Using Models to Improve the Availability of Automotive Software Architectures

The application of AI technology in architectural software has brought various innovations and changes to the industry. By introducing convolutional neural networks and deep neural networks, architectural design software is expected to automatically identify and generate complex architectural images, optimize the design process, and provide intelligent design assistance. Through literature research, this paper aims to discuss the specific application of CNN and DNN in parametric design and the innovation brought by them, and analyzes the application of these technologies in architectural image recognition, generation, design optimization and other aspects. This paper aims to provide a comprehensive reference for researchers in related fields and promote the innovative application of AI technology in architectural design. The application of AI technology in architectural software has brought numerous innovations and changes to the industry. By introducing convolutional neural networks and deep neural networks, architectural design software is expected to automatically identify and generate complex architectural images, optimize the design process, and provide intelligent design assistance. Through literature research, this paper aims to discuss the specific application of CNN and DNN in parametric design and the innovation brought by them; it also analyzes the application of these technologies in architectural image recognition, generation, design optimization, and other aspects. This paper aims to provide a comprehensive reference for researchers in related fields and promote the innovative application of AI technology in architectural design.

In order to achieve greater performance with low power dissipation at moderate clock rate which is required to reduce the electromagnetic interference and compatibility issues with high speed processors, multicore processors have been implemented in automotive electronic control units(ECUs). Multicore processors enable the automobile manufacturers to add more functionality into one ECU rather than integrating more number of single functional ECUs. With the introduction of multicore processors in automotive ECUs, complexity in the design, development, and verification of the applications software have been increased tremendously. Even though both the hardware and software have parallelizability, there are certain design challenges such as: integrating various application software and scheduling the application tasks to balance the load across the cores. It requires to sequencing threads within the chained tasks, segregating those into thread sets and allocating to the available processing cores. In this paper, we address the problem of clustering numerous task threads and allocating them on multiple identical cores.We present a low-complexity modified heuristic algorithm to partition and build thread sets and map those on to cores so as to balance the load across the cores. It is observed that, minimum average load of the total load is distributed to each core to achieve a balanced load with task scheduling in simulating environment. The performance of the algorithm on dual core, tri core and quad core processors have been verified and compared to the same on single core processor.

Context. Software systems play a pervasive role in people's lives. Since ethics in software systems is hardly ever considered as a first-class entity, its support of, or hindrance to, values of users and society is usually neglected. Addressing ethics requires both to consider the context in which a software system is used, and the fact that ethical values (e.g., social, cultural and personal) are intrinsically ambiguous and subjective. Software architecture and architecture design decision making are the right levels of abstraction to both consider such a context, and support reasoning about such subjectivities. Goal. We aim to embed ethical aspects in software architecture design decision making. We have studied the state of the art in ethics for software engineering, to identify the ethical aspects influencing software architecture design. We will use the learned ethical aspects to (i) support architecture design decision making with respect to ethics through proposing methods, models, and techniques, and (ii) conduct empirical studies to evaluate them in industrial practice. Method. We will adopt a design science approach for our research which includes three phases: (i) problem understanding, (ii) solution design, and (iii) solution validation. Results. Based on our previous literature study, we build models (and techniques) embedding the ethical aspects to be used in architecture design decision making. Also, we will apply design science research to use and validate these models in a method assisting practitioners and architects to embed ethical aspects in software architecture design.

Electronic Control Units (ECUs) are widely used to improve the comfort and reliability of vehicles. It has become the fundamental building block of any automotive subsystem and is interfaced with electro mechanics counterpart. To meet the system wide requirements, these ECUs are interconnected using the communication infrastructure. Although the communication infrastructure in terms of, predominantly, the CAN based vehicle network took its birth to enable ECUs to work in a coordinated manner in order to support system wide requirements, during the past decade, this infrastructure was also viewed as a potential means to incorporate extensibility in terms of addition of newer ECUs which are built for implementing additional requirements. With this paradigm, the number of ECUs started growing in a steep manner, uncontrolled and as a result, today, it is not hard to see a high segment automotive housing ECUs as large as 75–80. Hence, load balancing mechanisms are needed to ease ECU integration and for efficient utilization of CPU power in ECUs. In this paper, we explain the concept of load balancing on the basis of CPU utilization across ECUs.

This paper performs a feasibility analysis of deploying Model Predictive Control (MPC) for vehicle platooning on an On-Board Unit (OBU) and performance benchmarking considering interference from other (system) tasks running on an OBU. MPC is a control strategy that solves an implicit (on-line) or explicit (off-line) optimisation problem for computing the control input in every sample. OBUs have limited computational resources. The challenge is to implement an MPC algorithm on such automotive Electronic Control Units (ECUs) with an acceptable timing behavior. Moreover, we should be able to stop the execution if necessary at the cost of performance. We measured the computational capability of a unit developed by Cohda Wireless and NXP under the influence of its Operating System (OS). Next, we analysed the computational requirements of different state-of-the-art MPC algorithms by estimating their execution times. We use off-the-shelf and free automatic code generators for MPC to run a number of relevant MPC algorithms on the platform. From the results, we conclude that it is feasible to implement MPC on automotive ECUs for vehicle platooning and we further benchmark their performance in terms of MPC parameters such as prediction horizon and system dimension.

As de facto standards of in-vehicle network communications among various ECUs (Electronic Control Units), CAN (Controller Area Network) protocols invented by Bosch rely on the privately-defined unique identifiers CAN ID in CAN messages which do not convey any destination address. On the other hand, sticking to error handling mechanisms in CAN protocols, an ECU with an amount of transmission errors would enter bus-off state (i.e., go offline thereupon) and shall be recovered according to some prescribed bus-off recovery mode (BOM). All these sensitive CAN knowledge concealed inside an ECU by OEMs (Original Equipment Manufacturers) shall not be revealed and could be found extensive practical applications to both adversarial behavior (e.g., target ECU attacks) and security enhancement mechanisms (e.g., intrusion detection system designs). The paper presents FirmCAN, the first automatic analysis framework to dope out sensitive CAN knowledge (CAN IDs and bus-off recovery mode in particular) compiled in automotive ECU firmwares. FirmCAN first identifies base address (using accurate absolute function entry addresses), and then performs CAN module API positioning and sensitive configuration information resolution. We buckle down to automotive ECUs that resort to fixed-address mailboxes as CAN module transmission buffers (e.g., Renesas SuperH/RA series) and present concrete algorithms for each analysis phase. Our experimental evaluations first investigate firmwares extracted from real automotive ECUs. We then develop our own applications using RA6M4 development boards, which not only produce required firmwares to evaluate FirmCAN, but also create ground truth through hardware debugging. All evaluations demonstrate that FirmCAN can accurately garner above-mentioned sensitive CAN knowledge. FirmCAN can be trivially generalized to engage in extended frames and CAN modules with similar transmission logic, e.g., TI (Texas Instruments), ST (ST Microelectronics), etc.

Software architecture involves a series of decisions based on many factors in a wide range of software development. Architects face recurring issues in different software architecture design, and to reduce huge cost and risks, software architecture decisions can rely on a set of idiomatic patterns commonly named architectural styles or patterns. Architectural pattern determines the vocabulary of components and connectors that are used in instances of the pattern together with a set of constraints to combine the two. Little contemporary data exists to document actual practices used by software professionals when selecting and incorporating architectural patterns for their projects in industry. Therefore, a comprehensive survey of software professionals was conducted to attempt to discover these practices. This exploratory survey and its quantitative results offer opportunities for further interpretation and comparison. Data from this survey are presented in this paper and include characteristics of projects, practices, organizations, and practitioners related to the usage of architectural patterns. Some of the notable findings include that architectural patterns are widely used in software projects with the Model–View–Controller being the most common. Despite reported difficulties in incorporating architectural patterns, the majority of the software professionals revealed that patterns were the most essential for completing the projects. The most difficult pattern to implement and the most expensive to adopt was the peer-to-peer, while the easiest was the client–server.

The modern automotive market is heading towards significant transformations in terms of automation and driver assistance. To cope up with this rapidly evolving technology in modern vehicles, the use of electronic system has reached to a new level. Following this rapid growth of electronic systems in automotive industry, the need for ensuring safety and reliability has become one of the most important issues for all car manufacturers where the ISO 26262 functional safety standard plays a key role. The increased complexity in automotive electronic control units (ECU) has raised many technical and economic arguments for designers to choose between two options, either using multicore architecture or increasing monolithic processor's performance. This paper presents functional safety compliance of an electronic control unit for a battery pack system and looks into a novel multi-core architectural approach for fulfilling the requirements.

The complexity of electronic control units (ECU) in automotive applications increased dramatically over the past years. New functional requirements to control direct injection engines or adaptive cruise control for example introduce additional software algorithms. Furthermore, stricter regulations for the exhaust system and on-board diagnosis contribute to the fast growing code sizes. Next generation engine management systems include programs of more than 500 KBytes in size which run on 32 bit processors. For the first time floating point units will be used to perform computations with physical values directly, rather than transforming them to a hexadecimal representation. In order to run in pace with the physical process to be controlled, the ECU software has to meet stringent real-time constraints. Functions like injection and ignition require a highly accurate timing to guarantee fuel efficient operation. Moreover, knock-control and misfire-detection have to work reliably to prevent severe damages of the engine. Control units for braking and steering systems are directly linked to the passengers security and are thus classified as safety critical. Because real-time operating systems (OS) offer powerful means to handle complex functions under real-time conditions they are more and more introduced in automotive ECUs. The complexity of automotive applications varies a lot from simple control functions in the field of body electronics to high-end applications in the powertrain. Since conventional real-time operating systems are not able to fulfill the implied requirements in terms of runtime performance and memory consumption a lot of in-house solutions emerged in various companies. The wish to save development time by reusing existing components and the need of porting software between different ECUs even from different suppliers led to the OSEK/VDX standardization of an automotive real-time OS. Software sharing, i.e. the distributed development of ECU-software at different partner companies will also benefit from the introduction of a standardized OS. (18 pages)

This paper provides an introduction to the field of software engineering requires facility in architectural software design. The goal is to demonstrate the current state of the discipline and examine the ways in which architectural design can impact soft-ware design. Software architecture is used to describe a high level design methodology of large software systems. It provides the overall structure of a system in an abstract and structured fashion. A smart architectural demonstration holds the key to the effectiveness of a software architecture description and usage. This paper focuses on criterion to select appropriate architecture style for software system. It also gives overview of definition, goals and requirements of software architecture with various architecture styles, their benefits and applications. The authors have also described the requirements and goals of robotic software architecture. The proposal for layered robotic software architecture for a distributed system is also presented.

Future Advanced Driver Assistance Systems (ADAS) require the continuous computation of detailed maps of the vehicle's environment. Due to the high demand of accuracy and the enormous amount of data to be fused and processed, common architectures used today, like single-core processors in automotive Electronic Control Units (ECUs), do not provide enough computing power. Here, emerging embedded multi-core architectures are appealing such as embedded Graphics Processing Units (GPUs). In this paper, we (a) identify and analyze common subalgorithms of ADAS algorithms for computing environment maps, such as interval maps, for suitability to be parallelized and run on embedded GPUs. From this analysis, (b) performance models are derived on achievable speedups with respect to sequential single-core CPU implementations. (c) As a third contribution of this paper, these performance models are validated by presenting and comparing a novel parallelized interval map GPU implementation against a parallel occupancy grid map implementation. For both types of environment maps, implementations on an Nvidia Tegra K1 prototype are compared to verify the correctness of the introduced performance models. Finally, the achievable speedups with respect to a single-core CPU solution are reported. These range from 3x to 275x for interval and grid map computations.

In software architecture design, we explore design alternatives and make decisions about adoption or rejection of a design from a web of complex and often uncertain information. Different architectural design decisions may lead to systems that satisfy the same set of functional requirements but differ in certain quality attributes. In this paper, we propose a Bayesian Network based approach to rational architectural design. Our Bayesian Network helps software architects record and make design decisions. We can perform both qualitative and quantitative analysis over the Bayesian Network to understand how the design decisions influence system quality attributes, and to reason about rational design decisions. We use the KWIC (Key Word In Context) example to illustrate the principles of our approach.

Metric-based Evaluation of Implemented Software Architectures

As the complexity of automotive Electronic Control Units (ECU) constantly increases with functionalities such as Autonomous Driving (AD), Advanced Driving Assistance Systems (ADAS), and Augmented Reality (AR), new trends emerge in automotive ECU network topologies and software engineering. Centralized ECU architectures are gaining traction, consolidating more vehicle functions into fewer ECUs to reduce network load and improve efficiency, in comparison to traditional de-centralized ECU architectures. However, this shift introduces new challenges, particularly in terms of security and the continual operation of critical functions. A major challenge is that a potential security breach and the subsequent ECU compromise would impact numerous vehicle functionalities. Therefore, ensuring the reliability and security of these systems requires innovative solutions. This paper proposes an approach that addresses these challenges by presenting the concept of “vehicle functions migration” to alternative or auxiliary ECUs, enhancing the overall system’s robustness and security. Finally, the implementation and demonstration of this approach within the EU funded project “REWIRE” is presented.

Significant challenges arise when capturing architectural knowledge and design decisions for a software project, resulting in high capturing effort and few captured decisions. These challenges stem from the fact that software development is a group activity that involves different situations, goals, methodologies and needs of the software development organization. A projectpsilas documentation processes should be flexible to suit the needs and goals of an organization and allow multiple approaches. We propose three approaches for capturing design decisions to increase the knowledge retention and decision capture rates in an organization: 1) formal elicitation; 2) lightweight top-down capture; and 3) lightweight bottom-up capture. Customizable capturing methods are suggested to implement the approaches and a tool is created for each approach. Industry feedback and preliminary findings show the feasibility of the proposed approaches.