickCheck and applied to a more realistic case study. More generally, this work explores multi-purpose (or meta) modelling – an approach where one parametric model is used for different test targets, like functional testing or safety testing.

Two-Layered Falsification of Hybrid Systems Guided by Monte Carlo Tree Search

Few real-world hybrid systems are amenable to formal verification, due to their complexity and black box components. Optimization-based falsification-a methodology of search-based testing that employs stochastic optimization-is thus attracting attention as an alternative quality assurance method. Inspired by the recent work that advocates coverage and exploration in falsification, we introduce a two-layered optimization framework that uses Monte Carlo tree search (MCTS), a popular machine learning technique with solid mathematical and empirical foundations (e.g., in computer Go). MCTS is used in the upper layer of our framework; it guides the lower layer of local hill-climbing optimization, thus balancing exploration and exploitation in a disciplined manner. We demonstrate the proposed framework through experiments with benchmarks from the automotive domain.

Safety-Related Challenges and Opportunities for GPUs in the Automotive Domain

GPUs have been shown to cover the computing performance needs of autonomous driving (AD) systems. However, since the GPUs used for AD build on designs for the mainstream market, they may lack fundamental properties for correct operation under automotive's safety regulations. In this paper, we analyze some of the main challenges in hardware and software design to embrace GPUs as the reference computing solution for AD, with the emphasis in ISO 26262 functional safety requirements.

An Algebraic Framework for Runtime Verification

Runtime verification (RV) is a pragmatic and scalable, yet rigorous technique, to assess the correctness of complex systems, including cyber-physical systems (CPSs). Modern RV tools also allow to measure the distance of a CPS behavior from a given formal requirement, thus, to quantify the robustness of a CPS with respect to perturbations caused by the physical environment. In this paper, we propose algebraic RV (ARV), a general, semantic framework for correctness and robustness monitoring. ARV implements an abstract monitoring procedure, in which the specification language (STL) can be instantiated with various qualitative and quantitative semantics. This allows us to expose the core aspects of RV, by separating the monitoring algorithm from the concrete choice of the STL and its semantics. We demonstrate the effectiveness of our framework on two examples from the automotive domain.

Participatory Prototyping to Inform the Development of a Remote UX Design System in the Automotive Domain

This study reports on the empirical findings of participatory design workshops for the development of a supportive automotive user experience design system. Identifying and addressing this area with traditional research methods is problematic due to the different user experience (UX) design perspectives that might conflict and the related limitations of the automotive domain. To help resolve this problem, we conducted research with 12 user experience (UX) designers through individual participatory prototyping activities to gain insights into their explicit, observable, tacit and latent needs. These activities allowed us to explore their motivation to use different technologies; the system’s architecture; detailed features of interactivity; and to describe user needs including efficiency, effectiveness, engagement, naturalness, ease of use, information retrieval, self-image awareness, politeness, and flexibility. Our analysis led us to design implications that translate participants’ needs into UX design goals, informing practitioners on how to develop relevant systems further.

A Hardware Architecture for Cell-Based Feature-Extraction and Classification Using Dual-Feature Space

Many computer-vision and machine-learning applications in robotics, mobile, wearable devices, and automotive domains are constrained by their real-time performance requirements. This paper reports a dual-feature-based object recognition coprocessor that exploits both histogram of oriented gradient (HOG) and Haar-like descriptors with a cell-based parallel sliding-window recognition mechanism. The feature extraction circuitry for HOG and Haar-like descriptors is implemented by a pixel-based pipelined architecture, which synchronizes to the pixel frequency from the image sensor. After extracting each cell feature vector, a cell-based sliding window scheme enables parallelized recognition for all windows, which contain this cell. The nearest neighbor search classifier is, respectively, applied to the HOG and Haar-like feature space. The complementary aspects of the two feature domains enable a hardware-friendly implementation of the binary classification for pedestrian detection with improved accuracy. A proof-of-concept prototype chip fabricated in a 65-nm SOI CMOS, having thin gate oxide and buried oxide layers (SOTB CMOS), with 3.22-mm2 core area achieves an energy efficiency of 1.52 nJ/pixel and a processing speed of 30 fps for $1024\times 1616$ -pixel image frames at 200-MHz recognition working frequency and 1-V supply voltage. Furthermore, multiple chips can implement image scaling, since the designed chip has image-size flexibility attributable to the pixel-based architecture.

Enabling the Interoperability of the Modelica DSL and Matlab Simulink towards the Development of Self-Adaptive Dynamic Systems

Domain Specific Languages (DSL) are an important concept that is used in industry, in order to enable the fast and cost-efficient design of specific functions/components, and/or to target particular aspects of the systems' development and operation. In the current article, the authors describe their experiences on the integration of the Modelica DSL into a platform that enables the integration and interoperability of model-based tools across the various phases of the system development process. Furthermore, it is illustrated how Matlab Simulink can be used in parallel in the course of the same system design undertaking. Thereby, the authors present their approach and compare different tools which were used, in order to efficiently complete the integration, and finally exemplify the outcome on a case study related to a self-adaptive dynamic system from the automotive domain.

Vehicle-Based Relay Assistance for Opportunistic Crowdsensing Over Narrowband IoT (NB-IoT)

The Internet of Things (IoT) undergoes a fundamental transformation by augmenting its conventional sensor network deployments with more advanced and mobile devices, such as connected and self-driving cars. This fusion of embedded and automotive domains promises to deliver unprecedented mutual benefits, where vehicles will receive timely updates from their proximate sensors while assisting them in delivering their sensory data to the remote network infrastructure. In this paper, we put forward the vision of opportunistic crowdsensing applications, in which the ubiquitous deployments of low-cost and battery-constrained IoT sensors take advantage of more capable and energy-abundant vehicle-mounted mobile relays. In particular, we consider the use of the emerging narrowband IoT radio technology recently ratified by 3GPP and offering efficient means for underlying wireless connectivity. Our rigorous mathematical analysis supported with comprehensive system-level evaluations reveals the effects of vehicle-based relays on the important metrics of interest, such as connection reliability, transmission latency, and communication energy efficiency. These systematic findings advocate for an extensive utilization of vehicular relays as part of the next-generation IoT ecosystem.

Computational performance analysis of overheating mitigation measures in parked vehicles

Parked vehicles have the tendency to overheat quickly. This can lead to a negative impact on the thermal comfort of the driver and its passengers, as well as intensive use of air conditioning systems, and thus fuel consumption of the vehicle or, in the case of electric mobility, a reduced cruising range. In the search for effective measures to mitigate this effect, important guidance can be provided by the field of sustainable building design. On the one hand, inspiration can come from design strategies in terms of shapes and advanced cover materials, but this paper advocates that this can also pertain to the simulation-based design support tools that are used by building engineers. This paper first presents the results of a thermal soak test, and then uses this data to demonstrate the suitability of the building performance simulation tool EnergyPlus for predicting the thermal behavior of parked vehicles. This fit-for-purpose validated model is used to evaluate the performance of three overheating mitigation measures for two car models in two climates. The results show that spectrally selective glazing can reduce the cabin air temperature by 12.5 °C and when combined with solar reflective opaque surfaces, the reduction of cabin air temperature can reach 23.8 °C. Increased use of building performance simulation in the automotive domain can help to further optimize the overheating reduction potential of cars.

Energy Efficiency Due to a Common Global Timebase—Synchronizing FlexRay to 802.1AS Networks as a Foundation

Modern automotive control applications require a holistic time-sensitive development. Nowadays, this is achieved by technologies specifically designed for the automotive domain, like FlexRay, which offer a fault-tolerant time synchronization mechanism built into the protocol. Currently, the automotive industry adopts the Ethernet within the car, not only for embedding consumer electronics, but also as a fast and reliable backbone for control applications. Still, low-cost but highly reliable sensors connected over the traditional Controller Area Network (CAN) deliver data needed for autonomous driving. To fusion the data efficiently among all, a common timebase is required. The alternative would be oversampling, which uses more time and energy, e.g., at least double the perception rates of sensors. Ethernet and CAN do require the latter by default. Hence, a global synchronization mechanism eases tremendously the design of a low power automotive network and is the foundation of a transparent global clock. In this article, we present the first step: Synchronizing legacy FlexRay networks to the upcoming Ethernet backbone, which will contain a precise clock over the generalized Precision Time Protocol (gPTP) defined in IEEE 802.1AS. FlexRay then could still drive its strengths with deterministic transmission behavior and possibly also serve as a redundant technology for fail-operational system design.

Architecture enforcement concerns and activities - An expert study

Architecture enforcement is concerned with the correct and seamless implementation of architecture design decisions in order to ensure software quality. In a previous study, we conducted an empirical study in order to gain insight into the industrial practice of architecture enforcement. There, we asked 12 software architects from industry about their experience with the architecture enforcement process. As a result, we identified architecture enforcement concerns and activities. In this paper, we extend our contributions of the existing study. Firstly, we conducted five additional interviews with software architects from two different domains, namely the enterprise application and the automotive domain. This adds new architecture concerns and activities to the existing list. Secondly, we conducted a literature review. We compared our findings from the interviews with the results from the literature review and evaluated how architects’ enforcement concerns and activities are discussed in literature. We found that several concerns and activities are already known from literature, but are not viewed in the context of architecture enforcement by the software architecture community. Lastly, we connected the discovered architecture concerns and activities with each other. Those relationships determine the reason why a specific architecture enforcement activity is conducted.

Testing in the incremental design and development of complex products

Testing is an important aspect of design and development which consumes significant time and resource in many companies. However, it has received less research attention than many other activities in product development, and especially, very few publications report empirical studies of engineering testing. Such studies are needed to establish the importance of testing and inform the development of pragmatic support methods. This paper combines insights from literature study with findings from three empirical studies of testing. The case studies concern incrementally developed complex products in the automotive domain. A description of testing practice as observed in these studies is provided, confirming that testing activities are used for multiple purposes depending on the context, and are intertwined with design from start to finish of the development process, not done after it as many models depict. Descriptive process models are developed to indicate some of the key insights, and opportunities for further research are suggested.

Mediating role of process simplification in process integration and upstream supply chain flexibility

PurposeThe purpose of this paper is to investigate the mediating role of process simplification on the relationship between process integration and upstream supply chain flexibility in Indian automotive organizations.Design/methodology/approachThe three-step mediation analysis was performed using SPSS macro PROCESS to assess the mediating role of process simplification on the relationship between process integration constructs: top management commitment and supplier relationship; and upstream supply chain flexibility.FindingsThe results indicate a complete mediation effect of process simplification between supplier relationship and upstream supply chain flexibility, while partial mediation effect is noticed between top management commitment and upstream supply chain flexibility.Practical implicationsFor Indian automotive managers, the study suggests that for improving the upstream supply chain flexibility, organizations must have a strategy towards improving the simplification of supply chain processes by upgrading technology and providing training to their suppliers. This understanding will help the automotive managers to simplify their upstream supply chain processes for gaining competitive positioning and maximizing the organizational profit.Originality/valueThis study has considered the mediating role of process simplification (a relatively less studied variable) specifically in the context of its impact on upstream supply chain flexibility. Also, the presented study explores this role in the Indian automotive domain which further enhances its value for both practitioners and researchers alike.

Use, potential, and showstoppers of models in automotive requirements engineering

Several studies report that the use of model-centric methods in the automotive domain is widespread and offers several benefits. However, existing work indicates that few modelling frameworks explicitly include requirements engineering (RE), and that natural language descriptions are still the status quo in RE. Therefore, we aim to increase the understanding of current and potential future use of models in RE, with respect to the automotive domain. In this paper, we report our findings from a multiple-case study with two automotive companies, collecting interview data from 14 practitioners. Our results show that models are used for a variety of different purposes during RE in the automotive domain, e.g. to improve communication and to handle complexity. However, these models are often used in an unsystematic fashion and restricted to few experts. A more widespread use of models is prevented by various challenges, most of which align with existing work on model use in a general sense. Furthermore, our results indicate that there are many potential benefits associated with future use of models during RE. Interestingly, existing research does not align well with several of the proposed use cases, e.g. restricting the use of models to informal notations for communication purposes. Based on our findings, we recommend a stronger focus on informal modelling and on using models for multi-disciplinary environments. Additionally, we see the need for future work in the area of model use, i.e. information extraction from models by non-expert modellers.

Building an automotive security assurance case using systematic security evaluations

Security testing and assurance in the automotive domain is challenging. This is predominantly due to the increase in the amount of software and the number of connective entry points in the modern vehicle. In this paper we build on earlier work by using a systematic security evaluation to enumerate undesirable behaviours, enabling the assignment of severity ratings in a (semi-) automated manner. We demonstrate this in two case studies; firstly with the native Bluetooth connection in an automotive head unit, and secondly with an aftermarket diagnostics device. We envisage that the resulting severity classifications would add weight to a security assurance case, both as evidence and as guidance for future test cases.

On the Application of ISO 26262 in Control Design for Automated Vehicles

Research on automated vehicles has experienced an explosive growth over the past decade. A main obstacle to their practical realization, however, is a convincing safety concept. This question becomes ever more important as more sophisticated algorithms are used and the vehicle automation level increases. The field of functional safety offers a systematic approach to identify possible sources of risk and to improve the safety of a vehicle. It is based on practical experience across the aerospace, process and other industries over multiple decades. This experience is compiled in the functional safety standard for the automotive domain, ISO 26262, which is widely adopted throughout the automotive industry. However, its applicability and relevance for highly automated vehicles is subject to a controversial debate. This paper takes a critical look at the discussion and summarizes the main steps of ISO 26262 for a safe control design for automated vehicles.

Identifying the business and social networks in the domain of production by merging the data from heterogeneous internet sources

People, companies, and institutions form networks as part of their technical, economic, and social activities. As a consequence, these networks have an influence on how companies conduct business. Recently, the Internet, professional, and scientific social networks have contributed to the ease and simplicity of the network forming process and the public availability of the corresponding data. We investigate whether useful information about the relationships between individuals, companies, and institutions for the domain of production can be extracted from publicly available, structured and unstructured data that is merged from various Internet sources. We demonstrate that relevant information about the structures of these networks can be obtained by merging publicly available data using a combination of advanced computational methods including web crawling, machine learning, and creating mash-ups of publicly available services. The feasibility and the applicability of the approach are shown for a case in the automotive domain. A potential use case of the resulting data is demonstrated, showing how the approach can be used to find specific skills and expertise for a scientific community consisting of people from industry and academia. The proposed approach can be used for the modelling and analysis of various forms of collaboration between and within businesses. As a tool, it could be used for the purposes of strategic networking, to facilitate the creation of project consortia, to identify competitors and other stakeholders in a certain domain, to pinpoint communication channels, to search for specific expertise, or to identify organisational and social structures within organisations.

Software traceability in the automotive domain: Challenges and solutions

In the automotive domain, the development of all safety-critical systems has to comply with safety standards such as ISO 26262. These standards require established traceability, the ability to relate artifacts created during development of a system, to ensure resulting systems are well-tested and therefore safe. This paper contrasts general traceability challenges and solutions with those specific to the automotive domain, and investigates how they manifest in practice. We combine three data sources: a tertiary literature review to identify general challenges and solutions; a case study with an automotive supplier as validation for how the challenges and solutions are experienced in practice; and a multi-vocal literature review to identify challenges and solutions specific to the automotive domain. We found 22 challenges and 16 unique solutions in the reviews. 17 challenges were identified in the case study; six remain unsolved. We discuss challenges and solutions from the perspectives of academia, tool vendors, consultants and users, and identify differences between scientific and “grey” literature. We discuss why challenges remain unsolved and propose solutions. Our findings indicate that there is a significant overlap between general traceability challenges and those in the automotive domain but that they are experienced differently.

Estimation Design Using Youla Parametrization With Automotive Applications

Youla parametrization is a well-established technique in deriving single-input single-output (SISO) and, to a lesser extent, multiple-input multiple-ouput (MIMO) controllers (Youla, D., Bongiorno, J. J., Jr., and Lu, C., 1974, “Singleloop Feedback-Stabilization of Linear Multivariable Dynamical Plants,” Automatica, 10(2), pp. 159–173). However, the utility of this methodology in estimation design, specifically in the framework of controller output observer (COO) (Ozkan, B., Margolis, D., and Pengov, M., 2008, “The Controller Output Observer: Estimation of Vehicle Tire Cornering and Normal Forces,” ASME J. Dyn. Syst., Meas., Control, 130(6), p. 061002), is not established. The fundamental question to be answered is as follows: is it possible to design a deterministic estimation technique using Youla paramertization with the same robust performance, or better, than well-established stochastic estimation techniques such as Kalman filtering? To prove this point, at this stage, a comparative analysis between Youla parametrization in estimation and Kalman filtering is performed through simulations only. In this paper, we provide an overview of Youla parametrization for both control and estimation design. We develop a deterministic SISO and MIMO Youla estimation technique in the framework of COO, and we investigate the utility of this method for two applications in the automotive domain.

Blockchain in Automotive Domain

The Blockchain is a revolutionary database that does away with the weaknesses of traditional solutions for storing big data. It provides a transparent record of the entire business network, allowing buyers and sellers of each vehicle to track where the vehicle is in its lifecycle. The blockchain as a technology is more of a ledger recording agreements. It is a system which contains a continuously growing list of records, called blocks, which are linked and secured using blockchain-based Public Key Infrastructure (PKI) encryption. It also provides a complete history of deals made between two or more parties, in which the record cannot be altered retroactively without the alteration of all subsequent blocks and the collusion of the network.