 The city of Boston. How will autonomous vehicles change the look and feel of the city? What will the impact on traffic flow and congestion be? How will emissions, space and travel time be affected? To answer these questions, we developed a highly complex, agent-based model simulating real-life traffic flows in Boston. We modeled thousands of agents and their behaviors, different vehicle types traveling through the city, the city streets, traffic lights and pedestrians. We focused on the core of downtown Boston. It is a small but busy part of the city, spanning 0.45 square kilometers, with 35 kilometers of roadways and sidewalks and more than 180,000 trips per day from an origin to a specific destination. There are three types of vehicles in our simulation of Boston today. The personal car, public transit, as well as taxis and e-hailing, such as Uber and Lyft. In our study area, public transit accounts for more than half of the trips, the personal car for one-third and taxis and e-hailing for the remaining 11%. In addition to these existing travel modes, in the not too distant future, there are new autonomous vehicles available in the city of Boston and elsewhere in the world. The autonomous personal car, the autonomous taxi, the rideshared autonomous taxi, the autonomous minibus. Now let's look at two ways mobility in Boston could play out with those transport modes. Scenario one, the private car evolution. In this scenario, one-third of the users of private cars switch to self-driving private cars, half of which are electric. One-third keeps their traditional car, while the remaining third switches to the self-driving taxi. Every tenth public transit user switches to using more convenient and point-to-point mobility offered by self-driving taxis and shared self-driving taxis. As a result, half of the trips are taken by public transit, 11% by traditional private car, 11% by self-driving private car, twice as many by rideshared self-driving taxi, and only a few trips by self-driving taxi. The city benefits from this scenario, but it does not transform dramatically. The number of vehicles on the street falls. Vehicle distance traveled rises because taxis drive empty to pick up and drop off passengers. Traffic flows more fluidly and smoothly. Emissions decrease because part of the autonomous vehicle fleet is electrified. Scenario two, the robo-transport revolution. In this scenario, we observe a strong shift towards shared, electric, autonomous transportation. All trips done previously by personal car are now taken by self-driving taxi with and without ride-sharing, as well as by minibus. In addition, two-fifths of public transport trips are now done by one of the new autonomous shared transport modes. This is the resulting modal mix. Only one-third of trips are completed by public transit, one-third by self-driving minibus, one-fourth by self-driving taxi, and the remaining 14% by shared self-driving taxi. The impact of such a new reality on the city of Boston is disruptive. The number of vehicles decreases by one-third. Travel time and average speed improve considerably as residents' commute gets more and more predictable, especially during morning peak hours. Emissions fall steeply due to the fact that most AVs are electric. Space is gained because fewer cars need parking in our study area. The city's transportation system is now substantially more efficient and reliable, more spacious and more sustainable.