As we enter a period of autonomous vehicle pilot deployments it is instructive to understand how far we’ve come in making these vehicles an achievable reality, and what we still need to accomplish before autonomous fleets can address the mobility goals, we’ve set for consumer transportation and logistics. Technological innovation and adoption typically follow particular lifecycles. Think of the portable music players. Driverless mobility, comprising of on-demand mobility services and autonomous vehicles, is no exception. This post presents an analysis of the autonomous vehicles innovation lifecycle. It introduces four dimensions for assessing AV innovation performance over time. Finally, it presents six requirements that will need to be addressed before the use of autonomous vehicles can scale for consumer transportation and logistics.Continue reading
The congressional and European Parliament testimonies of Facebook’s CEO focused attention on Internet and ecommerce corporations and startups whose business models rely on the collection and exploitation of big data, with personal data being a major component. Legislators and the public at large came to realize a) the leverage such companies now possess through the dominant positions of the free and frequently personalized services they offer in exchange for the data they collect, b) the risks associated with not properly safeguarding this data, c) the legislators lack of detailed understanding about how the data is collected and used by these companies and their partners, and d) how difficult it will be to regulate the collection, processing, AI-based exploitation, and use of this data in a way that is agreeable to both consumers and businesses. These issues are re-emerging as more connected vehicles are shipped and will become more critical as companies using autonomous vehicles in a variety of services start to employ big data in insights-enabled business models. As we consider the monetization of transportation-related data it is necessary to understand who the main generators and users of this data are, who owns each type of generated data, the risks that may arise from mishandling the collected data, and whether existing and proposed regulations relating to autonomous vehicles and more broadly next-generation mobility suffice or need to be augmented.
In my book and previous posts I build a broad case for the key role big data and AI play in next-generation mobility, and provide several examples from transportation and logistics. Next-generation mobility is about intelligent, connected vehicles that utilize some form of electrified propulsion, and on-demand shared transport services of people and goods that will be offered through such vehicles. Many of these vehicles will be capable of autonomous movement. Next-generation mobility will help us address some of our biggest challenges, such as pollution and climate change, urbanization and congestion, aging population, and traffic fatalities, while enabling us to maintain economic prosperity by operating highly optimized supply chains that span the globe. It will give rise to a new value chain where big data and AI will play a key role. It is therefore important to identify the new monetization opportunities enabled by big data and AI in the context of this value chain.
This post first appeared on 4/27/17 in O’Reilly’s site. It has been revised since it first appeared.
In my book The Big Data Opportunity in Our Driverless Future I make two arguments. First, societal and urban challenges are accelerating the adoption of on-demand personal mobility services. Second, technology advances, including big data and AI, are making next-generation vehicles, and specifically Autonomous Connected and Electrified (ACE) vehicles a reality. I define Next-Generation Mobility as the movement of people and goods using a combination of ACE vehicles, and of transport services such as ride-hailing, car sharing, ridesharing, and others that are offered on a short-time, on-demand or as-needed basis. Next-Generation Mobility will cause three major shifts that can lead to the disruption of the automotive and transportation industries: a consumer shift, an automotive industry shift, and a mobility services shift.
In a series of posts, starting with this one, I examine what is causing these shifts, one of the value chains that is emerging as a result of these shifts, big data’s and AI’s key roles in the value chain, and the models being created around this value chain.
The Consumer Electronics Show (CES) is starting later this week and will be followed by the Detroit Auto Show (DAS). Both shows will serve as venues for the automotive industry to showcase Autonomous Connected Electrified (ACE) vehicles and new Mobility Services. ACE vehicles combined with Mobility Services such as ridesharing, car sharing and multimodal transportation options will give rise to a new personal mobility model that combines car ownership with car access. These innovations and the emerging model are creating two challenges for the automotive industry.