Autonomous Vehicles have gained significant attention in recent years. However, the underlying technologies that support them, including 5G and digital infrastructure are less understood. This in-depth look contains cutting-edge information from an industry that is going through immense change and will have a profound impact on our world. Autonomous vehicles are also known as self-driving cars, autonomous cars, driverless cars or robot cars. Below, we discuss the:
- Leaders in autonomous vehicles
- Levels of advanced driver-assistance systems (ADAS) and autonomous driving
- Key underlying technologies of autonomous vehicles, including 5G
- Main ways that 5G is acting as an enabling technology for the development of autonomous vehicles
- Initial use cases of 5G in autonomous vehicles
- Greater need for digital infrastructure as autonomous vehicles and 5G develop further
Leaders in Autonomous Vehicles
Successful leaders like Elon Musk at Tesla and innovative companies like Google are working on autonomous vehicles today. Ultimately, they are shaping where the world is going in the future. Below are some of the key companies leading in autonomous vehicle development:
Tesla has leadership in electric vehicles, the connected car, over-the-air software, and electric vehicle infrastructure. Indeed, these are all enabling technologies that have strategic value for autonomous vehicles.
Most auto makers, suppliers and technology enablers involved in autonomous vehicles describe Tesla as by far the most advanced automotive company in operation, at scale. Furthermore, Tesla is training and improving its neural network on all of the vehicles in its fleet, by collecting data from each vehicle.
Alphabet (formerly Google): Waymo
Alphabet, through Waymo One, is a self-driving taxi service that operates in Phoenix, Arizona. Waymo also has a partnership with ridesharing company Lyft, making some of its self-driving minivans available for customers in Phoenix, Arizona.
Additionally, Waymo operates a self-driving truck fleet, which is branded as its Waymo Via service.
Uber: Advanced Technologies Group
Through its Advanced Technologies Group, Uber is expanding into autonomous driving. The company has a number of partnerships with technology firms (including Nvidia) and auto makers (including Daimler, Toyota, and Volvo). Additionally, Uber is using autonomous technology within its Uber Freight division, which matches carriers with shippers.
Overall, Uber’s goal is to create a hybrid network of traditional and autonomous vehicles, reaching Level 4 (discussed below) fleet deployment.
General Motors: Cruise
Cruise is working to commercialize a robotaxi service, and plans to begin testing in San Francisco in late 2020. The company is majority owned by General Motors, with other investors that include SoftBank, Honda and T. Rowe Price.
Aptiv: Autonomous Mobility
Aptiv, through its Autonomous Mobility unit has the largest autonomous commercial mobility service. The company owns a fleet of 75 autonomous vehicles and has amassed over 100k paid rides. Aptiv mainly operates in Las Vegas, Boston, and Pittsburgh, within the United States. Additionally, Aptiv also operates internationally in Singapore, and China.
Aptiv has a partnership with ridesharing company Lyft, with 30 vehicles on the Lyft network, which have, in aggregate, travelled 1 million miles. Finally, Aptiv also has a partnership with auto maker BMW.
Argo AI (Ford and Volkswagen)
Argo AI’s goal is to deliver Level 4 (discussed below) capable autonomous vehicles for ridesharing services in dense urban areas. The company is backed by Ford and Volkswagen, and uses the Ford Fusion for its testing. Finally, Argo has plans to deploy commercial services in Miami and Washington, D.C. by 2021.
Apollo, which is owned by Chinese technology company Baidu, is trialing fully automated driving. Specifically, the company has carried over 100k passengers across 27 cities around the world.
Autonomous Vehicles – Levels
Autonomous driving can be classified into six different levels, from traditional vehicles being Level 0 to fully autonomous vehicles being Level 5.
Level 0 (Traditional Vehicle)
Represents vehicles in existence currently where a human is in full control of the vehicle at all times. Level 0 vehicles may incorporate early warning systems or an intervention system.
Level 1 (ADAS Vehicles)
Represents vehicles where steering, braking, and acceleration are augmented by a driver assistance system. However, a human performs all critical driving tasks. Examples of Level 1 features include adaptive cruise control (acceleration / deceleration), emergency braking and lane correction.
Level 2 (ADAS Vehicles)
Represents vehicles where steering, braking, and acceleration are done by a driver assistance system. But a human must monitor the system at all times and performs all remaining aspects of the dynamic driving task. Examples of Level 2 features include adaptive cruise control (acceleration / deceleration), steering and self-parking.
Level 3 (Conditional Autonomous Vehicle)
Autopilot performs the driving task under defined circumstances, such as low speed traffic jams. Furthermore, a human driver does not have to monitor the system at all times. However, a human driver is required to respond if there is a request to intervene and thus drive the vehicle.
Level 4 (Highly Autonomous Vehicle)
Autopilot performs the driving task under defined circumstances, such as low speed traffic jams and urban driving. Furthermore, a human driver is not needed and the system will run automatically. Therefore, the vehicle will react to an event, even if a human driver is not available to respond when requested.
Level 5 (Fully Autonomous Vehicle)
Driving task is solely performed by autopilot in all roadway and environmental conditions. Humans act only as passengers and therefore, no humans are required for vehicle operation.
Data Consumption by Autonomous Vehicles
Data Consumed Increases as the Level of Autonomy Increases
As vehicles increasingly shift from Level 1 to Level 5 autonomy, more decision-making capability will be given to the vehicle. In turn, the data consumed by the vehicle will increase, as the level of autonomy increases, because it has to make more decisions. Specifically, Level 1 vehicles consume 3 gigabytes per hour, whereas Level 5 vehicles consume 50 gigabytes per hour. Indeed, Level 5 vehicles consume almost 17 times more data than Level 1 vehicles.
Overall, autonomous vehicles will transmit data totaling 3,500 Exabytes by 2050. For context, 3,500 Exabytes is equivalent to 40x current global wireless data traffic.
Autonomous vehicle data is typically transferred back-and-forth using various sensors across the vehicle. Sensors include cameras, radar, and LiDAR (i.e., Light Detection and Ranging). As the level of automation increases, the number of sensors increase in tandem. For example, Waymo, which is targeting Level 4 and Level 5 autonomy, is using 8 cameras, 3 lidars and 5 radars in its vehicles.
Autonomous vehicles consume three data stream types, via their sensors and onboard computer:
- Navigation: data capture by several sensors, including LiDAR, radar, cameras, sonar, and maps. Autonomous vehicles use this data for real-time updates of maps applications.
- Telematics: component sensors. Autonomous vehicles use telematics for real-time updates of car diagnostics and to provide over-the-air software updates.
- Infotainment: includes video streaming (e.g., high-definition video content on Netflix), audio streaming, web browsing and sending e-mails.
Autonomous Vehicles – Technical Standards
Two Mobile Technical Standards are Used in Autonomous Vehicles:
- Cellular Vehicle-To-Everything (C-V2X): standard is peer-to-peer and leverages wireless networks, including 4G, LTE Advanced, and increasingly 5G.
- Dedicated Short Range Communication (DSRC): standard is peer-to-peer and does not require the use of traditional cellular networks. Instead, vehicles connect directly with other vehicles, in a similar way to Wi-Fi and Bluetooth technology.
Cellular Vehicle-To-Everything (C-V2X) is the dominant standard for autonomous vehicle technology. Therefore, Cellular Vehicle-To-Everything (C-V2X) will be the focus of this article.
Cellular Vehicle-To-Everything (C-V2X) – Overview
Cellular Vehicle-To-Everything (C-V2X) will allow autonomous vehicles to connect to the network and transmit data. This mobile standard has sub-groups as follows:
V2V technology connects a vehicle with other nearby vehicles, allowing vehicles to communicate with each other. The purpose of this platform is to transmit real-time data around driving patterns and relative positioning between vehicles. Specifically, V2V use cases focus on sharing video amongst connected vehicles, to enable a better view of what is occurring around the vehicle. Additionally, the underlying technology for V2V is the Internet of Things communication.
Example Use Cases of V2V include:
- Collision avoidance safety systems, such as emergency electronic braking
- Identifying slow or stationary vehicles
- Warnings for events including traffic jams and road work ahead
V2I technology connects vehicles directly with urban infrastructure (e.g., road, traffic signs, lights). The purpose of this platform is to transmit accurate, real-time data about the current state of infrastructure. For example, this includes the width of the road and if any turns are coming up. Furthermore, V2I can provide information on whether a particular road is one-way or two-way, and the status of traffic light signals. Similarly, the underlying technology for V2I is the Internet of Things communication.
Example Use Cases of V2I include:
- Weather condition information
- Intersection safety assessment
- Traffic signal priority requests (e.g., police car, ambulance, or fire truck)
V2N technology connects the vehicle with the rest of the world through the use of the cellular network. Specifically, 5G wireless networks, can support the transmission of any type of data. Indeed, the underlying technology for V2N is therefore, cellular communications.
Example Use Cases of V2N include:
- Infotainment (e.g., video, gaming, business discussions)
- Real-time traffic and routing, including 3D mapping
- Connection to cloud and edge services
V2P primarily allows for safety alerts to be sent to pedestrians and cyclists from vehicles.
Autonomous Vehicles – 5G Implications
In 2G and 3G wireless technologies, the automotive industry with its established manufacturers, supply chains and technology systems did not have much of a partnership with telecommunications. However, in 4G, the automotive supply chain and technology systems of the vehicle began to be disrupted by cellular technology, with the introduction of telematics, connecting the vehicle to the Internet.
In 5G, user experience, including the way in which users drive the vehicle, service the vehicle, and interact with the vehicle is now being framed by an experience akin to that of the smartphone.
Commitment of Technology Licensees and Automakers
In the 4G period, during 2013 to 2014, only two technology licensees (LG and Gemalto) developed Cellular Vehicle-To-Everything (C-V2X) services. Additionally, only two automakers (General Motors and Audi) launched Cellular Vehicle-To-Everything (C-V2X) services.
In comparison, 5G has 8 technology licensees developing and more than 18 automakers working on launches. Specifically, automakers are targeting 2021 to 2023 for their launches of C-V2X services, with 5G. The change in the commitment of these companies underscores the tremendous momentum with 5G technology.
5G is an Enabler of Autonomous Vehicles
Below we highlight a few notable points from our prior article titled “Explaining the Key Differences Between 4G and 5G“, which explains the key differences of 5G from 4G wireless technology.
5G Offers a Number of Step-Function Improvements from 4G, which are Critical to Autonomous Vehicles
- Lower Latency: 5G networks deliver 5x to 10x lower latency vs. 4G
- Increased Speed: 5G speeds have the potential to reach 10 gigabits per second, which compared to 4G could be 100x faster
- Higher Density (# of Connected Devices): 5G has the ability to support 10x as many connected devices per square kilometer of network vs. 4G
- Added Capacity (Network Throughput): 5G will increase network throughput, which is the amount of data that goes through a tower cell site, by 100x
- Energy Efficiency: 5G allows for only 10% of the current energy consumption experienced in 4G networks. Therefore, this translates into energy efficiency of 90%
Spectrum Used for Vehicle-to-Vehicle Networks
Allocation of clean spectrum to Cellular Vehicle-To-Everything (C-V2X) is important to allow the technology to function safely, where vehicles can communicate with each other in an undisturbed frequency. Above all, the goal for C-V2X is to have a global harmonized chunk of spectrum in the 5.9 GHz band.
As seen below, most countries have allocated high-bandwidth spectrum, using the 5.9 GHz spectrum band, for dedicated vehicle-to-vehicle communications.
In the United States, the Federal Communications Commission (FCC) has reserved one block of 75 MHz in the 5.9 GHz spectrum band to be used by intelligent transportation.
The European Telecommunications Standards Institute (ETSI) allocated a block of 30 MHz in the 5.9 GHz spectrum band for Intelligent Transportation Systems. Furthermore, the European Commission is pushing for technology neutrality in the 5.9 GHz band.
China is a leader in Cellular Vehicle-To-Everything (C-V2X) technology and has already made it their preferred standard. Specifically, China has allocated a 50 MHz block in the 5.9 GHz spectrum band. Further, China has ongoing pilot trials for a soft launch in progress.
For autonomous vehicles, Japan has uniquely allocated both low-band and mid-band spectrum. Specifically, Japan has allocated a 9 MHz block in the 700 MHz spectrum band and an 80 MHz block in the 5.8 GHz spectrum band.
Finally, South Korea has allocated a 70 MHz block in the 5.9 GHz spectrum band.
Roadside Infrastructure for Cellular Vehicle-To-Everything (C-V2X)
Once a global standard for spectrum is established, C-V2X needs to establish the infrastructure capable of facilitating communication. This infrastructure can take the form of roadside units, which have built-in cameras and sensors.
As an example, these roadside units can serve the purpose of identifying when road work is ongoing. Information on ongoing road work, will be broadcast over the C-V2X system. In turn, all vehicles on the road will be notified of the road work.
Overall, the goal of this infrastructure is to allow the roads to communicate with the vehicles. Therefore, reliance does not have to be placed on solely vehicle-to-vehicle communications to identify changes in road or driving conditions.
Autonomous Vehicles Use Cases Powered by 5G
Cellular Vehicle-To-Everything (C-V2X) – Use Case #1
5G innovations are driving accelerated improvements and comprehensive system integrations for automotive applications. Specifically, there are over 100 million vehicles currently on the road with 4G/LTE and 5G modems. These systems support automotive trends in telematics, infotainment, advanced driver-assistance programs (ADAS) & autonomous driving, and cloud mobile solutions.
Examples of Autonomous Vehicles Using the 5G Network
- Cellular Vehicle-To-Everything (C-V2X): which includes Vehicle-to-Vehicle (V2V), Vehicle-to-Infrastructure (V2I), Vehicle-to-Network (V2N) and Vehicle-to-Pedestrian (V2P).
- Auto Maker OEM Services: over-the-air software updates, upgrades, and packages.
- Precise Positioning: lane-level accuracy anywhere, anytime, using the Global Navigation Satellite System (GNSS).
- Connectivity for Passengers: content downloaded for the vehicle’s high-resolution multi displays, including video, premium audio, 3D maps and personalization settings.
Cellular Vehicle-To-Everything (C-V2X) platforms help vehicles communicate with each other and everything around them. Furthermore, C-V2X platforms help provide 360-degree, non-line-of-sight awareness and a higher level of predictability for improved road safety and features that will be used for autonomous driving. Two specific examples of the benefits of Cellular Vehicle-To-Everything (C-V2X) are the following:
Collision Avoidance – Initial Benefit of C-V2X
Autonomous vehicles can connect to their environment through V2V, V2I and V2P communications, over the 5G network. This is particularly important for latency-sensitive or data-intensive use cases, such as collision avoidance. C-V2X will be a technology that can save over 1 million lives, in the coming decades by helping to fix minor driving mistakes, that could have severe consequences.
As an example, when one vehicle is not using its blinker on a highway and decides to change lanes to the left, while another vehicle in that left lane is deciding to switch lanes to the right, at the same time. Through C-V2X, both vehicles will know the consequence of making that lane change and will stop the vehicles from changing lanes, avoiding a collision.
Sensor Sharing – Initial Benefit of C-V2X
Sensor sharing will allow transportation to become more efficient, through deeper coverage, by connecting vehicles to dense road infrastructure (e.g., sensors and traffic cameras) over the 5G network. Network-connected vehicles will no longer be restricted by line-of-sight limitations, they will have “eyes” everywhere.
Infotainment or Digital Cockpit – Use Case #2
Vehicle user experience is heavily influenced by cellular and because of this, the automakers are seeking ways to enhance their infotainment offering. Rich, in-vehicle experiences will be provided by high-resolution multi-displays, video for passenger displays, premium audio experiences and 3D maps. Enhanced 5G network communication, with fast and reliable access will facilitate these in-vehicle experiences.
Automakers want to deliver a user experience to their customers, particularly focused on providing services over the 5G network. Specifically, over-the-air updates, allowing the vehicle to update or repair itself i) while driving or ii) while parked overnight in the owner’s garage. In turn, this eliminates the need for vehicle owners to have to visit auto service centers to obtain the same upgrades.
Ultimately, auto makers want the ability to offer over-the-air upgrades or packages, similar to the functionality of an App Store on a smartphone or an in-home entertainment system. A recent KPMG survey found that 85% of automakers think that, in the future, the digital ecosystem for automotive (i.e., App Store) will generate much higher profits than the vehicle itself. Examples of these “App Store”-like packages include:
Remote Surveillance Mode on a Vehicle
Enables the ability to use the ultrasonic sensors and the cameras on a vehicle to determine if the vehicle’s alarm system was triggered by an attempted break-in or was a false alarm, set-off by an innocuous contact.
Driver and Occupant Monitoring
Important for monitoring drowsiness, medical conditions, fitness, wellness, and for personalization purposes.
Heads-up displays allow for augmented reality, natural voice prompts, natural language processing and gesturing in the vehicle. Therefore, the driver does not have to look down to push controls or touch screens. Instead, the driver will be able to keep their eyes on the road and hands on the wheel.
With heads-up displays, drivers can utilize augmented reality representations of the road and be able to adjust driving controls through non-physical means. Examples of these non-physical means include through voice or gestures.
Advanced Driver-Assistance Programs (ADAS) and Autonomous Driving – Use Case #3
ADAS and autonomous driving will rely on 5G’s step-function improvement in i) speed, ii) latency and iii) capacity, to deliver new levels of safety, efficiency, and convenience for consumers. Implementation will be through a progressive, staged adoption of driver assistance features over the next few years. Features including sign recognition, emergency braking and adaptive cruise control are going to be key areas of enhancement for ADAS and autonomous driving for the next 5 years.
Particularly relevant for ADAS, is artificial intelligence, which plays an incredibly central role in providing adjustable and continuously improving algorithms. Enhanced algorithms will allow drivers to slowly and incrementally, reduce their control of the functions that govern the vehicle. Instead, drivers will let the machine handle these functions.
With the larger amounts of data created as a result of artificial intelligence, 5G acts as a fast transport mechanism to data centers. In turn, these data centers provide central locations for processing that information with artificial intelligence technology for use in autonomous vehicles.
Cloud Management – Use Case #4
Autonomous vehicles will generate data at an unprecedented scale. Therefore, access to the cloud is critical, to process data, because local processing power within vehicles will not be sufficient.
Cloud connectivity will begin extending itself closer to the network edge, in order to take advantage of the low latency that is enabled by 5G. With this edge architecture, computational offload is possible, whereby data is sent from a vehicle to an edge data center.
For example, in order for autonomous driving to develop further, artificial intelligence is a fundamental technology that becomes part of the ecosystem. However, to be used in autonomous vehicles, artificial intelligence processing cannot be done in the cloud, and sent back to the vehicle, because there is too much latency in that round-trip path. Therefore, all that processing needs to be done on the device, which in this case, is the vehicle itself, or at edge data center locations. These edge data centers, can mitigate the latency issues of the cloud, by being physically closer to the vehicle.
Digital Infrastructure for Autonomous Vehicles
Digital Infrastructure is the physical link driving 5G connectivity as Internet traffic, mobile data traffic, and data storage needs increase. The four sectors of digital infrastructure, include Towers, Data Centers, Fiber, and Small Cells & Distributed Antenna Systems. Below are some highlights of how 5G and each type of digital infrastructure will co-exist.
Towers and Small Cells
Cellular towers support autonomous vehicles by sending the critical wireless signals to these vehicles. Specifically, towers will broadcast over the 5.9 GHz spectrum band. Additionally, the Internet of Things sensors powering Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) technologies reside on small cell infrastructure.
Ultimately, at the edge of these wireless networks are applications sitting in either edge data centers or are being backhauled or fronthauled to a network operation center (NOC). Importantly, artificial intelligence processing resides at these network operation centers (NOCs). In turn, it is this artificial intelligence that drives the autonomous vehicle, delivering a precise set of parameters and performance.
Edge Data Centers
Data consumption by an autonomous vehicle is massive because the vehicle is constantly processing its on-board mapping data and sending that information back-and-forth to the cloud, to ensure the map has not changed. For example, this data can include whether there is debris in the road or a road closure.
However, the majority of the time, the vehicle’s map has not changed and thus the autonomous vehicle does not need to update its on-board maps in real-time. Therefore, sending that mapping information back to a cloud data center, in Northern Virginia (a key data center hub), does not make sense, because most of the data is unnecessary, as it has not changed.
By using edge compute and 5G networks, the autonomous vehicle can filter out the data that has not changed at an edge data center location. Therefore, the vehicle only needs to send back to the cloud, the data that needs to be analyzed. Once the autonomous vehicle analyzes the data, it can then update its system.
By having this intermediate, edge computing step, it allows 5G networks to operate much more efficiently. Indeed, autonomous vehicles will process immense volumes of data. Therefore, edge computing and edge data centers will be an absolute necessity in the future.
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