The Future of Enhanced Mobility | The 4 ACES - Mobilitys autonomous future
Dr. Evangelo Damigos; PhD | Head of Digital Futures Research Desk
- Electric Vehicles
- Connected Intelligence
Publication | Update: Mar 2020
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According to the Mckinsey perspective ‘The trends transforming mobility’s future’, the levels of disruption coming over the next dozen years are likely to exceed those of the previous 50 or more.
In this context, four trends - ACES: autonomous driving, connectivity, the electrification of vehicles, and shared mobility, are identified by Mckinsey.
The global revenues associated with AVs in urban areas could reach 1.6 trillion a year in 2030.
Companies are enhancing their systems for developing integrated platforms and promote cross-functional activities among its business fields, including semiconductors, sensors and motors.
Nearly every auto OEM and major supplier has an AV project in progress, aimed at reshaping the very nature of how people experience mobility. To better understand the size and scope of the AV opportunity, the McKinsey Center for Future Mobility modeled more than 40 transportation use cases across a global mix of urban and highway settings, and under a range of technological, economic, and other conditions.
Nearly one-third of the benefit would arise from the public sector’s redevelopment of unnecessary parking spaces into more productive commercial or residential property. For context, the amount of land taken up by car parking in Los Angeles is more than 17 million square meters—equivalent to nearly 1,400 soccer fields.
About 15 percent would accrue annually to workers in the form of more productive commuting time. Further, we anticipate a yearly benefit of about one-half of 1 percent (somewhat less than 4 billion) in the form of reduced environmental damage, since, for example, more efficiently utilized vehicles idle less than others do.
Finally, more than half of the benefits would stem from safer roadways and the avoidance of the millions of fatal and nonfatal accidents caused each year by human error. A comparable analysis of Germany found that by 2040, self-driving vehicles could save the country €1.2 billion a year through lower costs for hospital stays, rehabilitation, and medication alone.
Though not all the impact of the AV-driven future are as positive as saved lives. The insurance industry, for example, could face disruption if revenues from premiums shrink and new issues of liability arise; alcohol consumption could well increase as cars become more of a living space, energy consumption would rise as self-driving cars, despite their efficiency, tap new pools of demand; and, most worryingly for cities, revenues from vehicle taxes and licensing fees would decrease dramatically.
The improved capabilities of 5G make autonomous driving more feasible, and more trustworthy.
According to Noah Waldman of Here360, 5G technology presents opportunities for automated vehicles and connected mobility, to carry out critical communications for safer driving, support enhanced V2X, and connected mobility solutions.
“5G will usher in the future of the automotive and telecommunications industries by enabling new in-car services, enhanced safety and autonomous driving,” said Edzard Overbeek, CEO of HERE360.
“We’re moving from being just a hardware provider to being a hardware, software, and experiences provider,” says Don Butler, head of Connected Vehicle and Services for Ford Motor Company. “The future is going to be different, and we are embracing that difference, and we’ll continue to be a part of people’s lives.”
Considering the 280 hours per year the average American spends behind the wheel, there’s real pressure to make that time productive, or at least entertaining, and it’s turning your car into an intensely personalized and customized extension of yourself.
The increased speed and capacity of 5G compared to other wireless standards increases the level of efficiency and safety that autonomous vehicles would be able to deliver to drivers and pedestrians alike. The increased bandwidth would allow connected cars to receive constant updates from other 5G-connected devices: a pedestrian's cell phone, other cars, traffic infrastructure, and more – giving the vehicles a clearer and more accurate picture of the what's around them and what awaits them down the road. The increased speed would allow them to communicate and react faster to everything the cars share a that road with.
For example, in live demonstrations performed in Turin, 5G connected cars were able to identify and react to pedestrians crossing in front of them, a connected bike riding beside them, and other cars that presented collision risks on straight ways and cross junctions. Additionally, 5G would enable “see-through” functions to help drivers avoid dangerous overtaking. Emergency services would be able to visualize an emergency situation using on-board cameras of surrounding vehicles, improving response times and providing situational awareness prior to arriving at the scene.
According to Asutosh Padhi senior partner in the McKinsey Chicago office and cofounder of the McKinsey Center for Future Mobility, there are still a couple challenges that remain. “The first one is object detection and categorization, which is the ability of a car, for example, to recognize a pedestrian: this is what it looks like if a pedestrian is pushing a stroller, if the pedestrian is carrying an umbrella, if the pedestrian is carrying a plant, when a pedestrian doesn’t look like a pedestrian, etc. And the second challenge is decision making. When there is human driving, there are a lot of subtle signals that drivers send to each other—right of way, etc.—and often if you’re an autonomous car, you can’t pick those up.”
In relation to testing and validation, being a concern for autonomous-driving-technology readiness Asutosh Padhi said. “There’s going to be a completely new paradigm that has to emerge for testing and validation in the world of autonomous vehicles. In this new world, it is less about driving millions of miles. If you drive millions of good miles, there is, in effect, no new learning that happens. It really is about looking at the millions of edge cases that you’d expect that do not usually happen on a more traditional and a more frequent basis. And it’s about teaching the car and the algorithms to recognize object detection as well as decision making in those edge cases. And what it essentially implies is that you can’t do this through physical validation and testing, because you can’t have a car drive a million miles. You have to borrow techniques that are used around software-based simulation from other industries like gaming as a way to be able to complete the necessary level of validation.”
When it comes to consider what type of autonomous-driving use cases we expect to see in the future, Philipp Kampshoff, a partner in McKinsey’s Houston office and coleads the McKinsey Center for Future Mobility contests: “Let me tie all these elements together to give you a couple of examples of these use cases. If we talk about transport of people in an urban environment [with AVs] owned by a professional company instead of a private person, then we are talking about the use case of robo-taxis. One question that we are always being asked is, “Is there going to be an Airbnb model of autonomous cars in the future, where people own autonomous vehicles, the autonomous vehicle takes them to work, and then they put it into the mobility-as-a-service system to work for them?” The math suggests that it is difficult for this vehicle to compete with a professional-fleet provider. The reason is that the professional-fleet provider, just because of economies of scale and purchasing power of not buying just one car but many, will get a different purchase price. They will be much more professional in terms of servicing and maintaining the fleet. And likely, the utilization of the car is going to be higher, too. So they will be able to operate at a different cost point in comparison to a private person who owns an AV and brings that into the system to work as a robo-taxi. Most likely we do not see the Airbnb model for robo-taxis, but professional-fleet providers providing that.”
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The degree of necessity. Luxury products and habit forming ones, typically have a higher elasticity.
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