Future of mobility 5 technology trends driving the future of mobility
To be successful in the future, mobility manufacturers must stay on top of technological advances and trends. As vehicles become smarter and more automated, vast amounts of technology will be needed to upshift user experience.
Technological advances have progressed the automotive manufacturing industry exponentially in recent years. Building cars for the future—be they autonomous, connected, electric, or a mix of all three—will require even more cutting-edge technology and processes.
To succeed in the new era of mobility, staying abreast of trends and advancements is imperative for automotive manufacturers. There are five main driving factors of the fast-moving mobility industry. So far, it appears just the surface has been scratched on the possibilities for these trends.
5 driving factors of the mobility industry
Buckle up, and we'll now take a closer look at each of the five trends driving the automotive industry.
Big Data and IoT
Lee Bauer, VP at autonomous and driver-assistance systems supplier Aptiv, has inferred that an hour of autonomous driving will generate four terabytes (4TB) of data. Processing that data while maintaining blistering-fast response times for ADAS systems and requires the vehicle to be nothing less than a rolling supercomputer. Storing, sorting, and making sense of this stockpile of data is har work. But, the powerful insights players both in and around the automotive industry can pull from car data are invaluable.
Widespread internet-of-things (IoT) integration will see autonomous vehicles able to communicate with each other on the road. Cars with varying levels of audiovisual (AV) abilities will be able to navigate congested roadways easier, intelligently pay roadway tolls, and reduce accidents from driver error. In short, the applications of car data are endless.
Decentralized Computing Models
As mentioned, 4TB of data per hour is obscenely difficult to process, much less store and pull valuable insights from. Limited onboard data storage would restrict AV integration, but cloud-based computing and data storage paves the way. Whether it's in processing the vast amounts of data, computing it quickly, or providing secure storage for sensitive information, carmakers are working on solutions.
Billions of dollars are being invested in research and development for cloud-based and hybrid computing models where vehicle data is decentralized. Increased accuracy and response times are the goals. And the stakes are high, neither on-road safety nor superior in-cabin experience can be compromised by carmakers looking to get ahead of the curve.
Apple CarPlay and Android Auto, Spotify and Google Music, mapping apps—they're all meant to enhance the user experience and keep occupants connected while in their car. In-car apps offer carmakers the ability to add value to drivers in ways aside from mere entertainment, though.
Connectivity through in-car apps provides an avenue for pertinent driving data such as road conditions, traffic congestion, POIs, and more. Furthermore, in-car apps can be used to display ads tailored after the user's interactions and environment.
Artificial Intelligence in automotive
Artificial Intelligence (AI) is closely tied to computing and IoT, yet AI and machine learning are integral to manufacturing, ADAS systems, and autonomous driving in particular. It's through advanced machine learning algorithms that autonomous cars can handle complex situations and navigate traffic, as is the case in emergency vehicle control, syncing with traffic signals, and monitoring the surrounding driving environment. Rather than counting on often-wrong human reactions, AI is reliable for intelligent, objective actions that rely on sensors and cameras rather than emotions like fear and surprise.
Vehicle manufacturing has become increasingly automated in the past few decades, and the evidence is in an overall better product. Digital factories take it several steps further. At its core, a digital factory uses digital technology to make the manufacturing process more efficient and informed. For the automotive industry, this means that vehicle and parts manufacturers can model the manufacturing process to understand areas of improvement, ensuring quality control and efficiency.
Information is instantly shared between, for example, people, machines, and the supply chain. Digital factories also incorporate robotics and artificial intelligence that can reduce instances of human error and continue production long after a human's work shift is over.
All five of these technology trends are relatively new. They promise to improve vehicle safety and increase manufacturing efficiency and accuracy in the coming years, probably well beyond what we understand right now.