Instructions for ASU collaborators

These instructions are tailored to the ASU Transportation AI Lab.

The most important tip: ask questions! File an issue, email dabreegster@gmail.com, or ask for a Slack invite.

Installing

A new version is released every Sunday, but you probably don't need to update every week.

1. Go to https://github.com/a-b-street/abstreet/releases and download the latest .zip file for Windows, Mac, or Linux.

2. Unzip the folder and run play_abstreet.sh or play_abstreet.bat. If you get security warnings, see here.

3. On the main title screen, click Sandbox. This starts in Seattle by default, so change the map at the top.

4. Choose USA, then Phoenix.

5. You'll be prompted to download some files. It should be quick. After it's done, click Phoenix again.

You've now opened up the Tempe map!

A shortcut and improving the simulation in Tempe

On Windows, edit run_abstreet.bat and change the last line to:

game.exe --dev data/system/us/phoenix/maps/tempe.bin --infinite_parking 1> ..\\output.txt 2>&1

On Mac, edit run_abstreet.sh and change the last line to:

RUST_BACKTRACE=1 ./game --dev data/system/us/phoenix/maps/tempe.bin --infinite_parking 1> ../output.txt 2>&1

--dev data/system/us/phoenix/maps/tempe.bin will skip the title screen and start on the Tempe map by default; this will save you lots of time.

--infinite_parking disables the parking simulation. By default, there's an unrealistic amount of people walking around Tempe just to reach the spot where their car is parked. We don't have good data yet about on- and off-street parking, so it's best to just make driving trips begin and end at buildings or off the map, without a step to search for parking.

There are a bunch of other startup parameters you can pass here too.

Importing a Grid2Demand scenario

When you run https://github.com/asu-trans-ai-lab/grid2demand, you get an input_agents.csv file. You can import this into A/B Street as a scenario.

1. Change the traffic from none

2. Click import Grid2Demand data

3. Choose your input_agents.csv file

4. A new scenario will be imported. Later you can launch this from the same menu; the scenario will be called grid2demand

Grid2Demand needs a .osm file as input. The extract of Tempe that A/B Street uses is at https://abstreet.s3.us-east-2.amazonaws.com/dev/data/input/us/phoenix/osm/tempe.osm.gz. Note the file is compressed.

Modifying a scenario

You can transform a scenario before simulating it. This example will cancel all walking and biking trips from the scenario, only leaving driving and public transit.

1. After loading a scenario, click 0 modifications to traffic patterns

2. Click Change trip mode

3. Select the types of trips that you want to transform, and change them to cancel. Click Apply.

Importing Vol2Timing data

https://github.com/asu-trans-ai-lab/Vol2Timing/ produces timing.csv files that you can import into A/B Street.

1. Open the traffic signal editor for an intersection in A/B Street.

2. Click Edit entire signal

3. Choose import from a new GMNS timing.csv, then pick your file.

The import process isn't finished yet; some movements aren't matched properly, some movements are incorrectly marked as protected, and no crosswalks are imported yet. When you import, some error messages may be displayed, and others might wind up printed to STDOUT (captured in output.txt on Windows).

If you want to import timing for more intersections in the same map, after Edit entire signal, you should also have n option like import from GMNS C:\path\to\timing.csv.

Debugging timing.csv

Along with QGIS, you can also visualize timing.csv in A/B Street directly.

1. From the title screen, choose Internal dev tools.

2. Change the map if necessary.

3. Click view KML.

4. Click load KML file, then choose your timing.csv.

5. Each movement is drawn in red. You can hover over a line-string to see its attributes, and click to open all details.

6. Using the key=value filter on the left, you can type in no=3 to match stage_no=3 and easily check what movements belong to each stage.