At Fetch.AI we’re focused on how Artificial Intelligence and Machine Learning can come together in a decentralised network to create truly autonomous systems. That’s why we’re part of the recently-announced MOBI consortium with major automotive companies such as BMW, Ford, GM and Renault. Transport is an ideal use case for Fetch, a complex ecosystem of moving parts that are poorly coordinated today, with very limited utilisation of assets.
In this blog we outline how an autonomous system like Fetch.AI can drastically improve coordination and asset utilisation in transport, as detailed in our newly released Transport Whitepaper: Knowledge-based Future of Mobility.
That’s because the owner has little ability to dynamically find others who would pay for their use when they are idle. There is little ability to share vehicle availability across different types of demand (such as package vs. passenger delivery.) The information systems and networks required to easily and flexibly coordinate among, say, private drivers and couriers has traditionally been prohibitively expensive. As a result, cars with empty space that could be used for packages often fight for space on roads with half-full delivery trucks going to the same area.
If anyone wishing to ship a package could query any combination of vehicles going in that direction, and automatically agree on pricing, pickup times and other terms for delivery, the value stranded in an idle, or half empty, private vehicles could be tapped by the vehicle owner.
Think of the gridlock that results from a single accident, at the wrong time, at the wrong intersection. Then think of the space freed up on roads, and the productive time freed up for drivers and passengers, if vehicles could be automatically routed around accidents, weather, congestion and other delays.
All these benefits are impossible today because of siloed transportation modes (such as private and public transport and passenger and freight carriers) provided by a mix of publicly and privately-owned vehicles controlled by millions of owners.
“The greatest obstacle to unlocking the value within today’s transportation infrastructure is the lack of a marketplace including all stakeholders”
Imagine if players ranging from vehicle owners to repair services to insurers to regulators and public safety agencies, can safely and securely exchange and analyze information in real time.
True progress will come not only with the wider sharing of data, but the democratization of knowledge among all players in the mobility ecosystem. This could allow, for example, local governments could to easily tweak pricing and other incentives to ease congestion and pollution. Business models we can only imagine will provide mobility “insights as a service” that let everyone unlock the wealth trapped in their transportation assets and data. The raw material for this knowledge will be more and more data from not only drivers, but vehicles, roads, charging stations and other devices on the Internet of Things.
An open, secure, real-time marketplace for such data will enable instant, dynamic “analytics as a service” in which even small transportation players will provide data, and service providers will deliver insights with no need for customers to invest in expensive data science skills, specialized algorithms or Big Data hardware or software. At the same time, the owner of every asset and data type will be able to realize the value of that data rather than giving it away for free.
With Fetch.AI we can:
* Allow all economic players to easily and instantly find and communicate with each other
* Enable all these players to exchange data and funds safely and securely
* Facilitate autonomous entities, ranging from self-driving cars to smart contracts, to discover each other and conduct transactions as distributed, cloud-based services
We can achieve this because we have significant machine learning and intelligence running through every layer of Fetch and because our unique ledger design can scale to support the millions and probably billions of micro-transactions necessary.