To spur the development of cloud-linked services using vehicle data, Renesas Electronics Corporation, a supplier of advanced semiconductor solutions, makes available its Connected Car Software Development Tools. Using the new tools, developers working with the R-Car system-on-chip (SoC) family can create applications, such as predictive safety infotainment applications that link dynamic data from the vehicle and the cloud in real time with algorithms developed based on big data in the cloud. This enables out-of-the-box development of innovative applications instead of the simply connecting the vehicle to the cloud, making cloud services available in the vehicle.
Due to the challenges of managing vehicle data and the need to develop applications under conditions where in-vehicle testing is difficult or impossible, it has been difficult for software developers to leverage the rich cloud services that Amazon Web Services (AWS) provides through vehicle data at the edge, such as predictive driving support applications. Renesas’ new software development toolset enables generation of new services that combine, in real time, vehicle data (e.g., the driving status and the state of the drivers) and cloud-based data (e.g., construction, congestion or other road conditions) as well as weather reports and maps.
To link the cloud and the edge, Renesas has adopted AWS’ 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.
“As autonomous driving systems continue to advance, the connected vehicles expect more new key players and to become mainstream,” says Masayasu Yoshida, senior director of Automotive Technical Customer Engagement Division at Renesas. “To capitalize on the expertise in vehicle data control, we will continue to work closely with AWS that holds enriched connected services and expertise in edge computing.”
“For automotive applications, AWS already provides the AWS IoT Framework for AGL, which enables the integration of AWS IoT core and AWS Greengrass with Automotive Grade Linux (AGL),” says Muneyuki Watanabe, director of Strategic Alliance & Partners / Channel, Amazon Web Services Japan K.K.
Scalability of such applications could be extended to enable coordination with additional data from driver monitoring. For example, predictive driving assistance can be realized in which the application would make calculations based on data from the vehicle, such as information on driver emergencies, driving skills, fuel, or tire pressure, plus forecasts of weather or road conditions from the cloud, and determine the optimal route or provide coaching to the driver.
Sources: Press materials received from the company.
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