Big Data Driving the Driverless Car: Digitizing Travel A major change to driving and travel is soon upon us. With little doubt, we can expect driverless cars in the next decade or so. However, it is not driverless cars that will change how we travel, but rather the digitization of travel, enabling driverless cars, which will change how we travel. In the earliest versions of automated cars, driverless automation was approached mechanically. An early version proposed vehicles locking into a monorail when on the interstate, for instance. Similarly, early versions of speed control were simply mechanical means for keeping the speed at a designated level, with no specific measuring of the surroundings. The development of sensors and rapid digital processing on cars changed the paradigm for control of the vehicle and its subsystems. Mechanics would be controlled by data, not uber mechanics. Instead of controlling mechanics by brute force, sensors and data allow or a more precise and agile adaption to how vehicles are operated. This paradigm shift and movement to data creation for the purposes of mechanical control has already overtaken the next generation of aircraft. A single flight on a Boeing 787 is estimated to create no less than half a TB of data from sensors. This data is, in many ways, data exhaust. The byproduct of proactive sensors and devices communicating their status and conditions around them. It is reflected in the Internet of Things (IoT) and how connected devices communicate their status even if action is not taking place. Just being connected will create data! Location, availability, and operating status are just some of the basic measures that can be captured on a continuous basis for any autonomous vehicles (even before trip begins). Once a trip is undertaken, data about the trip, deviations from the expected course, energy use, system performance, and specific environmental, traffic, and road interactions are captured. All of this is Big Data that is valuable to engineers, customers, regulators, and other businesses. The future of driverless vehicles includes a radical change in how we travel, owing to the digitization of travel. Soon, we will be able to open an app on our smartphones and summon a driverless car. It might come from Google, Uber, Apple, or a traditional automobile manufacturer. The collection of data begins even before the trip begins. In many ways, the wave of Big Data has digitized vehicle use already. Consider how Uber has digitized car services already. Owning a car is less critical if instead in can be summoned with high reliability and at a reasonable cost, as also in the case of Uber. Data about demand and supply of cars is currently used by Uber to price trips. Once driverless cars are available on demand, digitization of travel will create a new market for travel and the opportunity to seek out new efficiencies on when and how to travel. Data is created about the trip at a granular level allowing for new optimal decisions. In fact, the digital layer controls everything about the trip. By digitizing travel, travel by time of day, destination, route, and even purpose can be ascertained and used to make new optimal decisions. Might this suggest differential pricing? Sure it does. Want to go faster, you can pay for that. Taking the kids to school? Perhaps the local school district picks up part of the cost for the trip. Want to save on travel costs; your driverless car might suggest using the roads at non-peak hours or making long-distance trips at night. Taxing bodies might see the digitization of travel as a convenient means to tax trips based on distance, speed, energy use, or even just popularity and convenience of a road. You get a bill (on your app of course) that includes payments to all the invested parties: driverless car provider, tolls for roads, insurance, and energy use. The implications for how we travel and use vehicles are endless once we have digitized travel. The prerequisite digitized maps are now in place. Sensors allow Google’s driverless car to regularly travel on roads with traffic. Mobile technology is ready to interface with users. Digitizing travel will require Big Data and make new Big Data that will create new markets or travelers and travel providers. It will also change how we travel and pay for travel.

Big Data and Analytics, Digital Strategy

Big Data Driving the Driverless Car: Digitizing Travel

28 Feb , 2015  

Big Data Driving the Driverless Car: Digitizing Travel

A major change to driving and travel is soon upon us. With little doubt, we can expect driverless cars in the next decade or so. However, it is not driverless cars that will change how we travel, but rather the digitization of travel, enabling driverless cars, which will change how we travel.

In the earliest versions of automated cars, driverless automation was approached mechanically. An early version proposed vehicles locking into a monorail when on the interstate, for instance. Similarly, early versions of speed control were simply mechanical means for keeping the speed at a designated level, with no specific measuring of the surroundings. The development of sensors and rapid digital processing on cars changed the paradigm for control of the vehicle and its subsystems. Mechanics would be controlled by data, not uber mechanics.

Instead of controlling mechanics by brute force, sensors and data allow or a more precise and agile adaption to how vehicles are operated. This paradigm shift and movement to data creation for the purposes of mechanical control has already overtaken the next generation of aircraft. A single flight on a Boeing 787 is estimated to create no less than half a TB of data from sensors. This data is, in many ways, data exhaust. The byproduct of proactive sensors and devices communicating their status and conditions around them. It is reflected in the Internet of Things (IoT) and how connected devices communicate their status even if action is not taking place. Just being connected will create data!

Location, availability, and operating status are just some of the basic measures that can be captured on a continuous basis for any autonomous vehicles (even before trip begins). Once a trip is undertaken, data about the trip, deviations from the expected course, energy use, system performance, and specific environmental, traffic, and road interactions are captured. All of this is Big Data that is valuable to engineers, customers, regulators, and other businesses.

The future of driverless vehicles includes a radical change in how we travel, owing to the digitization of travel. Soon, we will be able to open an app on our smartphones and summon a driverless car. It might come from Google, Uber, Apple, or a traditional automobile manufacturer. The collection of data begins even before the trip begins. In many ways, the wave of Big Data has digitized vehicle use already. Consider how Uber has digitized car services already. Owning a car is less critical if instead in can be summoned with high reliability and at a reasonable cost, as also in the case of Uber. Data about demand and supply of cars is currently used by Uber to price trips. Once driverless cars are available on demand, digitization of travel will create a new market for travel and the opportunity to seek out new efficiencies on when and how to travel. Data is created about the trip at a granular level allowing for new optimal decisions. In fact, the digital layer controls everything about the trip.

By digitizing travel, travel by time of day, destination, route, and even purpose can be ascertained and used to make new optimal decisions. Might this suggest differential pricing? Sure it does. Want to go faster, you can pay for that. Taking the kids to school? Perhaps the local school district picks up part of the cost for the trip. Want to save on travel costs; your driverless car might suggest using the roads at non-peak hours or making long-distance trips at night. Taxing bodies might see the digitization of travel as a convenient means to tax trips based on distance, speed, energy use, or even just popularity and convenience of a road. You get a bill (on your app of course) that includes payments to all the invested parties: driverless car provider, tolls for roads, insurance, and energy use. The implications for how we travel and use vehicles are endless once we have digitized travel. The prerequisite digitized maps are now in place. Sensors allow Google’s driverless car to regularly travel on roads with traffic. Mobile technology is ready to interface with users. Digitizing travel will require Big Data and make new Big Data that will create new markets or travelers and travel providers. It will also change how we travel and pay for travel.

Professor Walker provides keynote talks, seminars presentations, executive training programs, and executive briefings.

Recent talk topics enjoyed by clients have included:

From Big Data to Big Profits: Getting the Most from Your Data and Analytics”

“Data Monetization”

“Leveraging Artificial Intelligence and Automation at Work”

“Winner Take All – Digital Strategy: From Data to Dominance”

“Success with an Inter-Generational Workforce: From Boomers to Millennials”

“FinTech, Payments, and Economic Trends and Outlooks in Consumer Lending”

“The World in 2050: Risks and Opportunities Ahead”

Exceptional executive training programs have included:

“Digital Disruption, Automation, Analytics, Data Science, the IoT, and the Big Data Wave”

“Master Course on Operational Risk: Measurement, Management, Leadership”

“Complete Course in Risk Management: Credit, Market, Operational, and Enterprise Risk”

“Cyber-security Training: Prevention, Preparation, and Post-Analysis”

“Managing Your Brand and Reputation in a Crisis.”

“Strategic Data-Driven Marketing”

“Enterprise Risk Management and the CRO”

Professor Walker has provided these talks and programs to leading firms and governmental organizations. Click here to learn more about his talks, references from clients, options for customized talks and programs, and details on scheduling a program for your organization.

, , , , , , , , , , , , , , , ,

By  -      
Russell Walker helps companies develop strategies to manage Risk and harness value through Analytics and Big Data. As Clinical Professor at the Kellogg School of Management of Northwestern University, Russell Walker has developed and taught leading executive programs on Big Data and Analytics, Strategic Data-Driven Marketing, Enterprise Risk, Operational Risk, and Global Leadership. He founded and teaches the popular Analytical Consulting Lab and Risk Lab, experiential classes, which bring Kellogg MBAs together with real-world projects in Analytics and risk evaluation. His is the author of the book From Big Data to Big Profits: Success with Data and Analytics (Oxford University Press, 2015) which examines data monetization strategies and the development of data-centric business models in the new digital economy. He is also the author of the award-winning text Winning with Risk Management (World Scientific Publishing, 2013), which examines the principles and practice of risk management as a competitive advantage. Dr. Walker consults with firms on the topics of Big Data and Analytics, Risk Management, and International Business Strategy. Russell Walker can be reached at: russell-walker@kellogg.northwestern.edu @RussWalker1492 russellwalkerphd.com



Leave a Reply

Your email address will not be published. Required fields are marked *