Author: Gary Hilson
Businesses looking to take advantage of edge computing in autonomous vehicles must first understand how multi-access edge computing (MEC) can benefit their business to fully leverage the benefits of future automotive edge computing.
Today, the connected vehicle is part of the fabric of commercial Internet of Things (IoT) deployments. Although edge computing in autonomous vehicles relies most on publicly available connectivity, businesses looking to deploy their own autonomous fleet may want to look at IoT solutions based on private 5G and MEC to maximize cellular vehicle-to-everything (C-V2X) applications such as vehicle, pedestrian, and road safety, as well as features that securely contribute to their business.
5G enables edge computing in autonomous vehicles
Before hitting the road, it's important to understand how 5G helps enable IoT and edge computing infrastructures that support autonomous vehicles.
The capabilities of 5G could be critical to IoT performance and functionality. It's a faster network with higher capacity and low latencies that can serve the needs of emerging use cases such as automotive edge computing. 5G cellular networks, with their expanded bandwidth and low lag, allow the types of fast data transfers that are the foundation for the implementation of edge computing-assisted autonomous vehicles. Connected cars are IoT endpoints that, along with cloud-connected traffic management and other applications, depend on near-instantaneous responses and data analysis.
MEC also plays an important role in processing road and driving information in near real time. It brings technology resources closer to the end user and businesses closer to their own autonomous fleets. Rather than sending data all the way back to a central, sometimes distant data center, data is processed and stored at the network's edge to further reduce latency. MEC also provides an IT service environment and cloud computing capabilities that enable developers to build applications for wireless edge devices, including autonomous vehicles.
MEC moves automotive edge computing forward
There are many MEC-enabled applications in development that enhance edge computing in autonomous vehicles and increase vehicle efficiency. Groups like the Automotive Edge Computing Consortium (AECC) often have a hand in pushing applications forward.
Consortium researchers see MEC enabling emerging services such as intelligent driving, which leverages maps with real-time data and driving assistance based on cloud computing. To use the technology vehicles must be connected to the cloud over networks that can transfer large amounts of data.
Edge computing in autonomous vehicles means every car, truck and bus on the road can become a repository of data. This allows for mobility as a service, where data can be used by third parties to offer services such as route guidance for travelers, ride sharing and providing information that can guide traffic flow control by road authorities. Other data generated by automotive edge computing could allow finance and insurance companies to engage with customers; insurers could offer usage-based coverage by monitoring driving behavior to assess risk and adjust rates.
Most of all, MEC allows for more diverse connectivity, including radio access technologies as various wireless technologies, including cellular and local radio access such as Wi-Fi and low-power wide-area (LPWA), that will connect a vehicle with distributed computing platforms.
Private MEC powers automotive edge computing
Autonomous vehicles mostly rely on public MEC because they typically roam outside the coverage of private area networks, but businesses serious about deploying their own commercial autonomous fleets need to consider the value of a private MEC infrastructure. Private MEC solutions can provide expanded coverage, which has currently been the main hindrance for applications on autonomous vehicles.
Private MEC can provide enhanced security and efficiency, especially if it leverages C-V2X. Businesses that want near real-time insights, decision-making and operations should consider a MEC solution that's integrated with a private 5G network because it provides enterprises with a secure and dedicated computing platform necessary for MEC-enabled applications that can enhance edge computing in autonomous vehicles.
Private MEC solutions are already used by logistics and supply chain companies to help automate and improve quality control processes through computer vision. High-definition cameras connected to a 5G network allow for the monitoring of product pick-and-pack lines so errors can be detected and corrected in near real time. The same latency and ability to perform near real-time data analysis and delivery could help power granular autonomous fleet management.
By using a private MEC solution, businesses have far more control over network performance to prioritize and secure specific kinds of data for added efficiency. A private MEC is further enhanced by C-V2X, which commonly uses the 5.9 GHz frequency band to communicate. This band has been officially designated the intelligent transportation system (ITS) frequency in most countries and uses 3GPP standardized 5G mobile cellular connectivity to send and receive signals from a vehicle to other vehicles, pedestrians, or to fixed objects, including traffic lights. With a range that exceeds more than a mile, C-V2X can function without network assistance.
Although a private edge computing solution that integrates 5G C-V2X offers many benefits to businesses looking to enhance edge computing in autonomous vehicles, deploying them comes with its own set of challenges, regardless of what they're for.
- MEC requires real estate, and that becomes complicated when edge computing gets closer to the user.
- Autonomous vehicles need larger geographic availability to utilize edge data.
- Edge computing solutions require power as the necessary data centers need dual sources for redundancy and resiliency.
These edge data centers may also need to be set up in less-than-ideal locations and environments, and each one will need access to fiber networks to provide the backhaul connectivity. These small MEC data centers will also have their own operations challenges, and given their distributed nature, they will have to be as hands-off as possible while still being monitored and secured.
Like with network deployments, 5G-enabled MEC that leverages C-V2X requires planning, expertise, and ongoing management support. For businesses looking to make the most of edge computing in autonomous vehicles, it's worth partnering with a service provider who can provide the private MEC infrastructure they need to propel them forward.
Learn more about how Verizon is supporting 5G connectivity for autonomous vehicles.
原文：https://www.verizon.com/business/resources/articles/s/edge-computing-in-autonomous-vehicles/
