Gallery

Below are some screenshots taken of the different city maps generated by the simulator in its early development stage, highlighting some of the features and data it is able to utilize. Some of the maps shown below have their utility pole data displayed in orange. All maps shown below have five routes plotted in various colors, with a car and number label for each. This model below being demonstrated would be the "consumer vehicle" model, that is, random personal vehicles driving from point A to B throughout the city.

Here is a close-up of the street network and generated routes for Washington, as well as the utility pole data:

Here are some of the specific features of our simulation:

Here is a screenshot of the simulator's GUI in its early development stage, before we began migrating to a more robust and customizable GUI using PyQt (currently it is using MatplotLib). We can see the GTFS utility pole data in orange and the different generated routes in various colors, with a car and number label for each. This model below being demonstrated would be the "consumer vehicle" model, that is, random personal vehicles driving from point A to B throughout the city.

As you can see above, the final simulator will contain a few key elements in its GUI. It will have a play/pause button (not shown), a slider to iterate over the frames of the animation, a textbox to jump to a specific point in the animation, and a button to toggle the visibility of the sensed poles. Pan/zoom controls have already been implemented to easily navigate the map by using the mouse buttons.

Above we can see the basis of the configuration file that will be passed to the simulator. Here we can define different parameters for our simulator based on what we want to do experimentally. We will be able to define whether we want an animation or just an output of data to a file, whether we want to simulate taxis, busses or consumer vehicles, the sensing radius of our vehicles, etc.