David Gee explores the potential ways in which artificial intelligence and edge computing can transform the safety and functionality of vehicles
Connectivity is critical across all aspects of life, and the automotive industry is no different. Globally, more than 400 million connected vehicles will operate by 2025, up from 237 million in 2021. With high-volume, low-latency processing more accessible than ever before and more connected cars on the road, the future of mobility looks bright, and one of the industry’s most promising, high-profile solutions―true Advanced Driver Assistance Systems (ADAS)―is finally within reach.
One report anticipates the global ADAS market will increase to 655 million units by 2030, growing at a CAGR of 11.9% with 150 million in the US alone. Innovations in artificial intelligence (AI) and edge computing will help develop new applications, make production more efficient, optimise fleet management increase safety and dramatically improve driving experiences. AI enables ADAS with better, more nuanced interpretations of on-road situations, while edge technology brings data processing closer to the source to transform insights into actions faster. Together, these technologies are redefining mobility in the automotive industry, creating safer, smarter, and more enjoyable driving experiences for millions of users globally, especially in urban areas.
Connected vehicles are equipped with internet capabilities, allowing them to communicate with devices on the inside and outside. These high-performance supercomputers, servers and workstations deliver responses more quickly than ever before, leading to improvements in three critical areas: safety and reliability, driver experience and community benefits.
Real-time communication between connected vehicles, manufacturers and service providers enables consistent monitoring of vehicle performance and safety. Telematics and remote diagnostics manage data related to a vehicle’s location, speed and driving patterns. This supports performance monitoring and facilitates timely maintenance. It also provides greater insight into a vehicle’s condition and surroundings and helps drivers maintain their vehicles and avoid risk.
The benefits of connectivity services, like GPS and WiFi, offer integrated navigation and expanded entertainment options for passengers. For example, digital car keys make life easier for drivers—they can simply connect their phone to a mobile app from the car’s manufacturer and lock, unlock and auto-start their car conveniently.
Connected vehicles present benefits for communities and local infrastructure as well. Communication between vehicles and transit infrastructure improves road safety, traffic efficiency and experiences on the road. For example, when driving a connected vehicle across Big Sur on a stormy day, a driver could receive an alert about a severe rainstorm, allowing them to change course, focus better and/or exercise more caution. If they encounter a flooded bridge or patch of ice, vehicle-to-everything (V2X) communication allows the car to transmit a signal to transit infrastructure, such as a traffic management centre, which also alerts other vehicles of danger. Expanded V2X capabilities can reduce risks created by inclement weather and traffic congestion as well as bring greater safety for drivers and passengers.
AI brings safer vehicles, safer roads
Automotive applications with AI technology improve driver and passenger safety—an imperative given the increase in incidents and fatalities in the US due to the widespread usage of cell phones. In fact, the number of vehicle-related fatalities in the US outnumbers that of other wealthy countries—including Canada, Germany, Japan and Britain—by up to five times. Growing global awareness of vehicle accidents has led to legislation requiring enhanced safety features like speeding alerts and risk detection technology, further increasing demand for ADAS.
ADAS reduces human error and promotes driver responsiveness and safety. Already widely used in newer models, these systems include features like adaptive cruise control, automated emergency braking and lane-keeping assistance. Since driver error on the road can be fatal, these AI-enabled safety features help save lives while keeping vehicles safe. Sensors can determine vehicles’ proximity to each other and either alert drivers to collision risks or even override drivers’ actions to avoid accidents. AI enables vehicles to process data from many different sources simultaneously and make smart decisions for safer roads.
Applications focused on predictive analytics alert vehicle owners to component failure, as well as key maintenance milestones like oil changes, engine maintenance and tyre rotation. AI maintenance alerts keep vehicles at peak performance while removing the planning burden from drivers.
How edge tech enables mobility transformation
In the pursuit of self- and assisted-driving vehicles, the question of how to process and respond to on-road conditions fast enough to keep drivers and pedestrians safe has stalled progress. For ADAS to function optimally, the system must have reliable, consistent and high-speed access to computing servers—and that’s a tall order at 60 miles per hour, considering that countless factors outside drivers’ or manufacturers’ control impact connection stability and speed. Self-driving vehicles cannot function reliably nor at scale until engineers address this obstacle.
Edge computing—a technology that offers various levels at which connected devices can process data (whether in-device, at the edge or in the cloud)—provides a solution to this persistent challenge. By allocating data processing tasks based on their relative importance to safety or other criteria, edge architecture reduces latency, ensuring high-priority functions (like auto-breaking) are handled as close to the device as possible and lower-priority functions (like maintenance analytics) happen farther away. It also preserves connection quality for each driver and the community by limiting the volume of data that must be transferred to central servers.
The end results are safer, more reliable ADAS and peace of mind for drivers and pedestrians that network errors will not interfere with the vehicle’s ability to stay on the road. Adaptive edge architectures take these benefits even further, allowing an ADAS to automatically adjust processing allocation based on real-time conditions―which is critical in time-sensitive situations wherein small lags can have fatal consequences.
Paving the way for mobility
McKinsey estimates that, by 2030, 95% of vehicles sold worldwide will be connected vehicles and 12% of these vehicles will have autonomous driving capabilities.
As autonomous vehicles become pervasive, edge technology is the platform that makes all of this work. It enables a seamless flow of data in real time to and from vehicles, keeping drivers safe, allowing them to communicate better and enjoy more comfortable experiences on the road. The result is a more seamless and innovative future of mobility.
About the author: David Gee is Director of Product Management at Synadia
