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The application of Model-Based Development (MBD) techniques for automotive control system and software development have become standard processes due to the potential for reduced development time and improved specification quality. In order to improve development productivity even further, it is imperative to introduce a systematic Verification and Validation (V&V) process to further minimize development time and human resources while ensuring control specification quality when developing large complex systems. Traditional methods for validating control specifications have been limited by control specification scale, structure and complexity as well as computational limitations restricting their application within a systematic model-based V&V process. In order to address these issues, Toyota developed Hierarchical Accumulative Validation (HAV) for systematically validating functionally structured executable control specifications.

This paper describes the development and achievement of a target engine sound for a V6 SUV in consideration of the sound quality preferences of customers in the U.S. First, a simple definition for engine sound under acceleration was found using order arrangement, frequency balance, and linearity. These elements are the product of commonly used characteristics in conventional development and can be applied simply when setting component targets. The development focused on order arrangement as the most important of these elements, and sounds with and without integer orders were selected as target candidates. Next, subjective auditory evaluations were performed in the U.S. using digitally processed sounds and an evaluation panel comprising roughly 40 subjects. The target sound was determined after classifying the results of this evaluation using cluster analysis.

A method for predicting body deformation during operation, which cannot be measured by conventional methods, has been developed. The method creates a body model based on the characteristics extracted by modal analysis of the results of a vibration testing of an actual vehicle. The model is combined with a suspension model, using multibody dynamics software, and body deformation calculations are performed. In this paper, the influence of body deformation on vehicle controllability and stability is studied and the usefulness of the method is verified.

Recently, the role of ECU(Electronic Control Unit) on vehicles has been becoming more important year by year in order to meet the requirements for safety and the environmental matters. Particularly, the ECU of Engine Management Systems has been becoming indispensable in order to realize high performance, low fuel consumption and low exhaust emission. Therefore, the size of software has also been increasing, and been becoming more complex and complicated. As the ECU software size becomes large and complex, the verification and validation of the software by using the current development method has been becoming more difficult. Especially it has been becoming more difficult to validate the Real-time property of the software. The Real-time property means whether the execution of the software is in time for the deadline which is decided on the software design.

Test and verification procedures are a vital aspect of the development process for embedded control systems in the automotive domain. Formal requirements can be used in automated procedures to check whether simulation or experimental results adhere to design specifications and even to perform automatic test and formal verification of design models; however, developing formal requirements typically requires significant investment of time and effort for control software designers. We propose Signal Template Library (ST-Lib), a uniform modeling language to encapsulate a number of useful signal patterns in a formal requirement language with the goal of facilitating requirement formulation for automotive control applications. ST-Lib consists of basic modules known as signal templates. Informally, these specify a characteristic signal shape and provide numerical parameters to tune the shape.

Automotive control systems such as powertrain control interact with the open physical environment, and from this nature, expensive prototyping is indispensable to capture a deep understanding of the system requirements and to develop the corresponding control software. Model-based development (MBD) has been promoted to improve productivity by virtual prototyping. Even with MBD, systematic validation of the software specification remains as a major challenge and it still depends heavily on individual engineers' skill and knowledge. Though the introduction of graphical software modeling improved the situation, it requires much time to identify the primal functions, so-called “design interests”, from a large complex model where irrelevant components are mixed with, and to validate it properly.

There are various standards to evaluate the quality of software. Tools to quantatively evaluate the quality of software have become available in recent year. Although these tools are effective, warning reports can become extensive, when the volume of software becomes large. And, the manpower to confirm the report also becomes large. Knowledge and experience are to analyze the warning report. Consequently, an oversight, a misapprehension, etc. may arise. To solve this problem, we are examining system to automate this work.

Teammate Advanced Drive is a driving support system with state-of-the-art automated driving technology that has been developed for customers’ safe and secure driving on highways based on the Toyota’s Mobility Teammate Concept. This SAE Level 2 (L2) system assists overtaking, lane changes, and branching to the destination, in addition to providing hands-free lane centering and car following. The automated driving technology includes self-localization onto a High Definition Map, multi-modal sensing to cover 360 degrees of the surrounding environment using fusion of LiDARs, cameras, and radars, and a redundant architecture to realize fail-safe operation when a malfunction or system limitation occurs. High-performance computing is provided to implement deep learning for predicting and responding to various situations that may be encountered while driving.

As vehicle control software becomes larger and more complex, it is increasingly important to improve the efficiency of the software development process. This study developed search-based testing technology to increase the efficiency of the validation process. Search-based testing can generate dynamic test data automatically, but it tends to overlook the generation of correct test data to detect problems when the software has many branches and paths. To resolve this problem, a method was devised that combines search-based testing [1] and formal methods such as model checking. This paper describes this method and shows application examples of engine control.

Reductions of hardware costs as well as implementations of new innovative functions are the main drivers of today's automotive electronics. Indeed more and more resources are spent on adapting existing solutions to different environments. At the same time, due to the increasing number of networked components, a level of complexity has been reached which is difficult to handle using traditional development processes. The automotive industry addresses this problem through a paradigm shift from a hardware-, component-driven to a requirement- and function-driven development process, and a stringent standardization of infrastructure elements. One central standardization initiative is the AUTomotive Open System ARchitecture (AUTOSAR). AUTOSAR was founded in 2003 by major OEMs and Tier1 suppliers and now includes a large number of automotive, electronics, semiconductor, hard- and software companies.

In recent vehicles, E/E architecture is defined and used as a platform to accommodate various electronics features for better development efficiency, lower cost and higher quality. As electronics features increase and integrated control systems make vehicle electronics more complex, good electronics platforms are vital for today's and future vehicle development. This paper first describes the evolution of vehicle electronics and its recent trend and then addresses the challenges facing vehicle electronics: ✓ More integrated control systems ✓ More software ✓ More networks ✓ Shorter time to market Finally, why JasPar1), Japan Automotive Software Platform and Architecture, was founded and how it is organized will be described including the working group activities on FlexRay implementation.

This paper describes a design tool and a software platform for FlexRay systems that are investigated in Nagoya University and are proposed to JasPar. The design tool reads the specification of a system as a task graph that consists of a set of tasks and messages among them. The design tool, then, allocates the tasks to ECUs and schedules the messages on a FlexRay network. The software platform consists of a middleware called time-trigger module (TTM) which dispatches time-triggered tasks, a communication middleware for a time-triggered network (TT-COM), a network management middleware for FlexRay (FlexRay-NM), and a device driver for FlexRay controller.