Autonomous Vehicle Storage Simulator

Autonomous Vehicle Storage Simulator

Student Author: 
Brian Liu
Date: 
May 2017
Supervisor(s): 
Maya Przybylski

The introduction of autonomous driving will have an immense impact on the nature of parking currently in place within our cities. It is predicted that autonomous cars will drastically reduce the number of cars on the road as well as reduce personal ownership of vehicles from the increased sharing of vehicles. As a result, the spatial requirements for the parking of vehicles within cities will be drastically reduced. Autonomous technology will also completely transform how we currently use cars. Users would be able to summon an autonomous vehicle to pick them up, be driven to their destination, dropped off and have the vehicle either perform more trips or park itself. This completely removes the need for areas of parking at origins and destinations of a trip. Parking lots and garages could therefore be centralized in more convenient areas and adopt a model similar to that of bike sharing today. Through computational exploration, we can begin to imagine how a network of garages could support a fleet of autonomous vehicles within the city.

The project is intended to be a representation of a future network of public garages within the city of Toronto which can effectively communicate information about itself. A business model similar to that of the shared biking system currently in place could be transferred to apply to a future system of shared public vehicles. A network of garages would be interspersed within the city and vehicles would travel from one to the other. The intended outcome of the code is to create an interactive map of Toronto with markers showing the locations of future garages as well as their characteristics. This would allow both the city government and the users of the public fleet of autonomous vehicles to track the capacity, availability and location of garages throughout the city. Capacity of a garage will be shown through the size of the marker on a map while it’s availability by its color.