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Change vehicles: How robo-taxis and shuttles will reinvent mobility

McKinsey 11 Jun 2019 12:00

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Modern cities feature an odd mix of excitement, opportunity—and pain. Much of the latter results from getting around: sitting in traffic congestion, hunting for parking spaces, breathing exhaust emissions.

Understanding cities’ problems with private cars

All cities, to a greater or lesser extent, have a problem with private cars. As an example, let’s look at Los Angeles. Today, it suffers from congestion that leads to an increase in travel time of 44 minutes per day, or 170 hours per year, that are lost for every driver, making it the most congested city in the United States and Western Europe.1 1.TomTom Travel Index, Tom Tom, tomtom.com. The city also aims to address car-related safety issues that it wants to solve with its “Vision Zero” target to reduce traffic deaths and serious injuries to zero by 2025.2 2.“Vision Zero Los Angeles, 2015–2025,” City of Los Angeles, visionzero.lacity.org. Furthermore, public-transportation usage in Los Angeles is low compared with car-based mobility; additionally, Los Angeles, like most other cities, faces emission problems, heading the list of most polluted US cities regarding ozone.3 3.“Most polluted cities,” American Lung Association, lung.org.

However, robo-taxi and shuttle mobility have the potential to disrupt our future mobility behavior and to cannibalize many of the miles people travel each day. This could fulfill daily mobility demands but also may signal the end of mass private-car ownership—at least in high-income urban and suburban areas.

The model is dynamic and regionally sensitive. For example, to model future robo-taxi and shuttle mobility as accurately as possible, we took several perspectives into account. Robo-taxi and shuttle mobility will differ from city to city, for instance. Each city is unique regarding its modal split, public-transport penetration, efficiency, congestion levels, the wage levels of taxi drivers, and so on. Other factors that can differ include the cost of car ownership, the cost of parking, local taxes, city tolls, and so on. These urban markets are also unique in their robo-taxi adoption rates, rollout speeds, feasibility, and city support. Consequently, we used a bottom-up approach, introducing a city-clustering technique using city archetypes, modeling the robo-taxi and shuttle development of selected representative cities, then extrapolating the results to the global market.

The overall speed of adoption will depend on regional differences: the speed of customer adoption and market ramp-up will differ by region according to unique regulations, economics, and other factors. For example, higher driver costs in Europe and the United States mean that robo-taxi mobility will reach an earlier tipping point in those regions than in China, where driver costs are much lower. This will lead to earlier market ramp-up in Europe and the United States.

Additionally, the introduction of potentially safer shared AV mobility options aligns with the city’s goal of reducing the number of traffic deaths and serious accidents.


About the author(s)

Kersten Heineke is a partner in McKinsey’s Frankfurt office, where Benedikt Kloss is a consultant; Philipp Kampshoff is a partner in the Houston office, and Martin Kellner is a consultant in the Munich office.

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Los AngelesMcKinsey Center for Future MobilityUnited StatesLos Angeles CountyEurope
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