The Role of Edge Computing in Autonomous Vehicles
Experion Technologies
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Today we live in a connected ecosystem, be it connected buildings, connected factories, or connected vehicles. The automotive industry is undergoing rapid transformation and edge computing plays a big role in this change. The transportation system is taking a rapid shift from being a traditional technology-driven system into a more potent data-driven system as a result of advancements in technology that include new sensors and enhanced data processing and control.
According to Gartner, 470 million connected vehicles will hit the roads by 2025. Adding to this, effectively processing and using huge amounts of data with existing communication networks can be a challenging task. Let’s have a look at how edge computing helps smoothen the process.
What is Edge Computing?
Edge computing consists of data storage, management, and analysis, allowing real-time data processing, which enables devices or vehicles to react to data instantly. This is a distributed form of computing in which all the operations takes place on a device, such as a robot or autonomous vehicle. This makes it an effective and fast-track computing process, reducing the need to manage data back and forth from the cloud.
Use cases of Edge Computing in Automotive
A wide range of automotive sub-systems, from sensors to apps to the end-user experience, can benefit from edge computing. Let's explore some of the most important potential applications of edge computing in the automotive industry.
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Sensors are now embedded in all smart devices, be it motion sensor lights or smoke sensors in smart buildings. The same algorithm is applied to autonomous vehicles too. A smart car works with the help of many sensors. Even though all of the generated data is processed in the vehicle, numerous in-car applications necessitate the transport of data to the cloud. Edge computing helps process and control the data at the edge, transferring very fewer data to the cloud, thus bringing down the data transmission cost for the user.
Today, we have some experience of V2X communications in the vehicles that we drive, however the full potential of it is yet to be seen. In simple terms, Vehicle-to-everything, or V2X, means a vehicle’s connected communications. It refers to any communication that takes place between the vehicle and any other surrounding object. More and more autonomous driving applications are starting to use V2X communications to increase the effectiveness of the in-vehicle edge computing system as a result of the rapid deployment of edge computing facilities in road infrastructure.
Battery monitoring and predictive maintenance are the two most essential things about electric cars. Therefore, the battery must be continuously monitored and maintained with the help of predictive maintenance. There are a lot of factors affecting the battery’s condition, such as way of driving, charging timings, traffic congestion, speed limit etc. All of this data can be combined by edge computing, enabling to check the critical battery characteristics in real-time and notify the owner of the car if there are any deviations. Key battery characteristics and sensor data could be aggregated using edge computing in real-time monitoring. Auto OEMs and network providers, particularly in the electric car market, can directly impact the customer experience by utilizing edge computing.
There is little doubt that intelligent vehicles, especially autonomous vehicles, will disrupt numerous economic sectors and drastically affect our daily lives. The adoption of edge computing in the automobile industry is tremendous. It's time to consider how you and your company may benefit from edge computing in the future.