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Team: Carlos Azevedo, Emma DeSoto, Ali Shamshiripour, Jinping (Jenna) Guan,  Moshe Ben-Akiva, Ravi Seshardi

New SAV/mobility services are often offered to customers via a mobility as a service (MaaS) platform. Mobility as a Service (MaaS) is a user-centric, digital and intelligent mobility service provision model in which passenger travel needs are met via a single platform. MaaS promises to bridge the gap between public and private operators by integrating currently fragmented services required to conduct a trip. Although MaaS has garnered increasing interest, its broader impacts remain uncertain. 

Therefore, the project aims to:  

1) Assess behavioral changes in response to the introduction of new shared autonomous vehicle (SAV) and  mobility services, including  modal-shifts across different types of cities. 

2) Quantify the system impacts of new AV/mobility services, including congestion and vehicle miles travelled, across different types of cities. 

3) Find optimal solutions for AV/mobility deployments balancing the interests of customers, fleet operators, and cities that could be scaled across cities of the same type. 

This study will leverage SimMobility — an activity-based, agent-based travel simulation platform— and three calibrated city simulation models developed by the ITS Lab. The city simulation models were built during a previous study which collected data from 300 cities around the world and used factor analysis to identify 12 urban typologies representing the heterogeneity in population, land use, transport networks and travel patterns across world cities. 

For each of the three typologies which are most prevalent in the US, (Auto-Sprawl, Auto-Innovative, and MassTransit- Heavyweight), a representative city was selected as the basis for a simulation model. These “prototype city” simulation models were built and validated using road networks from real cities (Baltimore, Boston, and Singapore). Real data from cities in each of the three respective typologies was used to derive generalized populations, land use, transit services, and travel patterns for calibrating the simulations. The resulting prototype city simulations provide highly granular results for various MaaS interventions and strategies as the simulations are conducted at the city-wide scale with incremental time steps of 5 secs. 

SimMobility provides the capability of simulating model cities from each typology to produce actionable insights in different types of markets like Detroit, Baltimore, Phoenix, and Las Vegas (classified into Auto-Sprawl), Miami, Chicago, Boston, Washington DC, San Francisco, Los Angeles, and Toronto (classified into Auto-Innovative), and New York, Berlin, Madrid, and Singapore (classified as Mass-Transit-Heavyweight). ITS Lab aims to build out prototype cities from the other 9 type categories so that findings could be scaled to the global scale. No other project is simulating cities on the same platform in this way.

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