Overview
A leading OEM partnered with intive to develop a new software component for driver monitoring. The new assistant detects drowsiness and distraction, provides visual and acoustic warnings to increase safety, and complies with the new Vehicle General Safety Regulation (GSR).
Client
Leading OEM
Industry
Automotive
Services
Process-compliant development of a generic module that is rolled out as AUTOSAR components to different platforms. Establishment of integrated process and tool infrastructure for series projects.
Driving Compliance and Navigating Safety Standards
Safety is no longer just a feature - it's an essential obligation. With road accidents predominantly caused by human error, the pressing need to enhance driver safety measures has never been more evident. Moreover, as regulatory bodies continue to enact new safety standards, Original Equipment Manufacturers (OEMs) find themselves obligated to become compliant with constantly evolving and stricter-than-ever traffic regulations.
In early 2019, intive competed against major suppliers to develop a generic algorithm for driver monitoring that could be used in different platforms within the cars of a leading OEM. The challenge was clear: ensure compliance with Regulation (EU) 2019/2144 while retaining control over the development process. intive's longstanding partnership and proven track record in attention and drowsiness systems spanning 9 years as of 2019 made it the ideal choice for the leading OEM to partner with and initiate a new project. Since then, intive has been instrumental in guiding the OEM towards compliance, leveraging its expertise to meet regulatory requirements effectively.
Proven Automotive Tech Stack and Methodology
As the project progressed, the size of intive team was adjusted according to the needs of a given phase. The team started with 11 people in 2019 and increased to 60 FTEs by 2022. Only with this large and agile team was it possible to achieve the integration of a driver monitoring system into different car platforms.
In more than 60 sprints, the team developed a unique algorithm that they integrated into different AUTOSAR Software Components. In parallel, intive developed an offline, online, and cloud simulation environment to test the software outside the normal context of vehicle use. Developing measurement equipment and toolchains enabled the record and analysis of relevant driver and vehicle data during the development phase.
To achieve optimal results, intive ensured that the SW-Development was done according to Automotive SPICE and used the C programming language for Classic AUTOSAR Handcoded Development. Additionally, a systematic analysis and selection of the tool infrastructure played a crucial role in establishing a robust and proven development infrastructure.
Tools Used:
ALM-Solution Base
Codebeamer
Development Tools
Model Based Development: MATLAB Simulink/Stateflow
CodeGeneration: dSPACE TargetLink
Compiler
Tasking TriCore
Hitex ARM
GreenHills PowerPC
GreenHills TriCore
HighTec RT
Wind River
Testing and Verification
Parasoft DTP, C++ Test, Static Analysis
Piketek TPT
MES Model Examiner (MXAM)
Infrastructure
Jetbrains CI/CD
GitLab
Meeting Regulatory Deadlines and Ensuring Seamless Production
Throughout the project, intive consistently met the challenging timeline of the Vehicle General Safety Regulation (GSR), working closely with the customer to achieve homologation milestones. The project timeline was crucial to ensure that the customer could sell their cars as planned, and intive successfully met the deadlines, allowing for uninterrupted production on the client's end.
Moreover, intive's work was compliant with the EURO NCAP Vision Zero Statement Roadmap 2025, China NCAP, China Insurance Automobile Safety Index (C-IASI), as well as GB/T Standards. Additionally, the development process was conducted in strict accordance with A-SPiCE requirements (Automotive Software Process Improvement and Capability Determination), guaranteeing the highest quality of embedded automotive software development.
Interpreting the Level of Drowsiness
As the level of attention and drowsiness is a personal feeling, attempting to measure it can seem impossible without clear variables. intive approached this task by leveraging its years of experience, which proved to be crucial throughout the entire process. Previous verification projects enabled the team to gather the necessary know-how in the domain of driver monitoring. Analyzing terabytes of test drive data helped the team interpret the most important signals accurately and in the right way.
intive’s highly automated and optimized tools enabled the team to manage a variety of complex data and generate additional value for the leading OEM. The data mining in the predevelopment phase allowed the team to establish classifiers for drowsiness and attention loss detection.
Indirect recognition like the analysis of the steering behavior of the driver and their following of the road lines served as a basis to develop the correct application algorithm and distinguish fatigue, drowsiness, and distraction symptoms. Additionally, threat detection was possible with or without a driver monitoring camera and was supported by the existing vehicle sensor-set. Once the system identified a tired driver, it emitted visual and acoustic HMI warnings to ensure safety.
Smartly Improving Road Safety
By developing a completely new software component for driver monitoring that is compatible with different car platforms, intive improved the leading OEM’s road safety methods. The unique algorithm detects not only short-term and long-term drowsiness and distraction, but also complies with new road laws and regulations, as required for the sale of new cars from 2022 onwards. For cars sold before 2022, this rule will also apply, but from 2024 onwards.
Additionally, intive's expertise made it possible to meet all the requirements set for automotive software development companies and contributed to the overall improvement of road safety. The applied fatigue detection improves the safety of drivers, passengers, pedestrians, and other road users, thus reducing the number of accidents on the roads.
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