Innovation in the connected vehicle

The automotive industry is undergoing a profound digital transformation. Since its inception, the bulk of a car’s value has been comprised of its mechanical, hardware, and other physical components, however software and connected services are quickly becoming the most important drivers of value, and a key differentiator, for automobile manufacturers as the industry looks to make its next great leap: digital standardization.

The next-generation vehicle architecture has evolved from being hardware-driven to software-defined. Software is now quite literally in the driver’s seat, steering the car industry and redirecting the way it has been organized since those halcyon days of Henry Ford—who famously remarked that customers could have any color they wanted so long as it was black.

 

Understanding the digital ecosystem

In recent years, app designers and programmers working on vehicles have faced a digital ecosystem without any semblance of standardization or strategic foresight.

Modern cars and trucks are built with thousands of parts from many different suppliers, with each vehicle model comprising a unique set of proprietary hardware and software components. These components, including an increasing variety of vehicle sensors, produce data in unique and specialized formats.

The highly specific skills required to interact with the data, as well as the challenges of accessing it from within contained vehicle subsystems, limit developers’ abilities to innovate quickly and bring new solutions to market.

The value of organizing this chaos and incompatibility cannot be overemphasized. What is most exciting is that the technology to address these issues already exists, and without having to take every existing car off the road for a redesign. This could significantly improve the process of tackling legacy issues and vulnerabilities in-vehicle software.

Traditionally, there has been a lack of contractual clauses assigning responsibility for addressing these quality defects. This meant that whenever an OEM (original equipment manufacturer) wanted to make a fix, it all too often became horrendously expensive. By standardizing how OEMs interact with different vehicles’ software, this process could be dramatically simplified.

As a result, a broader range of developer talent from outside the auto industry has the opportunity to contribute new in-vehicle features and services. Developers can build ML-powered capabilities and contextually aware, in-car experiences without requiring specialized automotive skills.

There is no need to worry about special automotive programming languages, hardware variations, or proprietary sensor data formats. Developers can design their application with in-car data and machine learning, and achieve scale by deploying it across multiple vehicle brands, makes, and models.

More generally, AI (artificial intelligence) and machine learning allow manufacturers to gain greater insights than thought possible even a few years ago. These technologies can provide a way to read vehicle sensor data, normalize it, and create actionable insights from that data—regardless of the different components.

 

Applications on the roadways

This new era for the industry is not just exciting for a select group of programmers. Rather, it presents a plethora of new opportunities and capabilities for automotive manufacturers to sell and consumers to enjoy.

Greater communication between a car’s components could offer new safety features. Vehicle sensors throughout the car including cameras and many others would be able to feed into a common processor in the car or the cloud that can build a more accurate picture of the conditions facing the car.

For instance, it could automatically detect icy conditions and enable relevant vehicle safety features such as traction control and advise the driver to reduce their speed.

The vehicle would also be able to interpret the behavior of the driver and passengers in the vehicle to provide a safer or more pleasant driving experience. By analyzing changes in human behavior such as handling and speed, cars could detect when the driver appears to be texting, distracted, or not observing speed limits. It would then alert the driver and prevent a potential accident.

Similarly, parents of infants could receive a reminder to engage the child safety lock when the vehicle detects a child in the rear seat.

In another example, drivers of electric vehicles could choose to share their car’s battery information with third-party charging networks to proactively reserve a charging connector and tailor charging time according to the driver’s current location and travel plans.

 

Efficiencies and maintenance

In addition to improving the tangible driving experience, connected cars would be able to gather and process data to create new insights into efficiency and maintenance.

For instance, by analyzing real-time performance data, automakers could recognize the first signs of potentially faulty parts, allowing them to diagnose and prevent total failures before they happen. This includes allowing developers to remotely deploy updates to vulnerable software, as well as alerting drivers to wear and tear detected in physical components.

Furthermore, the sensors in the car could detect the rate of deterioration in different parts and suggest ways to improve the lifespan of the vehicle. This could also apply to processes such as fuel usage; the car could advise more efficient driving speeds to reduce consumption and emissions.

Using machine learning algorithms to “score” driver behavior (acceleration, braking, steering, etc.), automakers also have the potential to create new usage-based insurance models. The data can then be shared with an insurance company (with the consent of the OEMs, insurance company, and owner) so that insurance premiums can more accurately reflect the number of miles driven and a driver’s behavior.

 

Looking ahead to the standardized future

Just as the use of universally compatible nuts and bolts opened a new era for cars at the turn of the twentieth century, data and connectivity are opening new avenues for innovation that will revolutionize the auto industry of tomorrow.

By standardizing the digital ecosystem in vehicles, automakers will be able to create a rich ecosystem of solutions that improve and enhance driver and passenger experiences and fundamentally change for the better the way we get from A to B and what we do in between.

The most exciting part of all this is that the technology to do exists today and the opportunity is within the industry’s reach.

 

Adam Boulton, Chief Technology Officer at BlackBerry Technology Solutions, wrote this article for Futurride. He has 15 years of experience within security engineering and serves as the Chief Architect for BlackBerry Jarvis, a revolutionary static binary analysis solution for safety and security-critical systems.