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Autonomous Driving Business Models: Part Two

Autonomous Driving Business Models: Part Two

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In my previous article, we discussed various drivers of business models and the way it will change cities, roads, parking, commuting, leisure and ownership while creating new jobs. In this follow-up piece to part one, we will explore a few more business models enabled by specific technologies.

Augmented Reality

Augmented reality creates sensor-enabled overlays for autonomous driving. They will play an essential role in the transition to Level 5 (i.e., full autonomy). The HUDs (head-up displays), navigation systems, personalized content and safety features impart holographic intelligence to the AV. Augmented reality can be monetized in the form of products, services or data.

5G And Edge Computing

Enabling real-time use cases such as autonomous driving requires 5G to be ubiquitous and located close to points of consumption (e.g., the edge for higher speeds and lower latency). The traditional telecom operators have been investing heavily in 5G, which will help them monetize data, bandwidth, capacity through subscriptions, usage and hybrid business models. Provisioning edge networks at remote locations will create new business models.

V2X (Vehicle To Everything)

V2X is the key connectivity and communication layer between vehicles and everything — people (V2P), infrastructure (V2I) and other vehicles (V2V). They can enable services like self-parking, remote diagnostics, monitoring and more. V2V will be revolutionary with instant data shared on vehicle position, speed, road conditions and weather conditions. New marketplaces and services and selling route priority and condition-based feature upgrades will become potential business models.

Blockchain

Blockchain has the potential to be the ecosystem glue within the AV value chain through decentralization. Use cases are centered on cooperation between manufacturers, OEMs and mobility companies. Blockchain can also play a critical role in bundling, storing and transmitting auto data with immutability and integrity. Other use cases are around supply chains or ensuring V2X interference prevention. Blockchain business models include providing infrastructure, scalability, security or enforcement as a service to the AV value chain.

Artificial Intelligence And Big Data

Big data and AI will be embedded into every function and aspect of an autonomous vehicle value chain. Big data collects information from sensors, IoT, mobile phones and V2X interactions. It also enables the creation of road flows for decongestion, diagnostics, marketplaces, new applications, data-enabled instant features and powers AI to learn faster. AI will help monetize big data through machine learning applied on predictive maintenance, condition monitoring and instant OTT upgrades. AI will power many things, including in-car voice assistants, fatigue detection or distraction through eye-tracking and face expression analysis. There will be several use cases and business models enabled through contextual AI and a variety of different in-car, B2B, B2C and ecosystem-level monetization options (e.g., safety, security, entertainment, convenience, emerging technologies).

Smart Sensors

Smart sensors are going to play a role in regulating the operation of autonomous vehicles. They will collect real-time data from LIDARs, RADARs, cameras and other sensors to create a long-range and safe view of the surrounding environment. Typical business models will be based on volumes of data and services enabled by the applications or APIs (e.g., dust cleaning, increased functionality in extreme weather, etc.).

Virtual Reality

VR is going to shift the aesthetics and interiors of a car and add desirable locations, ambience or activities to commutes. VR can make the interior of a car look like an office, a gymnasium or a vacation spot. Virtual reality can also enable spatial computing, which will find many different use cases, drawing compute from either the autonomous vehicle itself, the edge or the cloud depending on the use case. There will be several business models enabled around virtual reality and monetized in a variety of different ways.

Electrification

Most if not all autonomous cars will be electrically powered. As battery life and infrastructure evolve, one will see new business models such as energy as a service or EV chargers as a product, platform, marketplace, service or timeshare. Fleet-level electrification will create economies of scale and will reduce maintenance and downtime costs, making business models like MaaS (mobility as a service) mainstream with ARS (autonomous ridesharing).

Advanced Materials

Advanced materials (i.e., those that are lighter, safer and more robust) will be pivotal for scaling autonomous driving globally. Migrating out from steel reduces consumption and creates modularity while maintaining weight and safety. Advanced materials will also enable 3-D printing and additive manufacturing, creating efficiency in both design and assembly. Business models will mostly be centered on OEMs and suppliers through manufacturing.

HD Mapping

Standard-definition maps with GPS-based turning have not worked; hence, developers have sought more precision and accuracy. The accuracy needs to progress from road level to incorporate one’s driving lane, corners, and curb-position level. These maps must be three dimensional, computerized and highly detailed, needing high-definition technology to make them accurate. HD maps can be monetized in several ways, including subscriptions, usage, regional sales, one-time use and more.

Electronic Control Systems

ECS systems control one or more electrical systems or sub-systems. They are embedded into the car and replace legacy mechanical functions like braking, steering or shifting gears by building in automation. One can explore business models with enhanced features over and above basic safety and comfort being monetized at a premium.

Self-Healing Technologies

The sheer volume and velocity of data generated by cars, infrastructure and sensors will be difficult for humans to log, monitor, report and fix. The paradigm will change from post-facto operational fixes to preventive and autonomous healing or components and functionality. Autonomous prevention, detection and correction systems enabled by ML and deep learning will come into play. They will be monetized through OEMs, the insurance value chain and infrastructure providers.

Conclusion

The autonomous driving value chain will comprise multiple technologies, ecosystems and stakeholders even outside of traditional automakers. Many of these technologies are evolving at different speeds as they get embedded into the autonomous driving value chain.

Source: www.forbes.com

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