Connected car software devkit uses Amazon Web Services for vehicular data acquisition

16 October 2018

Credit: Shutterstock
Credit: Shutterstock

Spurring the development of cloud-linked services that utilise vehicle data, Renesas have announced their Connected Car Software Development Tools, which are connected to Amazon Web Services.

Developers working with the R-Car system-on-chip family (R-Car being Renesas's automotive computing platform) can now create applications (such as predictive-safety), which link dynamic, real-time vehicle status information – using both the vehicle and Amazon Web Services' (AWS) cloud-based big data processing capabilities.

This enables out-of-the-box development of innovative applications, instead of the traditional approach of simply connecting the vehicle to the cloud, to enable cloud services in the vehicle.

There are unique challenges in managing vehicle data and the need to develop applications under conditions where in-vehicle testing is challenging or impossible. It has therefore been difficult for software developers to leverage the rich cloud services that AWS provides, namely through vehicle data at the edge (consider the requirements of predictive driving support applications, for instance).

Renesas’s new software development toolset makes it possible to generate new services that combine, in real time, vehicle data (such as the driving status and the state of the drivers) and cloud-based data (for example, construction, congestion, or other road conditions), as well as weather reports and maps.

To link the cloud and the edge, Renesas have adopted AWS’s cloud services and the Greengrass for its software development tools. The software development tools have been validated by both AWS Greengrass and AWS IoT core and have been tested to run on the R-Car Starter Kit under Automotive Grade Linux environment.

Said Masayasu Yoshida, senior director of Automotive Technical Customer Engagement Division at Renesas: “As autonomous driving systems continue to advance, the connected vehicles expect more new key players and to become mainstream.

“To capitalise on the expertise in vehicle data control, we will continue to work closely with AWS, [which] holds enriched connected services and expertise in edge computing. We are confident that our AWS-linked new software development tools will serve as communication tools and be widely used in the connected vehicle industry.”

Credit: Shutterstock
Credit: Shutterstock

To quote Muneyuki Watanabe, director of Strategic Alliance & Partners/Channel, Amazon Web Services Japan K.K., moreover: “For automotive applications, AWS already provides the AWS IoT Framework for AGL [Automotive Grade Linux], which enables the integration of AWS IoT core and AWS Greengrass with AGL.

“I am delighted that Renesas’s new software development tools are providing visibility to vehicle data that could not previously be accessed and imported. We look forward to collaborating with Renesas to help AWS customers leverage these tools to develop new and innovative connected vehicle applications.”

Furthermore, scalability of such applications could be extended to enable coordination with additional data from driver monitoring. For example, predictive driving assistance can be realised, in which the application would make calculations based on data from the vehicle. This includes information on driver emergencies, driving skills, fuel, or tyre pressure, plus forecasts of weather or road conditions from the cloud – all determining the optimal route and/or providing coaching to the driver.

Realisation of the above new services will not only enhance convenience and safety for drivers, it will also help ‘mobility businesses’ (such as automakers, dealerships, insurance companies, and car rental agencies) to expand and provide more added value to customers. This leads to the acceleration of new businesses in the service layer and ultimately brings innovations – leading to a new age of mobility.

Footnote: Features of the connected car software development toolset

· A simulator that can generate vehicle data from the accelerator, brake pedals and the steering angle

· An edge controller that maintains the vehicle data

· A vehicle application programming interface that links with applications such as driver monitoring

· Interfaces that connect vehicle data to the cloud

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