Towards Managing Variability in the Safety Design of an Automotive Hall Effect Sensor

International audienceThis paper discusses the merits and challenges of adopting software product line engineering (SPLE) as the main development process for an automotive Hall Effect sensor. This versatile component is integrated into a number of automotive applications with varying safety requirements (e.g., windshield wipers and brake pedals). This paper provides a detailed explanation as to why the process of safety assessment and verification of the Hall Effect sensor is currently cumbersome and repetitive:~it must be repeated entirely for every automotive application in which the sensor is to be used. In addition, no support is given to the engineer to select and configure the appropriate safety solutions and to explain the safety implications of his decisions. To address these problems, we present a tailored SPLE-based approach that combines model-driven development with advanced model composition techniques for applying and reasoning about specific safety solutions. In addition, we provide insights about how this approach can reduce the overall complexity, improve reusability, and facilitate safety assessment of the Hall Effect sensor

Towards Managing Variability in the Safety Design of an Automotive Hall Effect Sensor

ABSTRACT This paper discusses the merits and challenges of adopting software product line engineering (SPLE) as the main development process for an automotive Hall Effect sensor. This versatile component is integrated into a number of automotive applications with varying safety requirements (e.g., windshield wipers and brake pedals). This paper provides a detailed explanation as to why the process of safety assessment and verification of the Hall Effect sensor is currently cumbersome and repetitive: it must be repeated entirely for every automotive application in which the sensor is to be used. In addition, no support is given to the engineer to select and configure the appropriate safety solutions and to explain the safety implications of his decisions. To address these problems, we present a tailored SPLEbased approach that combines model-driven development with advanced model composition techniques for applying and reasoning about specific safety solutions. In addition, we provide insights about how this approach can reduce the overall complexity, improve reusability, and facilitate safety assessment of the Hall Effect sensor

The state of adoption and the challenges of systematic variability management in industry

Handling large-scale software variability is still a challenge for many organizations. After decades of research on variability management concepts, many industrial organizations have introduced techniques known from research, but still lament that pure textbook approaches are not applicable or efficient. For instance, software product line engineering—an approach to systematically develop portfolios of products—is difficult to adopt given the high upfront investments; and even when adopted, organizations are challenged by evolving their complex product lines. Consequently, the research community now mainly focuses on re-engineering and evolution techniques for product lines; yet, understanding the current state of adoption and the industrial challenges for organizations is necessary to conceive effective techniques. In this multiple-case study, we analyze the current adoption of variability management techniques in twelve medium- to large-scale industrial cases in domains such as automotive, aerospace or railway systems. We identify the current state of variability management, emphasizing the techniques and concepts they adopted. We elicit the needs and challenges expressed for these cases, triangulated with results from a literature review. We believe our results help to understand the current state of adoption and shed light on gaps to address in industrial practice.This work is supported by Vinnova Sweden, Fond Unique Interminist´eriel (FUI) France, and the Swedish Research Council. Open access funding provided by University of Gothenbur

Big Data and the Internet of Things

Advances in sensing and computing capabilities are making it possible to embed increasing computing power in small devices. This has enabled the sensing devices not just to passively capture data at very high resolution but also to take sophisticated actions in response. Combined with advances in communication, this is resulting in an ecosystem of highly interconnected devices referred to as the Internet of Things - IoT. In conjunction, the advances in machine learning have allowed building models on this ever increasing amounts of data. Consequently, devices all the way from heavy assets such as aircraft engines to wearables such as health monitors can all now not only generate massive amounts of data but can draw back on aggregate analytics to "improve" their performance over time. Big data analytics has been identified as a key enabler for the IoT. In this chapter, we discuss various avenues of the IoT where big data analytics either is already making a significant impact or is on the cusp of doing so. We also discuss social implications and areas of concern.Comment: 33 pages. draft of upcoming book chapter in Japkowicz and Stefanowski (eds.) Big Data Analysis: New algorithms for a new society, Springer Series on Studies in Big Data, to appea

Investigating the feasibility of vehicle telemetry data as a means of predicting driver workload

Driving is a safety critical task that requires a high level of attention and workload from the driver. Despite this, people often also perform secondary tasks such as eating or using a mobile phone, which increase workload levels and divert cognitive and physical attention from the primary task of driving. If a vehicle is aware that the driver is currently under high workload, the vehicle functionality can be changed in order to minimize any further demand. Traditionally, workload measurements have been performed using intrusive means such as physiological sensors. Another approach may be to use vehicle telemetry data as a performance measure for workload. In this paper, we present the Warwick-JLR Driver Monitoring Dataset (DMD) and analyse it to investigate the feasibility of using vehicle telemetry data for determining the driver workload. We perform a statistical analysis of subjective ratings, physiological data, and vehicle telemetry data collected during a track study. A data mining methodology is then presented to build predictive models using this data, for the driver workload monitoring problem

Integration of Quality Attributes in Software Product Line Development

Different approaches for building modern software systems in complex and open environments have been proposed in the last few years. Some efforts try to apply Software Product Line (SPL) approach to take advantage of the massive reuse for producing software systems that share a common set of features. In general quality assurance is a crucial activity for success in software industry, but it is even more important when talking about Software Product Lines since the intensive reuse of assets makes the quality attributes (a measurable physical or abstract property of an entity) of the assets to be transmitted to the whole SPL scope. However, despite the importance that quality has in software product line development, most of the methodologies being applied in Software Product Line Development focus only on managing the commonalities and variability within the product line and not giving support to the non--¿ functional requirements that the products must fit. The main goal of this master final work is to introduce quality attributes in early stages of software product line development processes by means of the definition of a production plan that, on one hand, integrates quality as an additional view for describing the extension of the software product line and, on the other hand introduces the quality attributes as a decision factor during product configuration and when selecting among design alternatives. Our approach has been defined following the Model--¿ Driven Software Development paradigm. Therefore all the software artifacts defined had its correspondent metamodels and the processes defined rely on automated model transformations. Finally in order to illustrate the feasibility of the approach we have integrated the quality view in an SPL example in the context of safety critical embedded systems on the automotive domain.González Huerta, J. (2011). Integration of Quality Attributes in Software Product Line Development. http://hdl.handle.net/10251/15835Archivo delegad

Design and Validation of a High-Level Controller for Automotive Active Systems

Active systems, from active safety to energy management, play a crucial role in the development of new road vehicles. However, the increasing number of controllers creates an important issue regarding complexity and system integration. This article proposes a high-level controller managing the individual active systems - namely, Torque Vectoring (TV), Active Aerodynamics, Active Suspension, and Active Safety (Anti-lock Braking System [ABS], Traction Control, and Electronic Stability Program [ESP]) - through a dynamic state variation. The high-level controller is implemented and validated in a simulation environment, with a series of tests, and evaluate the performance of the original design and the proposed high-level control. Then, a comparison of the Virtual Driver (VD) response and the Driver-in-the-Loop (DiL) behavior is performed to assess the limits between virtual simulation and real-driver response in a lap time condition. The main advantages of the proposed design methodology are its simplicity and overall cooperation of different active systems, where the proposed model was able to improve the vehicle behavior both in terms of safety and performance, giving more confidence to the driver when cornering and under braking. Some differences were discovered between the behavior of the VD and the DiL, especially regarding the sensitivity to external disturbances

Trailer Reverse Assist. Optical Follow Me

Backing-up a trailer is a difficult task even for experienced users, and thus, solutions exist for assisting the steering of a vehicle-trailer system by just requiring the input of the desired trailer’s trajectory. Nevertheless, the problem is not entirely solved as the selected trajectory clearance while reversing a trailer is not completely available due to visibility obstructions, making reversing a trailer an unsafe maneuver. The objective of this work is to perform a proof-of-concept of a system which aids the user in the process of backing up a trailer through the desired trajectory where limited visibility is present. This was accomplished by developing an add-on feature capable of tracking a helping person. The new feature provides the required information so that existing compatible trailer reversing solutions can steer and accelerate the vehicle to follow the tracked person while also keeping a safe distance. Moreover, potential collisions are prevented by the addition of a close proximity object detection functionality. For this, a scaled prototype of the proposed system was developed by applying the “Vee Model” methodology where the requirements, architecture, solution design, implementation, and validation steps were followed. A successful proof-of-concept was accomplished after validating the capacity of the prototype to both identify and follow a person, while maintaining a safe distance, and to detect objects in the vehicle’s path. In addition, the documentation of the system’s design, development, and validation was achieved rendering the feature ready for full scale development. In conclusion, the “Trailer Reverse Assist - Optical Follow Me” system add-on can further assist in the process of backing-up a trailer safely in environments where the visibility is limited while also preventing collisions with nearby objects.ITESO, A. C.ContinentalConsejo Nacional de Ciencia y Tecnologí