How to enable software-defined cars?

In the rapidly evolving world of automotive technology, software is taking center stage. Software-defined vehicles (SDVs) offer a future of highly customizable features, over-the-air updates, and personalized experiences. However, this shift brings with it a surge in vehicle data that must be managed effectively in real time.

McKinsey said: “By 2030, around 95% of new cars sold worldwide will be connected, up from around 50% today. Given the many benefits that car data brings, even players with lower levels of connected vehicles can start paying attention to data.”

ITTIA has created a solution to address the challenges of in-vehicle device data management, enabling automotive OEMs to unleash the full potential of this revolution. ITTIA DB enables real-time data collection, processing and calculation from in-vehicle devices.

Benefits of SDV Data Management

SDVs generate unprecedented amounts of data from numerous sensors, ECUs (electronic control units), and connected systems. OEMs and Tier 1 suppliers are seeking options to modernize their traditional data management approaches to handle such large volumes of data. They want flexible data management options to consistently embed, deploy, and run applications on independently embedded devices within the vehicle and own their own data. Let’s look at some of the advantages that in-vehicle data computing brings:

Latency: Critical applications such as ADAS (Advanced Driver Assistance Systems) require lightning-fast decision making. Sending data to the cloud for processing adds unacceptable latency

Compliance with standards: The highly regulated nature of the automotive industry requires strong automotive product development practices to ensure compliance with a complex web of standards and regulations

Bandwidth and cost: The continuous transmission of large amounts of data will incur significant bandwidth costs and put pressure on communication networks.

Security and privacy: Car data is highly sensitive, and over-reliance on cloud connectivity increases the risk of data breaches and privacy issues

Data ownership: OEMs and/or Tier 1 suppliers must own the data from its generation and collection to its storage, analysis and possible deletion

Additionally, gaining insights quickly is a major challenge for SDV architectures because in-vehicle devices must be intelligent. There is a direct correlation between intelligence and data management, and in order to conduct data management activities to enhance competitive advantage and automate devices, data processing needs to be run inside vehicle devices. As with the Internet of Things, sensors, data sources, and devices in the car generate a large amount of raw data, most of which is useless on its own. Modern technologies such as ITTIA DB enable these devices to transform raw data into usable information through data stream processing and query capabilities so that embedded systems can gain insights and understanding of the system. As a result, applications embedded with ITTIA DB devices can choose how to collect, process, analyze, and store or transmit valuable information.

This support enables OEMs and Tier 1 suppliers to quickly build data-sensitive applications while maintaining strict control and ownership of the data within the device.

In the SDV era, sensors capture and transmit massive amounts of time-series data, turning cars into smart machines. Time series data contains a series of measurements or events that fluctuate over time, and they are tracked and monitored. In-vehicle data management software, such as the time series database ITTIA DB, is designed to filter, downsample, and aggregate time-stamped data, and then store the results on each device. As a result, data about the current state, trends, and past patterns of the system can be easily retrieved. The application can also manage concurrent inputs, enabling SDV devices to store and process large data streams simultaneously and help with integrated analysis.

The combination of time series storage and stream processing allows efficient indexing of data using timestamps; the timestamp linked to each data item is used as the primary input for computation. In addition, time series data from connected devices in the car form a data stream that is continuously collected and flows into the database. As a result, the overall data flow remains stable while the devices perform instantaneous data computations.

Key use cases for time series data management and streaming embedded in SDV

The ability to securely process large amounts of data in real time helps address a variety of automotive-specific use cases including:

Predictive maintenance: Collects and analyzes data from ECUs to identify wear patterns and predict component failures, enabling timely and cost-effective maintenance

ADAS Optimization: Local storage and processing of sensor data enhances ADAS features such as obstacle detection, lane departure warning, and adaptive cruise control

Personalized driving experience: Securely stores driver preferences and usage behavior on board, providing customized settings for seats, infotainment and climate control

Over-the-air (OTA) updates: Manage and track software versions and dependencies across ECUs for seamless, reliable software updates

Fleet Management and Learning: Enables selective sharing of insights from ITTIA database instances across vehicles to optimize fleet performance and train more powerful AI/ML models

Being able to collect and analyze real-time data from in-vehicle devices enables manufacturers to optimize SDV designs. When devices aggregate, analyze, and prepare data from sensors, vehicles are able to benefit from granular data to improve reliability. As a result, they can build applications to predict when components are likely to fail. Processed data enables OEM and Tier 1 supplier applications to benefit from it to perform maintenance before failure occurs, thereby reducing the risk of accidents and improving vehicle reliability. ITTIA DB provides tremendous value in real-time data management performance, optimized storage, strong security, and adaptability to automotive SDV platforms.