Can Self-Driving Cars Stop the Urban Mobility Meltdown?
This study uses five urban archetypes to form the bases of a simulation tool to explore how autonomous vehicles (AVs) could impact different cities in the future. The archetypes are: highly compact middleweight city; car-centric giant; prosperous innovation center; developing urban powerhouse; and high-density megacity. Policy-based scenarios were simulated and six key performance indicators (KPIs) were investigated: transportation costs, energy consumption, parking space, fatalities, travel time, and traffic volume. Mobility options examined include private automobile, public transportation, ridehailing, robo-pod, robo-taxi, robo-shuttle, micromobility, and walking. In a scenario where city inhabitants had the option of using AVs, improvements included: a 13% decline in transportation costs, a 12% decline in energy consumption, an average of 35% less land area needed for parking, a 37% decline in fatalities, a 3% decline in journey time, and a decline in traffic volume by 4%. Additional scenarios explored include: (1) shift from private cars to non-AV transportation modes, (2) micromobility (e-bikes and e-scooters) increases substantially, (3) shared robo-taxis and robo-shuttles are adopted, (4) small robo-pods dominate the modal split.
- Record URL:
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Corporate Authors:
Boston Consulting Group
,University of St. Gallen
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Authors:
- Lang, Nikolaus
- Herrmann, Andreas
- Hagenmaier, Markus
- Richter, Maximilian Alexander
- Publication Date: 2020-7
Language
- English
Media Info
- Media Type: Digital/other
- Features: Figures; Tables;
- Pagination: 27p
Subject/Index Terms
- TRT Terms: Autonomous vehicles; Cities; Forecasting; Impacts; Mobility; Modal split; Simulation; Vehicle sharing
- Subject Areas: Highways; Passenger Transportation; Planning and Forecasting; Vehicles and Equipment;
Filing Info
- Accession Number: 01774596
- Record Type: Publication
- Files: TRIS
- Created Date: Jun 22 2021 2:22PM